Factsheets: Limiting UK Emissions - User contributions [en-gb]

Nuclear + storage

2024-08-23T08:33:47Z

Trevor:

==Close-coupled nuclear generation & compressed air energy storage (CCNG-CAES)==

This case study – original work © Fluke – illustrates the scale of operation needed to provide 1.1 GW (one gigawatt) of electricity on a twelve hours on, twelve hours off cycle. This could be used for peak shaving renewable energy or balancing periods of low and high demand.

The base case, without storage, is a 2.0 GW (thermal) output nuclear power station producing electricity via steam turbines at a thermodynamic efficiency of one-third (33⅓ %) 24-hours per day, so 0.67 GW (electrical) continuously.

The study case is an identical power station, located adjacent to a large underground void.

It is feasible to use mechanical energy to compress air and place it into the void, which acts as a pressure vessel. The compression takes place in four stages, each compressor being directly driven from the output shaft of a steam turbine. SIX such arrangements in parallel are required to consume the entire thermal steam output and under this operation no electricity is generated.

At other times air is drawn from the store, heated (and reheated) using 43% of the steam output of the nuclear power station as it expands through four stages of air turbine driving generators. The balance of steam 57% is used to generate more electricity from three steam turbines. Again SIX of these lines are required to consume the entire thermal output and the power generation per line is 183 MW so 1.1 GW gross

So comparing cases, without storage the nuclear power station delivers 16 GW-h electricity continuously over a 24-hour period while the CCNG-CAES generates 13.2 GW-h for 12 hours and nothing for the other 12. The analogy is inexact but the system is in effect a 13.2 GW-h battery with a round trip efficiency of 82.5%

It is also informative to compare this with SSE’s Coire Glas pumped hydroelectric scheme – 30 GW-h storage with 1.5 GW input/output https://www.sserenewables.com/hydro/coire-glas/

==Flow diagrams==

The flow diagrams show the overall heat and mass balance for the compression / charging stage and the expansion /discharging stage of the close-coupled nuclear generation & compressed air energy storage operation. The complementary T-s diagrams present an alternative, graphical method of presenting the numerical spreadsheet calculations described below

* [[Media:CCNGCAES.pdf|Flow & T-s (temperature-entropy) diagrams]]

==Void requirement==

Each of six lines handles 850 tonnes per hour (850,000 kg) of air with the void pressure cycling between 5 MPa (50 bar) ‘discharged’ and 6 MPa (60 bar) ‘charged’. Density of air at 35°C at the two pressures is 56.85 kg/m³ and 68.21 kg/m³ respectively; difference is 11.37 kg/m³. One line for one hour therefore requires 74,787 cubic metres, multiplying by 6 lines and by 12 hours gives a total requirement of 5,385,000 m³.

To put this requirement in context, salt mining / extraction creates large volumes of void space and salt mines are favoured locations for compressed air storage. The void space at Veolia’s [https://www.veolia.co.uk/sites/g/files/dvc1681/files/document/2015/04/Minosus_Brochure_PDF.pdf Minosus] facility at Middlewich, Cheshire which is used for hazardous waste storage was an estimated 23 million cubic metres in 2006. Ongoing salt production of 1 million tonnes per year produces new void of about ½ million m³ a year.

==Compression stage==

Fresh air intake (design conditions 20°C, 1 bar) is compressed in four stages with intermediate and final pressures respectively 2.8 bar, 7.8 bar, 22 bar and 60 bar (6 MPa); the pressure ratio at each stage is ~2.8. Intercooling to 35°C is provided between stages and after the final stage prior to storage. Compression is carried out with an assumed isentropic efficiency of 0.85 and the procedure can conveniently be calculated by spreadsheet, using an equation of state for air that provides temperature as a function of (pressure, enthalpy) or (pressure, entropy); enthalpy function of (temperature, pressure) or (pressure, entropy) and entropy as a function of (temperature, pressure). For this study the equation of state used was the NIST Refprop 9.0 program. The following table illustrates the basic equations used to construct the spreadsheet

{|
|'''State'''
|'''Description'''
|'''T/C'''
|'''P/MPa'''
|'''h/kJ kg-1'''
|'''s/kJ kg-1 C-1'''
|-
|1
|Initial condition
|T1=20
|P1=0.1
|h1=fn(T1,P1)
|s1=fn(T1,P1)
|-
|2
|Isentropic compression
|T2=fn(P2,s2)
|P2=2.8*P1
|h2=fn(P2,s2)
|s2=s1
|-
|2'
|Compression (IE=0.85)
|T2'=fn(P2',h2')
|P2'=P2
|h2'=h1+(h2-h1)/0.85
|s2'=fn(T2',P2')
|-
|3
|Intercooling
|T3=35
|P3=P2'
|h3=fn(T3,P3)
|s3=fn(T3,P3)
|-
|4
|Isentropic compression
|Repeat stages 2-2'-3
|-
|4'
|Compression (IE=0.85)
|…
|-
|5
|Intercooling
|…
|
|
|
|}

==Expansion stage==

Compressed air from storage (design conditions 35°C, 60 bar / 6 MPa) is heated to 300°C and expanded in four stages with intermediate and final pressures in the reverse order to the compression stage: 22 bar, 7.8 bar, 2.8 bar and 1 bar; the pressure ratio at each stage as before is ~2.8. Reheating to 300°C is employed for the second and third expansions but not the final one. Expansion is carried out with the same assumed isentropic efficiency as for compression - 0.85 and a similar spreadsheet calculation can be constructed as shown in the following table illustrating the basic equations used

{|
|'''State'''
|'''Description'''
|'''T/C'''
|'''P/MPa'''
|'''h/kJ kg-1'''
|'''s/kJ kg-1 C-1'''
|-
|1
|Initial condition
|T1=35
|P1=6
|h1=fn(T1,P1)
|s1=fn(T1,P1)
|-
|2
|Heating
|T2=300
|P2=P1
|h2=fn(T2,P2)
|s2=fn(T2,P2)
|-
|3
|Isentropic expansion
|T3=fn(P3,s3)
|P3=P2/2.8
|h3=fn(P3,s3)
|s3=s2
|-
|3'
|Expansion (IE=0.85)
|T3'=fn(P3',h3')
|P3'=P3
|h3'=h2+(h3-h2)*0.85
|s3'=fn(T3',P3')
|-
|4
|Reheating
|T4=300
|P4=P3'
|h4=fn(T4,P4)
|s4=fn(T4,P4)
|-
|5
|Isentropic expansion
|Repeat stages 3-3'-4
|-
|5'
|Expansion (IE=0.85)
|…
|-
|6
|Reheating
|…
|
|
|
|}

==Mechanical equipment==

Siemens Energy offer a range of single-stage radial compressors:

* Volume flow rates up to 1,000,000 m³/h / 590,000 cfm
* Pressure ratio up to ~3 (up to ~6.5 in case of 2 units)
* Suitable for electric motor, steam turbine or gas turbine drive

The size and scale of one compressor unit can be gauged from the access ladders in the following illustration:

[[File:GearlessCompressor-SS-Overhung-jpg Original file.png|800px]]

Recall that the compressor stage is six lines of four compressors - and the expansion stage has 24 air turbine generators and 18 steam turbine generators

==Is it worth it?==

The question rather misses the point of the case study - which is to illustrate the sheer scale of the balance of plant required to provide 1.1 GW of discretionary power. Certainly the Coire Glas scheme has twice the storage and a greater output - but it doesn't produce any power in its own right, unlike CCNG-CAES. Many candidate sites for pumped hydroelectric energy storage are in the Scottish highlands and remote from electricity generation and demand; electricity transmission losses will not be trivial. And who knows what the future relationship between Scotland and the rest of the UK might be?

The feasibility of CCNG-CAES is subject both to the availability of suitable void from extractive industries and acceptable location of new nuclear generation build. It has, at least '''''the potential''''' of bringing flexible output generation capacity at scale in closer proximity to a high energy demand heavy industrial conurbation area.

File:GearlessCompressor-SS-Overhung-jpg Original file.png

2024-08-23T08:30:57Z

Trevor:

Nuclear + storage

2024-08-23T08:22:07Z

Trevor:

==Close-coupled nuclear generation & compressed air energy storage (CCNG-CAES)==

This case study – original work © Fluke – illustrates the scale of operation needed to provide 1.1 GW (one gigawatt) of electricity on a twelve hours on, twelve hours off cycle. This could be used for peak shaving renewable energy or balancing periods of low and high demand.

The base case, without storage, is a 2.0 GW (thermal) output nuclear power station producing electricity via steam turbines at a thermodynamic efficiency of one-third (33⅓ %) 24-hours per day, so 0.67 GW (electrical) continuously.

The study case is an identical power station, located adjacent to a large underground void.

It is feasible to use mechanical energy to compress air and place it into the void, which acts as a pressure vessel. The compression takes place in four stages, each compressor being directly driven from the output shaft of a steam turbine. SIX such arrangements in parallel are required to consume the entire thermal steam output and under this operation no electricity is generated.

At other times air is drawn from the store, heated (and reheated) using 43% of the steam output of the nuclear power station as it expands through four stages of air turbine driving generators. The balance of steam 57% is used to generate more electricity from three steam turbines. Again SIX of these lines are required to consume the entire thermal output and the power generation per line is 183 MW so 1.1 GW gross

So comparing cases, without storage the nuclear power station delivers 16 GW-h electricity continuously over a 24-hour period while the CCNG-CAES generates 13.2 GW-h for 12 hours and nothing for the other 12. The analogy is inexact but the system is in effect a 13.2 GW-h battery with a round trip efficiency of 82.5%

It is also informative to compare this with SSE’s Coire Glas pumped hydroelectric scheme – 30 GW-h storage with 1.5 GW input/output https://www.sserenewables.com/hydro/coire-glas/

==Flow diagrams==

The flow diagrams show the overall heat and mass balance for the compression / charging stage and the expansion /discharging stage of the close-coupled nuclear generation & compressed air energy storage operation. The complementary T-s diagrams present an alternative, graphical method of presenting the numerical spreadsheet calculations described below

* [[Media:CCNGCAES.pdf|Flow & T-s (temperature-entropy) diagrams]]

==Void requirement==

Each of six lines handles 850 tonnes per hour (850,000 kg) of air with the void pressure cycling between 5 MPa (50 bar) ‘discharged’ and 6 MPa (60 bar) ‘charged’. Density of air at 35°C at the two pressures is 56.85 kg/m³ and 68.21 kg/m³ respectively; difference is 11.37 kg/m³. One line for one hour therefore requires 74,787 cubic metres, multiplying by 6 lines and by 12 hours gives a total requirement of 5,385,000 m³.

To put this requirement in context, salt mining / extraction creates large volumes of void space and salt mines are favoured locations for compressed air storage. The void space at Veolia’s [https://www.veolia.co.uk/sites/g/files/dvc1681/files/document/2015/04/Minosus_Brochure_PDF.pdf Minosus] facility at Middlewich, Cheshire which is used for hazardous waste storage was an estimated 23 million cubic metres in 2006. Ongoing salt production of 1 million tonnes per year produces new void of about ½ million m³ a year.

==Compression stage==

Fresh air intake (design conditions 20°C, 1 bar) is compressed in four stages with intermediate and final pressures respectively 2.8 bar, 7.8 bar, 22 bar and 60 bar (6 MPa); the pressure ratio at each stage is ~2.8. Intercooling to 35°C is provided between stages and after the final stage prior to storage. Compression is carried out with an assumed isentropic efficiency of 0.85 and the procedure can conveniently be calculated by spreadsheet, using an equation of state for air that provides temperature as a function of (pressure, enthalpy) or (pressure, entropy); enthalpy function of (temperature, pressure) or (pressure, entropy) and entropy as a function of (temperature, pressure). For this study the equation of state used was the NIST Refprop 9.0 program. The following table illustrates the basic equations used to construct the spreadsheet

{|
|'''State'''
|'''Description'''
|'''T/C'''
|'''P/MPa'''
|'''h/kJ kg-1'''
|'''s/kJ kg-1 C-1'''
|-
|1
|Initial condition
|T1=20
|P1=0.1
|h1=fn(T1,P1)
|s1=fn(T1,P1)
|-
|2
|Isentropic compression
|T2=fn(P2,s2)
|P2=2.8*P1
|h2=fn(P2,s2)
|s2=s1
|-
|2'
|Compression (IE=0.85)
|T2'=fn(P2',h2')
|P2'=P2
|h2'=h1+(h2-h1)/0.85
|s2'=fn(T2',P2')
|-
|3
|Intercooling
|T3=35
|P3=P2'
|h3=fn(T3,P3)
|s3=fn(T3,P3)
|-
|4
|Isentropic compression
|Repeat stages 2-2'-3
|-
|4'
|Compression (IE=0.85)
|…
|-
|5
|Intercooling
|…
|
|
|
|}

==Expansion stage==

Compressed air from storage (design conditions 35°C, 60 bar / 6 MPa) is heated to 300°C and expanded in four stages with intermediate and final pressures in the reverse order to the compression stage: 22 bar, 7.8 bar, 2.8 bar and 1 bar; the pressure ratio at each stage as before is ~2.8. Reheating to 300°C is employed for the second and third expansions but not the final one. Expansion is carried out with the same assumed isentropic efficiency as for compression - 0.85 and a similar spreadsheet calculation can be constructed as shown in the following table illustrating the basic equations used

{|
|'''State'''
|'''Description'''
|'''T/C'''
|'''P/MPa'''
|'''h/kJ kg-1'''
|'''s/kJ kg-1 C-1'''
|-
|1
|Initial condition
|T1=35
|P1=6
|h1=fn(T1,P1)
|s1=fn(T1,P1)
|-
|2
|Heating
|T2=300
|P2=P1
|h2=fn(T2,P2)
|s2=fn(T2,P2)
|-
|3
|Isentropic expansion
|T3=fn(P3,s3)
|P3=P2/2.8
|h3=fn(P3,s3)
|s3=s2
|-
|3'
|Expansion (IE=0.85)
|T3'=fn(P3',h3')
|P3'=P3
|h3'=h2+(h3-h2)*0.85
|s3'=fn(T3',P3')
|-
|4
|Reheating
|T4=300
|P4=P3'
|h4=fn(T4,P4)
|s4=fn(T4,P4)
|-
|5
|Isentropic expansion
|Repeat stages 3-3'-4
|-
|5'
|Expansion (IE=0.85)
|…
|-
|6
|Reheating
|…
|
|
|
|}

==Mechanical equipment==

Siemens Energy offer a range of single-stage radial compressors:

* Volume flow rates up to 1,000,000 m³/h / 590,000 cfm
* Pressure ratio up to ~3 (up to ~6.5 in case of 2 units)
* Suitable for electric motor, steam turbine or gas turbine drive

The size and scale of one compressor unit can be gauged from the access ladders in the following illustration:

https://p3.aprimocdn.net/siemensenergy/f8bf87f9-03a9-484e-9c3d-b00d006a5e5d/GearlessCompressor-SS-Overhung-jpg_Original%20file.jpg

Recall that the compressor stage is six lines of four compressors - and the expansion stage has 24 air turbine generators and 18 steam turbine generators

==Is it worth it?==

The question rather misses the point of the case study - which is to illustrate the sheer scale of the balance of plant required to provide 1.1 GW of discretionary power. Certainly the Coire Glas scheme has twice the storage and a greater output - but it doesn't produce any power in its own right, unlike CCNG-CAES. Many candidate sites for pumped hydroelectric energy storage are in the Scottish highlands and remote from electricity generation and demand; electricity transmission losses will not be trivial. And who knows what the future relationship between Scotland and the rest of the UK might be?

The feasibility of CCNG-CAES is subject both to the availability of suitable void from extractive industries and acceptable location of new nuclear generation build. It has, at least '''''the potential''''' of bringing flexible output generation capacity at scale in closer proximity to a high energy demand heavy industrial conurbation area.

File:Greta British Energy.png

2024-06-14T12:52:19Z

Trevor: Trevor uploaded a new version of File:Greta British Energy.png

File:Greta British Energy.png

2024-06-14T08:41:31Z

Trevor:

File:Global.1751 2008.ems2.png

2024-05-29T11:08:45Z

Trevor:

File:Global.1751 2008.ems.png

2022-12-14T12:32:11Z

Trevor:

Home Insulation

2022-09-16T11:36:32Z

Trevor: /* Relationship between SAP, energy costs, energy consumption and CO2 emissions */

== Case study - 92 properties in SK31 ==

Energy performance certificates (EPC) are a legal requirement when properties are built, sold or rented in the UK and the information is in the public domain. FLUKE has made a case study of 92 properties in the East Midlands, England, ordnance survey grid area SK31. The housing stock consists of a mixture of older Victorian and early 20th century terraced housing and some more modern, estate built houses. (The data are anonymised and given the grid area covers 100 square kilometres; this ''should'' provide adequate data protection to any individual householder). An EPC is issued following a detailed survey of the property and contains much useful information. This case study mainly focusses on the Standard Assessment Procedure (SAP) scores for the '''current''' and '''potential'''
energy efficiency ratings. The latter score indicates the potential improvement in efficiency that might be achieved, if all the energy-conserving measures including insulation, low energy lighting, solar water heating etc. recommended in the report were indeed carried out. The comparison between these 'before' and 'after' SAP rating figures provides a simple method for assessing the potential improvement achievable if the entire housing stock were renovated to all the recommended measures in the EPC.

== Histograms for the current and potential SAP ratings ==

The following two charts show the distribution of SAP ratings for the 92 houses:

[[File:SAP histogram current.png|frameless|left|Current]]
[[File:SAP histogram potential.png|frameless|Potential]]

As would be expected, when energy efficiency is improved the distribution shifts to the right hand side of the histogram, as energy saving measures are implemented. A more detailed way to view the data at the level of individual properties, is to correlate the SAP ratings before and after improvements:

[[File:SAP correlation.png|frameless|Correlation]]

There is considerable scatter in the data. Some of the lowest rated properties would benefit greatly from insulation, on the other hand mid-range rated houses may be old stock that have already been insulated to a good standard - or new houses that haven't been improved. The correlation between SAP values is positive, that is, the more energy efficient the house is to begin with, the higher the final achievable value. This relationship is subject to diminishing returns since an adequately insulated house can only be improved so far by further insulation, whereas an old and poorly insulated property has great scope for improvement in both absolute and percentage terms yet still not achieve the highest score even after all the recommended improvements. The thinner black trend line is the 'best-fit' to the data points and the bolder, red 45° line represents the current situation. The ''GAP'' between the red and black lines may be regarded as the realistic potential for improvement in SAP rating

==Relationship between SAP, energy costs, energy consumption and CO2 emissions==

A convenient relationship between SAP rating and household expenditure on energy … and by extension, the households' energy consumption and CO2 emissions … was required. The data set from Appendix 8 of [https://www.fuelpovertylibrary.info/sites/default/files/EAGA40%20%282006%29%20REPORT%20SAP%20targets%20and%20affordability%20in%20Social%20Housing.pdf EAG Charitable Trust] was used to produce the following correlation and trendline. The exponential equation appears to be reasonable fit and the semi-empirical form can be justified from the observation that improvements in insulation and other energy-saving measures will reduce but never eliminate the need to purchase energy i.e. the law of diminishing returns

[[File:SAP to cost.png|frameless|left|Cost correlation]] 

The final step is to tabulate the results, making use of the two correlations. First assign mid-point SAP values to category bands: B=86, C=74.5, D=61.5, E=46.5 F=29.5, G=10.5. Use the cost correlation to convert SAP to current cost and a combination of both correlations to calculate the potential cost (after energy saving measures). Then weight these costs to take into account the percentage of houses in each EPC band and compute the weighted saving.

{| class="wikitable"
|-
! Band !! % in band !! Current !! Weighted current !! Potential !! Weighted potential !! Weighted saving
|-
| G || 9% || £1,753 || £152 || £802 || £70|| £82
|-
| F || 20% || £1,315 || £257 || £727 || £142 || £115
|-
| E || 16% || £1,017 || £166 || £667 || £109 || £57
|-
| D || 42% || £811 || £344 || £617 || £262|| £82
|-
| C || 12% || £666 || £80 || £578 || £69 || £11
|-
| B || 1% || £560 || £6 || £545 || £6 || £0
|-
| TOTALS || 100% || || £1,005 || || £657 || £348
|}

== Conclusion ==

Energy performance certificates (EPC) and Standard Assessment Procedure (SAP) ratings provide a valuable data source for assessing existing household energy consumption and the scope for reduction that consumption by energy saving measures

The average energy consumption cost for this case study of 92 houses is £1,005 with considerable variation due to the age and state of insulation of individual properties. If ''ALL'' the 'recommended measures' detailed in the EPC were implemented for all the houses in the study there would be a saving of £348 (35%) reducing the annual energy consumption to £657 (all figures on a weighted-average basis)

Energy costs can be regarded as a proxy for energy consumption and CO2 emissions. Large scale programs for retrofitting home-insulation for the existing UK housing stock have been proposed as a measure to 'de-carbonise' home heating. Based on this case study, a 35% reduction seems practicable

HadCET CUSUM analysis

2022-08-10T10:22:15Z

Trevor: Include New Scientist article

CUSUM analysis - a statistical technique borrowed from the quality control discipline - is deceptively simple to calculate by spreadsheet or even by hand yet a powerful tool for screening out 'noise' and spotting trend changes
# calculate the deviations from mean average
# first value = 0
# second value = first value + first deviation
# third value = second value + second deviation
# and so on
# final value = 0 ''by definition of average'' must be so
The thing to look for is abrupt kinks in the graph, which shout 'something changed here'. The chart below - original work by FLUKE - appears to show four distinct trend periods: 1772 to 1892, 1892 to 1932, 1932 to 1988 and 1988 to present

It is interesting to compare these results - which are purely a result of statistical analysis of temperature at a single location - with the broader world-wide climate trends over the last 120 years. For example the [https://www.newscientist.com/article/dn9912-timeline-climate-change/ New Scientist climate-change timeline] which identifies the period from 1940 to 1970 as one of global ''cooling'' which interrupted the earlier 'dust bowl' epoch and the present day heating periods

[[File:Hadcet3.png|800px]]

Ground Source Heat Pump

2022-08-01T10:05:04Z

Trevor:

== GSHP in a suburban setting - a case study ==
In the following scenario an early adopter installs a Ground Source Heat Pump (GSHP) and initially enjoys uncontended use of the sensible heat contained within a hemispherical volume of sub-soil beneath her - and her neighbours' properties. Later, under a policy of mass adoption of GSHP technology, all the surrounding properties are competing for the same heat and the effective source volume is bounded by the area of property, straight down.

[[File:Catchment.png|frameless|left|Early Adopter]]
[[File:Conceptual model.png|frameless|Mass uptake]]

This latter case can be mathematically modelled as "Transient Heat Conduction in a Semi-infinite Solid". The housing estate is an infinite surface plane, held at the heat extraction temperature T0°C. The ground extends to an infinite distance in all horizontal directions - and downward (hence ''semi''-infinite solid) and is initially at a uniform temperature Ti°C. Since Ti > T0 heat flows from below ground towards the surface where it is collected by the slinky coils and used to heat the house. The mathematical solution (proof not given here) provides equations for the '''temperature distribution''' within the sub-soil, as a function of ''time'' and ''depth'' and the '''heat flux''', that is the quantity of heat that can be extracted at the surface, a function of ''time'' alone

== Temperature distribution ==

The governing equation is:
[[File:TDequation.png|frameless|left]] 
where T(x,τ) is the sub-soil temperature at depth x metres and after τ days

''erf''() is the Gauss error function; conveniently, this function is supported for MS Excel spreadsheets as =ERF()

and for this case study the following values were used:

T0 = 5°C, the temperature at which heat is being extracted

Ti = 10°C, the initial, uniform temperature throughout the ground

α = 0.0647 m²/day the Thermal Diffusivity for "Coal Measures Group" geology (GeoReports, British Geological Survey)

Additionally, the house is on a 12 metre x 18 metre plot and has a heating requirement of 12,000 kW-h per year equivalent to the OFGEM Typical Domestic Consumption Value (TDCV) for ''gas'', for a medium size household (the GSHP is providing space heating and domestic hot water in place of a gas boiler). 12,000 kW-h equates to a year-round average demand of 1,370 W; the demand model was further refined to reflect varying seasonal requirements using a 'degree-days' method, explained elsewhere. Also it was assumed that for every 3.5 kW of heat delivered to the house, 2.5 kW came from the ground and 1 kW from the electrical energy to drive the heat pump (coefficient of performance / COP = 3.5). The case study covers an eight month 'heating season' from October to May. It is a fairly trivial exercise to create a spreadsheet from scratch using the information given above and then one can compare, for example, the times for the subsoil to cool to 7°C at depths 0.5m, 1m, 2m: 7 days, 28 days and 112 days respectively. At 5m depth the temperature never goes below 8°C and at 10m the sub-soil barely drops ½°C. Here is a graph of the results:

[[File:TDchart.png|800px|frameless|Sub-surface temperature distribution, over time]] 

== Heat flux at the surface ==

A second equation gives the heat flux, that is, the rate of heat that can be extracted from the ground directly below the householder's property boundary:
[[File:Qequation.png|frameless|left]] 
where ''Qsurface'' is heat flux in Watts (W)

k = 1.79 W/m/K, the Thermal Conductivity for "Coal Measures Group" geology (GeoReports, British Geological Survey)

A = 216 m², the area of the property (12m by 18m)

T0 = 5°C, the temperature at which heat is being extracted

Ti = 10°C, the initial, uniform temperature throughout the ground

π = 3.1415…

α = 0.0647 m²/day the Thermal Diffusivity for "Coal Measures Group" geology (GeoReports, British Geological Survey)

Again, creating a spreadsheet is a trivial exercise and the results are illustrated below:

[[File:Qchart.png|800px|frameless|Sub-surface temperature distribution, over time]] 

== Solar Assisted Ground Source Heat Pump Systems ==

Further analysis carried out by Fluke in 2022 shows that a long term steady state system may be achieved by solar heat assistance. In this scenario, heat is recharged into the ground for part of the year to be extracted again during the heating season. The charging and discharging temperatures used in the model are 25°C and 5°C respectively.

[[File:GSHP2.xlsm_-_Excel_2022-08-01_10-11-17.mp4|1600px|frameless|Multi-year temperature distribution, with solar assist]] 

== Conclusions ==

Mass deployment of Ground Source Heat Pumps in a suburban setting would result in inadequate space heating and domestic hot water for the households in the scheme. The area available per property is simply too small

The findings can be understood in qualitative terms. Initially, at the start of the heating season demand is low and ground heat is close to the surface, easy to extract. But as time progresses the shallower sub-soil cools close to the extraction temperature and heat must then be obtained from deeper into the ground making it harder to extract - just at the same time demand is reaching its winter peak

In urban settings the problem would be exacerbated due to the higher property density. In rural environments and for properties with extensive grounds, GSHP may be an appropriate solution

The working assumption is that solar gain during summer would be sufficient to "recharge" the ground with heat ready for the next heating season. This is by no means certain and further study must be made to check if there would be a multi year cooling effect from using GSHP technology

Ground Source Heat Pump

2022-08-01T10:03:45Z

Trevor: /* Solar Assisted Ground Source Heat Pump Systems */

== GSHP in a suburban setting - a case study ==
In the following scenario an early adopter installs a Ground Source Heat Pump (GSHP) and initially enjoys uncontended use of the sensible heat contained within a hemispherical volume of sub-soil beneath her - and her neighbours' properties. Later, under a policy of mass adoption of GSHP technology, all the surrounding properties are competing for the same heat and the effective source volume is bounded by the area of property, straight down.

[[File:Catchment.png|frameless|left|Early Adopter]]
[[File:Conceptual model.png|frameless|Mass uptake]]

This latter case can be mathematically modelled as "Transient Heat Conduction in a Semi-infinite Solid". The housing estate is an infinite surface plane, held at the heat extraction temperature T0°C. The ground extends to an infinite distance in all horizontal directions - and downward (hence ''semi''-infinite solid) and is initially at a uniform temperature Ti°C. Since Ti > T0 heat flows from below ground towards the surface where it is collected by the slinky coils and used to heat the house. The mathematical solution (proof not given here) provides equations for the '''temperature distribution''' within the sub-soil, as a function of ''time'' and ''depth'' and the '''heat flux''', that is the quantity of heat that can be extracted at the surface, a function of ''time'' alone

== Temperature distribution ==

The governing equation is:
[[File:TDequation.png|frameless|left]] 
where T(x,τ) is the sub-soil temperature at depth x metres and after τ days

''erf''() is the Gauss error function; conveniently, this function is supported for MS Excel spreadsheets as =ERF()

and for this case study the following values were used:

T0 = 5°C, the temperature at which heat is being extracted

Ti = 10°C, the initial, uniform temperature throughout the ground

α = 0.0647 m²/day the Thermal Diffusivity for "Coal Measures Group" geology (GeoReports, British Geological Survey)

Additionally, the house is on a 12 metre x 18 metre plot and has a heating requirement of 12,000 kW-h per year equivalent to the OFGEM Typical Domestic Consumption Value (TDCV) for ''gas'', for a medium size household (the GSHP is providing space heating and domestic hot water in place of a gas boiler). 12,000 kW-h equates to a year-round average demand of 1,370 W; the demand model was further refined to reflect varying seasonal requirements using a 'degree-days' method, explained elsewhere. Also it was assumed that for every 3.5 kW of heat delivered to the house, 2.5 kW came from the ground and 1 kW from the electrical energy to drive the heat pump (coefficient of performance / COP = 3.5). The case study covers an eight month 'heating season' from October to May. It is a fairly trivial exercise to create a spreadsheet from scratch using the information given above and then one can compare, for example, the times for the subsoil to cool to 7°C at depths 0.5m, 1m, 2m: 7 days, 28 days and 112 days respectively. At 5m depth the temperature never goes below 8°C and at 10m the sub-soil barely drops ½°C. Here is a graph of the results:

[[File:TDchart.png|800px|frameless|Sub-surface temperature distribution, over time]] 

== Heat flux at the surface ==

A second equation gives the heat flux, that is, the rate of heat that can be extracted from the ground directly below the householder's property boundary:
[[File:Qequation.png|frameless|left]] 
where ''Qsurface'' is heat flux in Watts (W)

k = 1.79 W/m/K, the Thermal Conductivity for "Coal Measures Group" geology (GeoReports, British Geological Survey)

A = 216 m², the area of the property (12m by 18m)

T0 = 5°C, the temperature at which heat is being extracted

Ti = 10°C, the initial, uniform temperature throughout the ground

π = 3.1415…

α = 0.0647 m²/day the Thermal Diffusivity for "Coal Measures Group" geology (GeoReports, British Geological Survey)

Again, creating a spreadsheet is a trivial exercise and the results are illustrated below:

[[File:Qchart.png|800px|frameless|Sub-surface temperature distribution, over time]] 

== Solar Assisted Ground Source Heat Pump Systems ==

Further analysis carried out by Fluke in 2022 shows that a long term steady state system may be achieved by solar heat assistance. In this scenario, heat is recharged into the ground for part of the year to be extracted again during the heating season. The charging and discharging temperatures used in the model are 25°C and 5°C respectively.

[[File:GSHP2.xlsm_-_Excel_2022-08-01_10-11-17.mp4|frameless|Multi-year temperature distribution, with solar assist]] 

== Conclusions ==

Mass deployment of Ground Source Heat Pumps in a suburban setting would result in inadequate space heating and domestic hot water for the households in the scheme. The area available per property is simply too small

The findings can be understood in qualitative terms. Initially, at the start of the heating season demand is low and ground heat is close to the surface, easy to extract. But as time progresses the shallower sub-soil cools close to the extraction temperature and heat must then be obtained from deeper into the ground making it harder to extract - just at the same time demand is reaching its winter peak

In urban settings the problem would be exacerbated due to the higher property density. In rural environments and for properties with extensive grounds, GSHP may be an appropriate solution

The working assumption is that solar gain during summer would be sufficient to "recharge" the ground with heat ready for the next heating season. This is by no means certain and further study must be made to check if there would be a multi year cooling effect from using GSHP technology

Ground Source Heat Pump

2022-08-01T09:50:30Z

Trevor:

== GSHP in a suburban setting - a case study ==
In the following scenario an early adopter installs a Ground Source Heat Pump (GSHP) and initially enjoys uncontended use of the sensible heat contained within a hemispherical volume of sub-soil beneath her - and her neighbours' properties. Later, under a policy of mass adoption of GSHP technology, all the surrounding properties are competing for the same heat and the effective source volume is bounded by the area of property, straight down.

[[File:Catchment.png|frameless|left|Early Adopter]]
[[File:Conceptual model.png|frameless|Mass uptake]]

This latter case can be mathematically modelled as "Transient Heat Conduction in a Semi-infinite Solid". The housing estate is an infinite surface plane, held at the heat extraction temperature T0°C. The ground extends to an infinite distance in all horizontal directions - and downward (hence ''semi''-infinite solid) and is initially at a uniform temperature Ti°C. Since Ti > T0 heat flows from below ground towards the surface where it is collected by the slinky coils and used to heat the house. The mathematical solution (proof not given here) provides equations for the '''temperature distribution''' within the sub-soil, as a function of ''time'' and ''depth'' and the '''heat flux''', that is the quantity of heat that can be extracted at the surface, a function of ''time'' alone

== Temperature distribution ==

The governing equation is:
[[File:TDequation.png|frameless|left]] 
where T(x,τ) is the sub-soil temperature at depth x metres and after τ days

''erf''() is the Gauss error function; conveniently, this function is supported for MS Excel spreadsheets as =ERF()

and for this case study the following values were used:

T0 = 5°C, the temperature at which heat is being extracted

Ti = 10°C, the initial, uniform temperature throughout the ground

α = 0.0647 m²/day the Thermal Diffusivity for "Coal Measures Group" geology (GeoReports, British Geological Survey)

Additionally, the house is on a 12 metre x 18 metre plot and has a heating requirement of 12,000 kW-h per year equivalent to the OFGEM Typical Domestic Consumption Value (TDCV) for ''gas'', for a medium size household (the GSHP is providing space heating and domestic hot water in place of a gas boiler). 12,000 kW-h equates to a year-round average demand of 1,370 W; the demand model was further refined to reflect varying seasonal requirements using a 'degree-days' method, explained elsewhere. Also it was assumed that for every 3.5 kW of heat delivered to the house, 2.5 kW came from the ground and 1 kW from the electrical energy to drive the heat pump (coefficient of performance / COP = 3.5). The case study covers an eight month 'heating season' from October to May. It is a fairly trivial exercise to create a spreadsheet from scratch using the information given above and then one can compare, for example, the times for the subsoil to cool to 7°C at depths 0.5m, 1m, 2m: 7 days, 28 days and 112 days respectively. At 5m depth the temperature never goes below 8°C and at 10m the sub-soil barely drops ½°C. Here is a graph of the results:

[[File:TDchart.png|800px|frameless|Sub-surface temperature distribution, over time]] 

== Heat flux at the surface ==

A second equation gives the heat flux, that is, the rate of heat that can be extracted from the ground directly below the householder's property boundary:
[[File:Qequation.png|frameless|left]] 
where ''Qsurface'' is heat flux in Watts (W)

k = 1.79 W/m/K, the Thermal Conductivity for "Coal Measures Group" geology (GeoReports, British Geological Survey)

A = 216 m², the area of the property (12m by 18m)

T0 = 5°C, the temperature at which heat is being extracted

Ti = 10°C, the initial, uniform temperature throughout the ground

π = 3.1415…

α = 0.0647 m²/day the Thermal Diffusivity for "Coal Measures Group" geology (GeoReports, British Geological Survey)

Again, creating a spreadsheet is a trivial exercise and the results are illustrated below:

[[File:Qchart.png|800px|frameless|Sub-surface temperature distribution, over time]] 

== Solar Assisted Ground Source Heat Pump Systems ==

Further analysis carried out by Fluke in 2022 shows that a long term steady state system may be achieved by solar heat assistance. In this scenario, heat is recharged into the ground for part of the year to be extracted again during the heating season. The charging and discharging temperatures used in the model are 25°C and 5°C respectively.

[[File:GSHP2.xlsm_-_Excel_2022-08-01_10-11-17.mp4800px|frameless|Multi-year temperature distribution, with solar assist]] 

== Conclusions ==

Mass deployment of Ground Source Heat Pumps in a suburban setting would result in inadequate space heating and domestic hot water for the households in the scheme. The area available per property is simply too small

The findings can be understood in qualitative terms. Initially, at the start of the heating season demand is low and ground heat is close to the surface, easy to extract. But as time progresses the shallower sub-soil cools close to the extraction temperature and heat must then be obtained from deeper into the ground making it harder to extract - just at the same time demand is reaching its winter peak

In urban settings the problem would be exacerbated due to the higher property density. In rural environments and for properties with extensive grounds, GSHP may be an appropriate solution

The working assumption is that solar gain during summer would be sufficient to "recharge" the ground with heat ready for the next heating season. This is by no means certain and further study must be made to check if there would be a multi year cooling effect from using GSHP technology

File:GSHP2.xlsm - Excel 2022-08-01 10-11-17.mp4

2022-08-01T09:47:26Z

Trevor: Video of simulation: Solar Assisted Ground-source heating

== Summary ==
Video of simulation: Solar Assisted Ground-source heating

File:Sine versus sine-cubed.pdf

2021-12-01T10:54:14Z

Trevor: Trevor uploaded a new version of File:Sine versus sine-cubed.pdf

File:Sine versus sine-cubed.pdf

2021-12-01T10:50:56Z

Trevor:

File:WindSolar2019.pdf

2021-11-22T15:26:26Z

Trevor: Average power in GW derived from wind and solar PV in 2019

== Summary ==
Average power in GW derived from wind and solar PV in 2019

Geological Time

2021-11-04T11:02:39Z

Trevor:

If the world were an woman … we could call her Gaia … aged 43

[[File:Gaia.gif|frameless|center]]

Let's set a scale of 2 million years = 1 Gaia week, so 104 million years = 1 year. And sure enough, in round numbers, 44 Gaia years = 4.6 billion years which is our current scientific understanding of the age of the Earth. At the other end of the scale, 6,000 years which encompasses all of written human history = ½ a Gaia hour

== Gaia tells the story of her life ==

{| class="wikitable"
|-
! Event !! Gaia's Age !! How long ago 'Gaia time'
|-
| About 3.5 - 3.8 billion years of simple cells (prokaryotes). || 8 years 7 months || 35 years 1 month
|-
| 3 billion years of photosynthesis. || 14 years 10 months || 28 years 10 months
|-
| Great Oxidation Event || 23 years 8 months || 20 years
|-
| 2 billion years of complex cells (eukaryotes). || 24 years 5 months || 19 years 2 months
|-
| 1 billion years of multicellular life. || 34 years || 9 years 7 months
|-
| 600 million years of simple animals. || 37 years 10 months || 5 years 9 months
|-
| 570 million years of arthropods (ancestors of insects, arachnids and crustaceans). || 38 years 2 months || 5 years 5 months
|-
| 550 million years of complex animals. || 38 years 4 months || 5 years 3 months
|-
| 500 million years of fish and proto-amphibians. || 38 years 10 months || 4 years 9 months
|-
| 475 million years of land plants. || 39 years 1 month || 4 years 6 months
|-
| 400 million years of insects and seeds. || 39 years 10 months || 3 years 10 months
|-
| 360 million years of amphibians. || 40 years 2 months || 3 years 5 months
|-
| 300 million years of reptiles. || 40 years 9 months || 2 years 10 months
|-
| First dinosaurs || 41 years 5 months || 2 years 2 months
|-
| 200 million years of mammals. || 41 years 9 months || 1 year 11 months
|-
| 150 million years of birds. || 42 years 2 months || 1 year 5 months
|-
| 130 million years of flowers. || 42 years 5 months || 1 year 3 months
|-
| 65 million years since the non-avian dinosaurs died out. || 43 years || 7 months
|-
| 2.5 million years since the appearance of Homo. || 43 years 7 months || 8 days
|-
| 200,000 years since the appearance of modern humans. || 43 years 8 months || 16 hours
|-
| 25,000 years since Neanderthals died out. || 43 years 8 months || 2 hours
|-
|}

Geological Time

2021-11-04T11:01:13Z

Trevor:

If the world were an woman … we could call her Gaia … aged 43

[[File:Gaia.gif|frameless|center]]

Let's set a scale of 2 million years = 1 Gaia week, so 104 million years = 1 year. And sure enough, in round numbers, 44 Gaia years = 4.6 billion years which is our current scientific understanding of the age of the Earth. At the other end of the scale, 6,000 years which encompasses all of written human history = ½ a Gaia hour

== Gaia tells the story of her life ==

{| class="wikitable"
|-
! Event !! Gaia's Age !! How long ago 'Gaia time'
|-
| About 3.5 - 3.8 billion years of simple cells (prokaryotes). || 8 years 7 months || 35 years 1 month
|-
| 3 billion years of photosynthesis. || 14 years 10 months || 28 years 10 months
|-
| Great Oxidation Event || 23 years 8 months || 20 years
|-
| 2 billion years of complex cells (eukaryotes). || 24 years 5 months || 19 years 2 months
|-
| 1 billion years of multicellular life. || 34 years || 9 years 7 months
|-
| 600 million years of simple animals. || 37 years 10 months || 5 years 9 months
|-
| 570 million years of arthropods (ancestors of insects, arachnids and crustaceans). || 38 years 2 months || 5 years 5 months
|-
| 550 million years of complex animals. || 38 years 4 months || 5 years 3 months
|-
| 500 million years of fish and proto-amphibians. || 38 years 10 months || 4 years 9 months
|-
| 475 million years of land plants. || 39 years 1 month || 4 years 6 months
|-
| 400 million years of insects and seeds. || 39 years 10 months || 3 years 10 months
|-
| 360 million years of amphibians. || 40 years 2 months || 3 years 5 months
|-
| 300 million years of reptiles. || 40 years 9 months || 2 years 10 months
|-
| First dinosaurs || 41 years 5 months || 2 years 2 months
|-
| 200 million years of mammals. || 41 years 9 months || 1 years 11 months
|-
| 150 million years of birds. || 42 years 2 months || 1 years 5 months
|-
| 130 million years of flowers. || 42 years 5 months || 1 years 3 months
|-
| 65 million years since the non-avian dinosaurs died out. || 43 years || 7 months
|-
| 2.5 million years since the appearance of Homo. || 43 years 7 months || 8 days
|-
| 200,000 years since the appearance of modern humans. || 43 years 8 months || 16 hours
|-
| 25,000 years since Neanderthals died out. || 43 years 8 months || 2 hours
|-
|}

Geological Time

2021-11-02T14:58:02Z

Trevor: Created page with "If the world were an woman … we could call her Gaia … aged 44 center Let's set a scale of 2 million years = 1 Gaia week, so 104 million yea..."

If the world were an woman … we could call her Gaia … aged 44

[[File:Gaia.gif|frameless|center]]

Let's set a scale of 2 million years = 1 Gaia week, so 104 million years = 1 year. And sure enough, in round numbers, 44 Gaia years = 4.6 billion years which is our current scientific understanding of the age of the Earth. At the other end of the scale, 6,000 years which encompasses all of written human history = ½ a Gaia hour

== Gaia tells the story of her life ==

‘First simple cells appeared at age 9 but I had not acquired my green colouration until I was 15 and learned how to photosynthesize. It took another 9 years though, for me to get an oxygen atmosphere and by the time I was 25 more complex cells started to appear. Not till I was 35 did these begin to group together to first form multi-cell life forms. My late 30’s saw the first insects, fish and land plants and my early 40’s saw amphibians and reptiles. At age 42 came the first dinosaurs – and the first mammals. Birds followed and then flowers the year after. The dinosaurs died out around the time I turned 44, finally giving a chance for the mammals to flourish.

Things have got interesting in the last ten days; a few brainy biped types have learnt to make fire and stone tools and yesterday started forming more complex societies, art, music. The more northern, thicker browed type died out two hours ago and the survivors, the ones that emerged from the large southern tropical continent have named, for themselves, this last half-hour “all of recorded history” ‘

File:Gaia.gif

2021-11-02T14:37:07Z

Trevor:

North Sea Wind Variability

2021-09-24T15:07:10Z

Trevor: /* KNMI Data Source */

== KNMI Data Source ==

The KNMI Koninklijk Nederlands Meteorologisch Instituut (Royal Netherlands Meteorological Institute) is a useful resource of accessible and free to download data and include the [https://dataplatform.knmi.nl/dataset/knw-csv-ts-update-1-0 dataset]: '''Wind - model time series from 2014 to August 2019 at 10-200 meters above the North Sea in individual 2.5 km grid location files'''

''Would that there were an equivalent (non-paywall) resource by the UK''

The data cover a rectangular area latitude 50°N to 55°N longitude 1°E to 8°E and while this information is most of interest to the Dutch, the coverage does include Dogger Bank and is suitable for analysing the potential performance of new UK wind farm projects.

The KNW-1.0_H37-ERA_NL-001-142.csv file relates to the 2.5km² tile centred on 53.59°N 1.47°E which is located within the proposed 1.5GW '''Green Investment Group - Total''' development east of Kingston-Upon-Hull

[[Image:53 59degN 1 47degE.gif|frameless|center|Animation of five years' of wind data in the North Sea]]

== Validation of a Weibull distribution for hourly wind speed data ==

Using the Microsoft Excel function

={total number of measurements]WEIBULL.DIST({wind_velocity_m_s},2.318741605,11.81669862,FALSE)

it can be seen there is a good correlation between the fitted Weibull function curve (orange line) and the actual histogram data (blue bars)

[[File:Wind Speeds 2014 2019.png|thumb]]

North Sea Wind Variability

2021-09-24T15:03:42Z

Trevor: /* KNMI Data Source */

== KNMI Data Source ==

The KNMI Koninklijk Nederlands Meteorologisch Instituut (Royal Netherlands Meteorological Institute) is a useful resource of accessible and free to download data and include the [https://dataplatform.knmi.nl/dataset/knw-csv-ts-update-1-0 dataset]: '''Wind - model time series from 2014 to August 2019 at 10-200 meters above the North Sea in individual 2.5 km grid location files'''

''Would that there were an equivalent (non-paywall) resource by the UK''

The data cover a rectangular area latitude 50°N to 55°N longitude 1°E to 8°E and while this information is most of interest to the Dutch, the coverage does include Dogger Bank and is suitable for analysing the potential performance of new UK wind farm projects.

The KNW-1.0_H37-ERA_NL-001-142.csv file relates to the 2.5km² tile centred on 53.59°N 1.47°E which is located within the proposed 1.5GW Green Investment Group - Total development east of Kingston-Upon-Hull

[[Image:53 59degN 1 47degE.gif|frameless|center|Animation of five years' of wind data in the North Sea]]

== Validation of a Weibull distribution for hourly wind speed data ==

Using the Microsoft Excel function

={total number of measurements]WEIBULL.DIST({wind_velocity_m_s},2.318741605,11.81669862,FALSE)

it can be seen there is a good correlation between the fitted Weibull function curve (orange line) and the actual histogram data (blue bars)

[[File:Wind Speeds 2014 2019.png|thumb]]

North Sea Wind Variability

2021-09-24T15:02:59Z

Trevor:

== KNMI Data Source ==

The KNMI Koninklijk Nederlands Meteorologisch Instituut (Royal Netherlands Meteorological Institute) is a useful resource of accessible and free to download data and include the [https://dataplatform.knmi.nl/dataset/knw-csv-ts-update-1-0 dataset]: '''Wind - model time series from 2014 to August 2019 at 10-200 meters above the North Sea in individual 2.5 km grid location files'''

''Would that there were an equivalent (non-paywall) resource by the UK''

The data cover a rectangular area latitude 50°N to 55°N longitude 1°E to 8°E and while this information is most of interest to the Dutch, the coverage does include Dogger Bank and is suitable for analysing the potential performance of new UK wind farm projects.

The KNW-1.0_H37-ERA_NL-001-142.csv file relates to the 2.5km² tile centred on 53.59°N 1.47°E which is located within the proposed 1.5GW Green Investment Group - Total development east of Kingston-Upon-Hull

[[File:53 59degN 1 47degE.gif|frameless|center|Animation of five years' of wind data in the North Sea]]

== Validation of a Weibull distribution for hourly wind speed data ==

Using the Microsoft Excel function

={total number of measurements]WEIBULL.DIST({wind_velocity_m_s},2.318741605,11.81669862,FALSE)

it can be seen there is a good correlation between the fitted Weibull function curve (orange line) and the actual histogram data (blue bars)

[[File:Wind Speeds 2014 2019.png|thumb]]

File:53 59degN 1 47degE.gif

2021-09-24T14:58:00Z

Trevor:

Off-shore Wind Power

2021-09-24T14:57:28Z

Trevor: /* Round 4 Offshore Wind Projects */

It is difficult to overstate the importance of offshore wind's contribution to the UK's renewable electricity generation capacity. As an island, the country has a large area of surrounding territorial waters and a significant proportion with a shallow sea bed - notably in the North Sea. Wind shares other renewables' intermittency problems [[North Sea Wind Variability]] however, manufacturers have improved the capacity factor in the latest designs of wind turbines [[GE 1.5 MW Wind Turbine]]

== Contracts for Difference (CfD) Allocation Round One - 2015 ==

Twenty-six projects using a number of technologies - CHP, Solar PV, On-shore and Off-shore wind were the successful applicants. Offshore contributed 1162 MW out of a total 2139 MW (54%)

== Contracts for Difference (CfD) Allocation Round Two - 2017 ==

Eleven projects based on just three technologies Advanced Conversion Technologies, Dedicated Biomass with CHP and Off-shore wind submitted successful bids. Offshore contributed 3196 MW out of a total 3346 MW (96%) demonstrating that for the UK's renewable energy generation policy, offshore is becoming increasingly a 'one trick pony'

== Round 3 Offshore Wind Projects - 2019 ==

Of the 12 projects that were successful applicants for the 2019 Round 3 CfD allocation, five large offshore wind projects make up 5454 MW of the total 5775 MW (94%) and continuing the trend of fewer, bigger projects, overwhelmingly offshore wind

[[File:CfD Round 3 Projects.png|thumb]]
{| class="wikitable"
|-
! Project No. !! Project Name !! Developer !! Location !! Capacity
|-
|
|-
| 1 || Doggerbank Creyke Beck A P1 ||SSE Renewables / Equinor / Eni || Dogger Bank || 1200
|-
| 2 || Doggerbank Creyke Beck B P1 || SSE Renewables / Equinor / Eni|| Dogger Bank || 1200
|-
| 3 || Doggerbank Teeside A P1 || SSE Renewables / Equinor|| Dogger Bank || 1200
|-
| 4 || Sofia Offshore Wind Farm Phase 1 || Sofia Offshore Wind Farm Limited|| Dogger Bank || 1400
|-
| 5 || Seagreen Phase 1 || Seagreen Wind Energy Limited || Long Forties ||454
|}

Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

== Round 4 Offshore Wind Projects ==
In 2021 companies bid for "annual option fees" for the right to develop future wind farm projects. A further auction will take place under the Contract for Difference (CfD) support scheme to determine the price paid for electricity likely to be decided in 2022. Allowing for a planning process of 4-5 years the overall lead time on these projects is around 7 years. So these six projects represent the foreseeable future pipeline of offshore wind until the end of the decade.
[[File:CfD Round 4 Projects.png|thumb]]
{| class="wikitable"

|-
! Project No. !! Preferred Bidder !! Location !! Capacity
|-
|
|-
| 1 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 2 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 3 || Green Investment Group - Total || Eastern Regions || 1500 MW
|-
| 4 || Consortium of EnBW and BP || Northern Wales & Irish Sea|| 1500 MW
|-
| 5 || Offshore Wind Limited (a joint venture between Cobra Instalaciones y Servicios S.A and Flotation Energy plc) || Northern Wales & Irish Sea || 480 MW
|-
| 6 || 1500 MW || Northern Wales & Irish Sea || 1500 MW
|}
 
Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

Project sites identified from [https://www.thecrownestate.co.uk/media/3721/the-crown-estate-offshore-wind-leasing-round-4-selected-projects.pdf The Crown Estate website]

Wind Power

2021-09-24T11:14:11Z

Trevor:

Fluke commentary tends to focus on issues at the national rather than international level. If I lived in - say - Morocco, I would be considerably more excited about the potential of solar PV. But ''for the UK,'' wind power

== On-shore wind generation ==
Although now ubiquitous across the country, a cursory examination of the [https://en.wikipedia.org/wiki/List_of_onshore_wind_farms_in_the_United_Kingdom List of onshore wind farms] on Wikipedia reveal on-shore wind farms in the UK were/are:
* Relatively small developments (single figures to a few dozen wind-turbines)
* Relatively low capacity (many <10MW; most <100MW)
* Construction dates in 1990's or 2000's

==DTI on-shore wind speed database==

This data set is now moved to [[On-shore wind database]]

On-shore wind database

2021-09-24T10:34:27Z

Trevor: Created page with "=DTI on-shore wind speed database= Previously the DTI published a database of average on-shore wind speeds at 10, 25 and 45 metres above ground level (AGL) for every square k..."

=DTI on-shore wind speed database=

Previously the DTI published a database of average on-shore wind speeds at 10, 25 and 45 metres above ground level (AGL) for every square kilometre across the UK. Despite the obvious usefulness of this data, the project was discontinued and the website archived, some of the links are now broken and there is no guarantee this archived material will be retained. At the time the DTI website was live, the data files were freely available - and as a public service Fluke is making these files available now:

* [http://windgod.fluke.org.uk/database-only.zip Original DTI ASC files]
* [http://windgod.fluke.org.uk/database-and-program.zip Original DTI ASC files plus DTI software]

Although the data files have a *.asc extension they are '''NOT''' [http://resources.esri.com/help/9.3/arcgisengine/java/GP_ToolRef/spatial_analyst_tools/esri_ascii_raster_format.htm ESRI compliant] rather they are simply readable plain text 'ascii' files. Fluke carried out some original work to convert the data files from the proprietary DTI format to ESRI-compliant ASC files which '''should''' be suitable for GIS software (they have been successfully tested with Autodesk AutoCAD Map 3D 2019)

* [http://windgod.fluke.org.uk/ESRISpeed10.asc 10 metres above ground level wind speed]
* [http://windgod.fluke.org.uk/ESRISpeed25.asc 25 metres above ground level wind speed]
* [http://windgod.fluke.org.uk/ESRISpeed45.asc 45 metres above ground level wind speed]

For readers without GIS software interested in viewing the data, Fluke has produced a three page pdf showing a map of the UK colour-coded according to wind speed

Index: Page 1 = 10m AGL; Page 2 = 25m AGL; Page 3 = 45m AGL

Key: 1-3 m/s = dark grey; 3-6 m/s dull red; 6-7 m/s red; 7+ m/s yellow

* [[Media:UK_onshore_windmap.pdf|UK average windspeed map]]
* [[Media:ARCHIVED_CONTENT_Windspeed_Database_-_DTI.pdf |Archive copy of the DTI webpage. Includes references]]

The original DTI website included a calculator to display the wind speed at three elevations for any OS grid reference; Fluke may replicate this here at a later date

==Code for conversion DTI ASC to ESRI ASC==

Readers interested in verifying the conversion are welcome to experiment with the following Microsoft Excel VBA code:

Sub convert()
Dim r As Range, i As Long, j As Long, s As String, t As String, x As Long
Dim TextFile As Integer
Dim FilePath As String
Set fs = CreateObject("Scripting.FileSystemObject")
Set a = fs.CreateTextFile("C:\path\to\required\folder\output.txt", True, False)

a.WriteLine "ncols 700"
a.WriteLine "nrows 1300"
a.WriteLine "xllcorner 0"
a.WriteLine "yllcorner 0"
a.WriteLine "cellsize 1"
a.WriteLine "nodata_value -9999"

Set r = Range("a1") 'original DTI ASC file copied into column A
For i = 2 To 9095 Step 7
t = ""
For j = 0 To 6
s = r(i + j, 1)
x = InStr(1, s, ";")
s = Mid(s, x + 2, 9999)
s = Replace(s, ";", " ")
t = t + s
If j < 6 Then t = t + " "
Next j
t = Replace(t, " ", " ")
a.WriteLine t
Next i
'Save & Close Text File
a.Close
End Sub

Renewable Energy

2021-09-24T10:28:26Z

Trevor:

== Confusing energy, electricity and fuel? ==
Don't worry - you're in good company. Many politicians and journalists - ''who should know better'' - also get confused. 'Energy' and 'electricity' in particular get used interchangeably, almost as synonyms - but they're not. So you get gushing comments like:
<blockquote>"On 14 May, Britain generated a quarter of its energy from the sun - the largest proportion yet." 
BBC News Website 
31 May 2019 
</blockquote>
All electricity is energy, but not all energy is electricity. In fact most of the energy (around three-quarters) used in the UK ''isn't'' electricity - rather it comes from '''fossil fuels'''. ''Fuels'' are a source of energy rather than energy as such and are characterised by having a physical existence (solid, liquid or gas) and portability - which explains their particular usefulness in transportation.
== Renewable Energy in the United Kingdom (2020 figures) ==


So how much energy does the UK produce and consume - and how much of it comes from renewable sources?
According to the latest (2020) official figures published by the [https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1006380/Energy_flow_chart_2020.pdf Department for Business, Energy & Industrial Strategy] we used 170 million tonnes of oil equivalent
[[File:Energy flow chart 2020.png|thumb]]
Here's the breakdown:
* Gas - excluding gas for electricity generation - largely used for heating - 42 units
* Electricity - many uses - 30 units, derived from:
** 7 units from hydro, wind and solar PV
** Bio-fuels (10 units)
** Balance supplied from mostly gas, nuclear, coal and imports
* Primary demand for petroleum products - largely used for transport - 53 units
[[File:UK Mix 2020.png|thumb]]

So we can see electricity is the smallest of three broad categories of energy production/supply - about a quarter. And renewables contribute around about a quarter of ''electricity'' generation. Excluding electricity generation, there are a few examples where renewable fuels are used to supplement fossil fuels. Bio-ethanol was added as a 5% admixture to unleaded petrol (recently increased to 10%). Small amounts of bio-methane is added to (fossil) natural gas under the 'gas-to-grid' scheme. Overall, though, renewables contribute only around 10% of '''''total''''' UK energy.

Given that wind turbine and solar PV technologies produce electricity, the burden falls onto finding ways to do things which previously needed fuels and replacing by electricity. Equally challenging is transforming the 'pie' from one quarter electric to mostly electric; the implication being we need to ''quadruple'' electricity generation

Electricity ''can'' be used for heating (e.g. heat pumps) and electricity ''can'' be used for transport (electric trains, electric cars); the figures above show there is a '''huge''' shortfall perhaps by an '''order of magnitude''' which not only would cost a great deal to build, but also create logistical problems with the stability of the grid, if it were.

Presently our National (electricity) Grid compensates for renewables' [[intermittency]] to balance supply and demand by managing output from Combined Cycle Gas Turbine power stations (the work-horses of UK electricity generation) and the relatively few still operating coal-fired power stations. When these all '''close in 2025''' grid stabilisation will become harder and power shortages are a real possibility.

Without fossil-fuelled power generation to prop-up renewables, some other measure is needed to shave the peaks and fill the troughs of supply - storage is one possibility, but it is incredibly difficult and costly even at renewables' present day 25% contribution. Could '''''you''''' devise a storage strategy to balance variations in wind and solar PV to within +/- 1000 MW of the average 6700 MW (actual 2019 figures)? 
[http://windgod.fluke.org.uk/ Have a go!]

# [[Solar Power]]
# [[Wind Power]]
# [[Tidal Power]]

File:UK Mix 2020.png

2021-09-24T09:20:18Z

Trevor:

File:Energy flow chart 2020.png

2021-09-24T08:47:47Z

Trevor:

North Sea Wind Variability

2021-09-23T15:52:05Z

Trevor:

== KNMI Data Source ==

The KNMI Koninklijk Nederlands Meteorologisch Instituut (Royal Netherlands Meteorological Institute) is a useful resource of accessible and free to download data and include the [https://dataplatform.knmi.nl/dataset/knw-csv-ts-update-1-0 dataset]: '''Wind - model time series from 2014 to August 2019 at 10-200 meters above the North Sea in individual 2.5 km grid location files'''

''Would that there were an equivalent (non-paywall) resource by the UK''

The data cover a rectangular area latitude 50°N to 55°N longitude 1°E to 8°E and while this information is most of interest to the Dutch, the coverage does include Dogger Bank and is suitable for analysing the potential performance of new UK wind farm projects.

The KNW-1.0_H37-ERA_NL-001-142.csv file relates to the 2.5km² tile centred on 53.59°N 1.47°E which is located within the proposed 1.5GW Green Investment Group - Total development east of Kingston-Upon-Hull

== Validation of a Weibull distribution for hourly wind speed data ==

Using the Microsoft Excel function

={total number of measurements]WEIBULL.DIST({wind_velocity_m_s},2.318741605,11.81669862,FALSE)

it can be seen there is a good correlation between the fitted Weibull function curve (orange line) and the actual histogram data (blue bars)

[[File:Wind Speeds 2014 2019.png|thumb]]

File:Wind Speeds 2014 2019.png

2021-09-23T15:47:06Z

Trevor:

North Sea Wind Variability

2021-09-23T15:46:39Z

Trevor: Created page with "== KNMI Data Source == The KNMI Koninklijk Nederlands Meteorologisch Instituut (Royal Netherlands Meteorological Institute) is a useful resource of accessible and free to dow..."

== KNMI Data Source ==

The KNMI Koninklijk Nederlands Meteorologisch Instituut (Royal Netherlands Meteorological Institute) is a useful resource of accessible and free to download data and include the [https://dataplatform.knmi.nl/dataset/knw-csv-ts-update-1-0 dataset]: '''Wind - model time series from 2014 to August 2019 at 10-200 meters above the North Sea in individual 2.5 km grid location files'''

''Would that there were an equivalent (non-paywall) resource by the UK''

The data cover a rectangular area latitude 50°N to 55°N longitude 1°E to 8°E and while this information is most of interest to the Dutch, the coverage does include Dogger Bank and is suitable for analysing the potential performance of new UK wind farm projects.

The KNW-1.0_H37-ERA_NL-001-142.csv file relates to the 2.5km² tile centred on 53.59°N 1.47°E which is located within the proposed 1.5GW Green Investment Group - Total development east of Kingston-Upon-Hull

== Validation of a Weibull distribution for hourly wind speed data ==

Using the Microsoft Excel function

={total number of measurements]WEIBULL.DIST({wind_velocity_m_s},2.318741605,11.81669862,FALSE)

it can be seen there is a good correlation between the fitted Weibull function curve (orange line) and the actual histogram data (blue bars)

GE 1.5 MW Wind Turbine

2021-09-23T14:57:06Z

Trevor:

General Electric describe their GE 1.5sle 1.5 MW wind turbine as "the industry workhorse" and "the most widely used wind turbine in its class" with "12,000+ turbines are in operation worldwide, 19 countries, 170+ million operating hours, 100,000+ GWh produced (Data as of March, 2009)"

== Modelling the power curve ==

The theoretical relationship between wind speed and power output is a cube-law equation. In practice the power is capped at the nominal rating so above that wind speed the power is constant (up to the point where high winds require the turbine to be stopped for safety reasons)

Original work by FLUKE has identified a function available in the standard Microsoft Excel spreadsheet program that fits published data well following the general form

=P*WEIBULL.DIST(wind_velocity_m_per_s,ALPHA,BETA,TRUE)

where P is the peak rated power and ALPHA, BETA are two empirical constants chosen to 'best-fit' the data. Specifically for the GE 1.5sle:

=1500*WEIBULL.DIST(wind_velocity_m_per_s,4.3,9,TRUE)

In the graphic to the right, the red data points and trendline are the WEIBULL function; the green line actual manufacturer's data is from page 4 of the [https://geosci.uchicago.edu/~moyer/GEOS24705/Readings/GEA14954C15-MW-Broch.pdf GE brochure]

This equation is used elsewhere [[North Sea Wind Variability]] for modelling the variability of the potential POWER generation from published hourly wind-speed data
[[File:Weibull Fit.png|thumb]]

GE 1.5 MW Wind Turbine

2021-09-23T14:52:34Z

Trevor: Created page with "General Electric describe their GE 1.5sle 1.5 MW wind turbine as "the industry workhorse" and "the most widely used wind turbine in its class" with "12,000+ turbines are in op..."

General Electric describe their GE 1.5sle 1.5 MW wind turbine as "the industry workhorse" and "the most widely used wind turbine in its class" with "12,000+ turbines are in operation worldwide, 19 countries, 170+ million operating hours, 100,000+ GWh produced (Data as of March, 2009)"

== Modelling the power curve ==

The theoretical relationship between wind speed and power output is a cube-law equation. In practice the power is capped at the nominal rating so above that wind speed the power is constant (up to the point where high winds require the turbine to be stopped for safety reasons)

Original work by FLUKE has identified a function available in the standard Microsoft Excel spreadsheet program that fits published data well following the general form

=P*WEIBULL.DIST(wind_velocity_m_per_s,ALPHA,BETA,TRUE)

where P is the peak rated power and ALPHA, BETA are two empirical constants chosen to 'best-fit' the data. Specifically for the GE 1.5sle:

=1500*WEIBULL.DIST(wind_velocity_m_per_s,4.3,9,TRUE)

In the graphic to the right, the red data points and trendline are the WEIBULL function; the green line actual manufacturer's data is from page 4 of the [https://geosci.uchicago.edu/~moyer/GEOS24705/Readings/GEA14954C15-MW-Broch.pdf GE brochure]

This equation is used elsewhere for modelling the variability of the potential POWER generation from published hourly wind-speed data
[[File:Weibull Fit.png|thumb]]

File:Weibull Fit.png

2021-09-23T14:44:35Z

Trevor:

Weibull Fit

Off-shore Wind Power

2021-09-23T14:11:56Z

Trevor:

It is difficult to overstate the importance of offshore wind's contribution to the UK's renewable electricity generation capacity. As an island, the country has a large area of surrounding territorial waters and a significant proportion with a shallow sea bed - notably in the North Sea. Wind shares other renewables' intermittency problems [[North Sea Wind Variability]] however, manufacturers have improved the capacity factor in the latest designs of wind turbines [[GE 1.5 MW Wind Turbine]]

== Contracts for Difference (CfD) Allocation Round One - 2015 ==

Twenty-six projects using a number of technologies - CHP, Solar PV, On-shore and Off-shore wind were the successful applicants. Offshore contributed 1162 MW out of a total 2139 MW (54%)

== Contracts for Difference (CfD) Allocation Round Two - 2017 ==

Eleven projects based on just three technologies Advanced Conversion Technologies, Dedicated Biomass with CHP and Off-shore wind submitted successful bids. Offshore contributed 3196 MW out of a total 3346 MW (96%) demonstrating that for the UK's renewable energy generation policy, offshore is becoming increasingly a 'one trick pony'

== Round 3 Offshore Wind Projects - 2019 ==

Of the 12 projects that were successful applicants for the 2019 Round 3 CfD allocation, five large offshore wind projects make up 5454 MW of the total 5775 MW (94%) and continuing the trend of fewer, bigger projects, overwhelmingly offshore wind

[[File:CfD Round 3 Projects.png|thumb]]
{| class="wikitable"
|-
! Project No. !! Project Name !! Developer !! Location !! Capacity
|-
|
|-
| 1 || Doggerbank Creyke Beck A P1 ||SSE Renewables / Equinor / Eni || Dogger Bank || 1200
|-
| 2 || Doggerbank Creyke Beck B P1 || SSE Renewables / Equinor / Eni|| Dogger Bank || 1200
|-
| 3 || Doggerbank Teeside A P1 || SSE Renewables / Equinor|| Dogger Bank || 1200
|-
| 4 || Sofia Offshore Wind Farm Phase 1 || Sofia Offshore Wind Farm Limited|| Dogger Bank || 1400
|-
| 5 || Seagreen Phase 1 || Seagreen Wind Energy Limited || Long Forties ||454
|}

Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

== Round 4 Offshore Wind Projects ==
In 2021 companies bid for "annual option fees" for the right to develop future wind farm projects. A further auction will take place under the Contract for Difference (CfD) support scheme to determine the price paid for electricity likely to be decided in 2022. Allowing for a planning process of 4-5 years the overall lead time on these projects is around 7 years. So these six projects represent the foreseeable future pipeline of offshore wind until the end of the decade.
[[File:CfD Round 4 Projects.png|thumb]]
{| class="wikitable"

|-
! Project No. !! Preferred Bidder !! Location !! Capacity
|-
|
|-
| 1 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 2 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 3 || Green Investment Group - Total || Easter Regions || 1500 MW
|-
| 4 || Consortium of EnBW and BP || Northern Wales & Irish Sea|| 1500 MW
|-
| 5 || Offshore Wind Limited (a joint venture between Cobra Instalaciones y Servicios S.A and Flotation Energy plc) || Northern Wales & Irish Sea || 480 MW
|-
| 6 || 1500 MW || Northern Wales & Irish Sea || 1500 MW
|}
 
Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

Project sites identified from [https://www.thecrownestate.co.uk/media/3721/the-crown-estate-offshore-wind-leasing-round-4-selected-projects.pdf The Crown Estate website]

Off-shore Wind Power

2021-09-23T13:56:37Z

Trevor:

== Contracts for Difference (CfD) Allocation Round One - 2015 ==

Twenty-six projects using a number of technologies - CHP, Solar PV, On-shore and Off-shore wind were the successful applicants. Offshore contributed 1162 MW out of a total 2139 MW (54%)

== Contracts for Difference (CfD) Allocation Round Two - 2017 ==

Eleven projects based on just three technologies Advanced Conversion Technologies, Dedicated Biomass with CHP and Off-shore wind submitted successful bids. Offshore contributed 3196 MW out of a total 3346 MW (96%) demonstrating that for the UK's renewable energy generation policy, offshore is becoming increasingly a 'one trick pony'

== Round 3 Offshore Wind Projects - 2019 ==

Of the 12 projects that were successful applicants for the 2019 Round 3 CfD allocation, five large offshore wind projects make up 5454 MW of the total 5775 MW (94%) and continuing the trend of fewer, bigger projects, overwhelmingly offshore wind

[[File:CfD Round 3 Projects.png|thumb]]
{| class="wikitable"
|-
! Project No. !! Project Name !! Developer !! Location !! Capacity
|-
|
|-
| 1 || Doggerbank Creyke Beck A P1 ||SSE Renewables / Equinor / Eni || Dogger Bank || 1200
|-
| 2 || Doggerbank Creyke Beck B P1 || SSE Renewables / Equinor / Eni|| Dogger Bank || 1200
|-
| 3 || Doggerbank Teeside A P1 || SSE Renewables / Equinor|| Dogger Bank || 1200
|-
| 4 || Sofia Offshore Wind Farm Phase 1 || Sofia Offshore Wind Farm Limited|| Dogger Bank || 1400
|-
| 5 || Seagreen Phase 1 || Seagreen Wind Energy Limited || Long Forties ||454
|}

Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

== Round 4 Offshore Wind Projects ==
In 2021 companies bid for "annual option fees" for the right to develop future wind farm projects. A further auction will take place under the Contract for Difference (CfD) support scheme to determine the price paid for electricity likely to be decided in 2022. Allowing for a planning process of 4-5 years the overall lead time on these projects is around 7 years. So these six projects represent the foreseeable future pipeline of offshore wind until the end of the decade.
[[File:CfD Round 4 Projects.png|thumb]]
{| class="wikitable"

|-
! Project No. !! Preferred Bidder !! Location !! Capacity
|-
|
|-
| 1 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 2 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 3 || Green Investment Group - Total || Easter Regions || 1500 MW
|-
| 4 || Consortium of EnBW and BP || Northern Wales & Irish Sea|| 1500 MW
|-
| 5 || Offshore Wind Limited (a joint venture between Cobra Instalaciones y Servicios S.A and Flotation Energy plc) || Northern Wales & Irish Sea || 480 MW
|-
| 6 || 1500 MW || Northern Wales & Irish Sea || 1500 MW
|}
 
Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

Project sites identified from [https://www.thecrownestate.co.uk/media/3721/the-crown-estate-offshore-wind-leasing-round-4-selected-projects.pdf The Crown Estate website]

Off-shore Wind Power

2021-09-23T13:08:13Z

Trevor:

== Round 3 Offshore Wind Projects ==
[[File:CfD Round 3 Projects.png|thumb]]
{| class="wikitable"
|-
! Project No. !! Project Name !! Developer !! Location !! Capacity
|-
|
|-
| 1 || Doggerbank Creyke Beck A P1 ||SSE Renewables / Equinor / Eni || Dogger Bank || 1200
|-
| 2 || Doggerbank Creyke Beck B P1 || SSE Renewables / Equinor / Eni|| Dogger Bank || 1200
|-
| 3 || Doggerbank Teeside A P1 || SSE Renewables / Equinor|| Dogger Bank || 1200
|-
| 4 || Sofia Offshore Wind Farm Phase 1 || Sofia Offshore Wind Farm Limited|| Dogger Bank || 1400
|-
| 5 || Seagreen Phase 1 || Seagreen Wind Energy Limited || Long Forties ||454
|}

Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

== Round 4 Offshore Wind Projects ==
In 2021 companies bid for "annual option fees" for the right to develop future wind farm projects. A further auction will take place under the Contract for Difference (CfD) support scheme to determine the price paid for electricity likely to be decided in 2022. Allowing for a planning process of 4-5 years the overall lead time on these projects is around 7 years. So these six projects represent the foreseeable future pipeline of offshore wind until the end of the decade.
[[File:CfD Round 4 Projects.png|thumb]]
{| class="wikitable"

|-
! Project No. !! Preferred Bidder !! Location !! Capacity
|-
|
|-
| 1 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 2 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 3 || Green Investment Group - Total || Easter Regions || 1500 MW
|-
| 4 || Consortium of EnBW and BP || Northern Wales & Irish Sea|| 1500 MW
|-
| 5 || Offshore Wind Limited (a joint venture between Cobra Instalaciones y Servicios S.A and Flotation Energy plc) || Northern Wales & Irish Sea || 480 MW
|-
| 6 || 1500 MW || Northern Wales & Irish Sea || 1500 MW
|}
 
Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

Project sites identified from [https://www.thecrownestate.co.uk/media/3721/the-crown-estate-offshore-wind-leasing-round-4-selected-projects.pdf The Crown Estate website]

File:CfD Round 3 Projects.png

2021-09-23T12:50:19Z

Trevor:

Off-shore Wind Power

2021-09-23T12:49:54Z

Trevor:

== Round 3 Offshore Wind Projects ==

{| class="wikitable"
|-
! Project No. !! Project Name !! Developer !! Location !! Capacity
|-
|
|-
| 1 || Doggerbank Creyke Beck A P1 ||SSE Renewables / Equinor / Eni || Dogger Bank || 1200
|-
| 2 || Doggerbank Creyke Beck B P1 || SSE Renewables / Equinor / Eni|| Dogger Bank || 1200
|-
| 3 || Doggerbank Teeside A P1 || SSE Renewables / Equinor|| Dogger Bank || 1200
|-
| 4 || Sofia Offshore Wind Farm Phase 1 || Sofia Offshore Wind Farm Limited|| Dogger Bank || 1400
|-
| 5 || Seagreen Phase 1 || Seagreen Wind Energy Limited || Long Forties ||454
|}

== Round 4 Offshore Wind Projects ==
In 2021 companies bid for "annual option fees" for the right to develop future wind farm projects. A further auction will take place under the Contract for Difference (CfD) support scheme to determine the price paid for electricity likely to be decided in 2022. Allowing for a planning process of 4-5 years the overall lead time on these projects is around 7 years. So these six projects represent the foreseeable future pipeline of offshore wind until the end of the decade.
{| class="wikitable"

|-
! Project No. !! Preferred Bidder !! Location !! Capacity
|-
|
|-
| 1 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 2 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 3 || Green Investment Group - Total || Easter Regions || 1500 MW
|-
| 4 || Consortium of EnBW and BP || Northern Wales & Irish Sea|| 1500 MW
|-
| 5 || Offshore Wind Limited (a joint venture between Cobra Instalaciones y Servicios S.A and Flotation Energy plc) || Northern Wales & Irish Sea || 480 MW
|-
| 6 || 1500 MW || Northern Wales & Irish Sea || 1500 MW

|}
[[File:CfD Round 4 Projects.png|left|thumb]]
Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

Project sites identified from [https://www.thecrownestate.co.uk/media/3721/the-crown-estate-offshore-wind-leasing-round-4-selected-projects.pdf The Crown Estate website]

Off-shore Wind Power

2021-09-23T12:08:01Z

Trevor: /* Round 4 Offshore Wind Projects */

== Round 3 Offshore Wind Projects ==
{| class="wikitable"

|-
! Project No. !! Project Name !! Developer !! Location !! Capacity

|-
|
|-
| 1 || Doggerbank Creyke Beck A P1 ||SSE Renewables / Equinor / Eni|| Dogger Bank||1200
|-
| 2 || Doggerbank Creyke Beck B P1 SSE Renewables / Equinor / Eni 1200
|-
| 3 || Doggerbank Teeside A P1 SSE Renewables / Equinor 1200
|-
| 4 || Sofia Offshore Wind Farm Phase 1 Sofia Offshore Wind Farm Limited 1400
|-
| 5 || Seagreen Phase 1 Seagreen Wind Energy Limited 454
|}

== Round 4 Offshore Wind Projects ==
In 2021 companies bid for "annual option fees" for the right to develop future wind farm projects. A further auction will take place under the Contract for Difference (CfD) support scheme to determine the price paid for electricity likely to be decided in 2022. Allowing for a planning process of 4-5 years the overall lead time on these projects is around 7 years. So these six projects represent the foreseeable future pipeline of offshore wind until the end of the decade.
{| class="wikitable"

|-
! Project No. !! Preferred Bidder !! Location !! Capacity
|-
|
|-
| 1 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 2 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 3 || Green Investment Group - Total || Easter Regions || 1500 MW
|-
| 4 || Consortium of EnBW and BP || Northern Wales & Irish Sea|| 1500 MW
|-
| 5 || Offshore Wind Limited (a joint venture between Cobra Instalaciones y Servicios S.A and Flotation Energy plc) || Northern Wales & Irish Sea || 480 MW
|-
| 6 || 1500 MW || Northern Wales & Irish Sea || 1500 MW

|}
[[File:CfD Round 4 Projects.png|left|thumb]]
Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

Project sites identified from [https://www.thecrownestate.co.uk/media/3721/the-crown-estate-offshore-wind-leasing-round-4-selected-projects.pdf The Crown Estate website]

Off-shore Wind Power

2021-09-23T10:53:36Z

Trevor: /* CfD Round 4 Offshore Wind Projects */

== Round 4 Offshore Wind Projects ==

In 2021 companies bid for "annual option fees" for the right to develop future wind farm projects. A further auction will take place under the Contract for Difference (CfD) support scheme to determine the price paid for electricity likely to be decided in 2022. Allowing for a planning process of 4-5 years the overall lead time on these projects is around 7 years. So these six projects represent the foreseeable future pipeline of offshore wind until the end of the decade.
{| class="wikitable"

|-
! Project No. !! Preferred Bidder !! Location !! Capacity
|-
|
|-
| 1 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 2 || RWE Renewables || Dogger Bank || 1500 MW
|-
| 3 || Green Investment Group - Total || Easter Regions || 1500 MW
|-
| 4 || Consortium of EnBW and BP || Northern Wales & Irish Sea|| 1500 MW
|-
| 5 || Offshore Wind Limited (a joint venture between Cobra Instalaciones y Servicios S.A and Flotation Energy plc) || Northern Wales & Irish Sea || 480 MW
|-
| 6 || 1500 MW || Northern Wales & Irish Sea || 1500 MW

|}
[[File:CfD Round 4 Projects.png|left|thumb]]
Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

Project sites identified from [https://www.thecrownestate.co.uk/media/3721/the-crown-estate-offshore-wind-leasing-round-4-selected-projects.pdf The Crown Estate website]

Off-shore Wind Power

2021-09-23T10:19:39Z

Trevor:

== CfD Round 4 Offshore Wind Projects ==

{| class="wikitable"

|-
! Project No. !! Project Name !! Developer !! Location !! Capacity
|-
|
|-
| 1 || abc || RWE Renewables || Dogger Bank || 1500 MW
|-
| 2 || def || RWE Renewables || Dogger Bank || 1500 MW
|-
| 3 || ghi || Green Investment Group - Total || Easter Regions || 1500 MW
|-
| 4 || jkl || Consortium of EnBW and BP || Northern Wales & Irish Sea|| 1500 MW
|-
| 5 || mno || Offshore Wind Limited (a joint venture between Cobra Instalaciones y Servicios S.A and Flotation Energy plc) || Northern Wales & Irish Sea || 480 MW
|-
| 6 || pqr || 1500 MW || Northern Wales & Irish Sea || 1500 MW

|}
[[File:CfD Round 4 Projects.png|left|thumb]]
Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

Project sites identified from [https://www.thecrownestate.co.uk/media/3721/the-crown-estate-offshore-wind-leasing-round-4-selected-projects.pdf The Crown Estate website]

File:CfD Round 4 Projects.png

2021-09-23T10:14:58Z

Trevor:

Off-shore Wind Power

2021-09-23T10:13:10Z

Trevor: Created page with "== CfD Round 4 Offshore Wind Projects == {| class="wikitable" |- ! Project No. !! Project Name !! Developer !! Location !! Capacity |- | |- | 1 || abc || RWE Renewables ||..."

== CfD Round 4 Offshore Wind Projects ==

{| class="wikitable"

|-
! Project No. !! Project Name !! Developer !! Location !! Capacity
|-
|
|-
| 1 || abc || RWE Renewables || Dogger Bank || 1500 MW
|-
| 2 || def || RWE Renewables || Dogger Bank || 1500 MW
|-
| 3 || ghi || Green Investment Group - Total || Easter Regions || 1500 MW
|-
| 4 || jkl || Consortium of EnBW and BP || Northern Wales & Irish Sea|| 1500 MW
|-
| 5 || mno || Offshore Wind Limited (a joint venture between Cobra Instalaciones y Servicios S.A and Flotation Energy plc) || Northern Wales & Irish Sea || 480 MW
|-
| 6 || pqr || 1500 MW || Northern Wales & Irish Sea || 1500 MW

|}

Map data source: Ordnance Survey MiniScale covered by the Open Government Licence (OGL). Contains OS data © Crown copyright and database right 2021

Project sites identified from [https://www.thecrownestate.co.uk/media/3721/the-crown-estate-offshore-wind-leasing-round-4-selected-projects.pdf The Crown Estate website]

Air Source Heat Pump

2021-09-21T13:06:16Z

Trevor: /* Economics */

== Basic principle of the Air Source Heat Pump (ASHP) ==

A Heat Pump is a mechanical device for extracting heat from a lower-temperature source and delivering it to a higher-temperature medium. The word 'pump' is used by analogy with that familiar device for raising water from a lower to higher elevation. In either case, mechanical energy is expended to reverse a natural, spontaneous flow of heat from hot to cold - or water from above to below. The operating principal for a heat pump is very similar to a refrigerator or an air conditioning unit; the main distinction being whether heating or cooling is regarded as the 'useful' task; the term heat pump is generally used where '''heating''' is the desired result. From the energy balance:

Heatextracted + Workinput = Heatoutput

it can be seen that output heat is always greater than the input work and the ratio of heat to work necessarily exceeds 1. This is sometimes referred to (inaccurately) as heat pumps having an efficiency greater than 100%; engineers prefer the term 'coefficient of performance' or COP:

COP = Heatoutput / Workinput

Under favourable conditions, an electric-powered ASHP with a HFC working-fluid operating to a reverse Rankine cycle may achieve COP values in the range 2.5 to 3; that is for every 1 kW-h of electricity consumed, 2.5-3 kW-h of heat is produced. The COP is not, however a fixed value. By extending the pump analogy the greater the head of water pumped, the more power is required. Likewise heat pumps perform less efficiently on cold days than mild ones - ''the opposite way to what might be desired''

A typical domestic ASHP, positioned outside the house, is a box-shaped housing containing fans plus the mechanisms to extract heat. Fans draw outdoor air over rows of tubes containing the cold '''working fluid''' which, being even colder than the outside air is 'warmed' by the air (relatively speaking); the air is simultaneously cooled. Through a somewhat complex closed-loop cycle the '''working fluid''' so warmed is first compressed, raising its temperature so it can provide 'useful' heat. It is then expanded, returning to its original cold state and ready to absorb more heat from the air.

Heat pumps of the air-to-air type extract heat from outdoor air to heat indoor air which is circulated for space heating only (like a convection heater). Air-to-water ''extract'' heat in exactly the same way but ''provide'' heat to the house in the form of hot water, which can be used for both space heating via the central heating system and domestic hot water, potentially replacing the gas boiler and the immersion heater

== Heat availability and performance in the UK climate ==
 
[[File:ASHP.png|800px|frameless|left]] 

In calm air conditions, the heat in a volume of air surrounding one individual property can be calculated from its dimensions, the density and specific heat capacity of air and the air's temperature before and after heat is extracted. So for a plot size of 12 metres by 18 to a height of 10 metres (2,160 m³), an initial temperature of 10°C and final temperature 1°C
Density of air @ 1 atmosphere / 10°C = 1.25 kg/m³
Specific heat capacity of air @ 1 atmosphere / 10°C = 1.00 kJ/kg/°C
Mass of air = 1.25 * 2160 = 2,700 kg
Heat content = 2,700 * 1.00 * (10 - 1) = 24,300 kJ (or 6.8 kW-h)
An ASHP operating at a COP of 3 would produce ~ 10.2 kW-h for the house (6.8 kW-h air-sourced heat plus 3.4 kW-h electricity = 10.2 kW-h; 10.2 / 3.4 = 3, the COP) which means the house could be heated at 2kW for 5 hours

10°C is the year-round average temperature (day & night, all seasons) for much of the UK and would be regarded as mild - in winter. ASHPs have been used successfully in Scandinavian climates with air temperatures -10°C or lower '''''- but this is dry air'''''. With the exception of this [http://www.davidstrong.co.uk/web_documents/air_source_heatpumps1.pdf Paper by Professor David Strong] FLUKE has seen little research on the practical application of ASHPs, under conditions which anyone with a passing familiarity with the British 'maritime' climate would recognise
* cold - say 1 to 5°C
* wet - rain, drizzle, mist etc.
under these conditions it is a near-certainty the ASHP will ice-up causing it not only to cease providing heat completely but actually require a heat '''input''' for the defrost cycle

Some real-life consumers' experiences are documented [https://www.carboncommentary.com/blog/2013/03/25/time-to-stop-promoting-air-source-heat-pumps-and-ask-why-they-dont-work-in-the-uk here]

If a large array of ASHPs are adopted as in the illustration resulting in the surrounding air temperature dropping from 10°C to 1°C, according to the 'degree-days' method of estimating heat demand, the rate of heat loss from a house might be expected to increase by a factor of (15.5-1)/(15.5-10) = 2.6 times

A layer of cold air close to the ground - when it occurs naturally - is called a temperature inversion, often associated with a low level layer of mist or fog. The phenomenon is also associated with trapping air pollutants.

=== The marketing view ===

[[File:Eonthumb.png|frameless|left|link=https://www.facebook.com/watch/?v=1644804825584998]]
 

=== The consumers' view ===

Some real-life consumers' experiences are documented [https://www.carboncommentary.com/blog/2013/03/25/time-to-stop-promoting-air-source-heat-pumps-and-ask-why-they-dont-work-in-the-uk at Carbon Commentary]

== A simple model for estimating Air Source Heat Pump performance ==

The Building Research Establishment carried out tests [http://web.archive.org/web/20181123111606/http://www.e-si.com/downloads/BRE%20Test%20Report%20Mitsi_W90.pdf BRE Test Report] on a Mitsubishi PUHZ-W90VHA air-to-water heat pump and the test results presented in table 3 of that document were analysed against a reverse-Carnot cycle ('''original work by FLUKE'''). The Carnot cycle describes the maximum theoretical efficiency of ''ANY'' thermodynamic process and has the advantage that it can be calculated without any knowledge of the device, but simply from two temperatures expressed in degrees Kelvin: the cold and hot limits of the process, in this case the outside air heat source temperature and the supply temperature to hot water for space heating. So the two equations are

COPACTUAL = Heat output (kW) / Electrical power input (kW) ''… as reported''

COPCARNOT = 1 / ( 1 - TCOLD / THOT ) ''… T in Kelvin''

which when expressed in Celsius and rearranged gives:

COPCARNOT = (tHOT + 273) / (tHOT - tCOLD) ''… t in Celsius''

The average value over 30 tests for COPACTUAL/COPCARNOT is 0.342 so the COP value for the Mitsubishi heat pump can be estimated simply from the outdoor air temperature and the hot water supply temperature from the equation:

COPCALC = 0.342 * (tHOT + 273) / (tHOT - tCOLD) ''… t in Celsius''

Other makes and models of ASHP may be expected to have factors slightly higher or lower than 0.342. To assess the validity of the model, calculated versus actual (test) values of COP are presented below:

[[File:ASHPmodel.png|480px|frameless|left]] 
== Application of the model to a case study ==

Armed with a simple equation to calculate COP and 'degree day' data averaged over 20 years (method discussed elsewhere) , a case study 'typical' house can be modelled based on providing heat for space heating and domestic hot water using the heat pump instead of a gas boiler that would otherwise have a 'medium' gas consumption of 12,000 kW-h per year (OFGEM). The supply temperature is 55°C so that the ASHP can be used as a retrofit to a normal central heating system for economy (compared to say, replacing with brand new low-temperature underfloor heating). The outside temperature is assumed to be constant at the monthly average and heat demand is weighted accordingly

{| class="wikitable"
|-
! Month !! 20-year average degree days !! Days/month !! Mean temperature below 15.5C !! Mean temperature !! THOT K !! TCOLD K !! COPCARNOT !! COPCALC !! Mean monthly heat demand kW !! Mean monthly motor power kW
|-
|A|| B|| C|| D=B/C || E=15.5-D || F || G=E+273 || H || I=0.342*H || J || K=J/I
|-
|January || 362 || 31 || 11.7 || 3.8 || 328 || 276.8 || 6.41 || 2.19 || 2.43 || 1.11
|-
|February || 318 || 28 || 11.4 || 4.1 || 328 || 277.1 || 6.45 || 2.21 || 2.13 || 0.97
|-
|March || 299 || 31 || 9.6 || 5.9 || 328 || 278.9 || 6.67 || 2.28 || 2.00 || 0.88
|-
|April || 235 || 30 || 7.8 || 7.7 || 328 || 280.7 || 6.93 || 2.37 || 1.57 || 0.66
|-
|May || 156 || 31 || 5.0 || 10.5 || 328 || 283.5 || 7.37 || 2.52 || 1.05 || 0.42
|-
|June || 90 || 30 || 3.0 || 12.5 || 328 || 285.5 || 7.72 || 2.64 || 0.60 || 0.23
|-
|July || 45 || 31 || 1.5 || 14.0 || 328 || 287.0 || 8.01 || 2.74 || 0.30 || 0.11
|-
|August || 52 || 31 || 1.7 || 13.8 || 328 || 286.8 || 7.97 || 2.72 || 0.35 || 0.13
|-
|September || 95 || 30 || 3.2 || 12.3 || 328 || 285.3 || 7.69 || 2.63 || 0.64 || 0.24
|-
|October || 183 || 31 || 5.9 || 9.6 || 328 || 282.6 || 7.22 || 2.47 || 1.23 || 0.50
|-
|November || 270 || 30 || 9.0 || 6.5 || 328 || 279.5 || 6.76 || 2.31 || 1.81 || 0.78
|-
|December || 348 || 31 || 11.2 || 4.3 || 328 || 277.3 || 6.47 || 2.21 || 2.33 || 1.05
|-
| '''Totals''' || '''2453''' || || || || || || || || '''11,967''' || '''5,147'''
|-
| || °day|| || || || || || || || kW-hth/year || kW-he/year
|}

== Economics ==

According to the [https://www.moneyadviceservice.org.uk/blog/how-much-is-the-average-gas-and-electricity-bill-per-month Money Advice Service] the average cost to the UK consumer in 2018 of gas was 4.5p per kW-h and of electricity 18.4p per kW-h. 12,000 kW-h of heat would therefore cost £540 from a conventional gas boiler compared to £947 from an ASHP. However, under the Renewable Heat Incentive (RHI) - a government subsidy scheme designed to encourage uptake of renewable technologies - applicants can claim 10.71p per kW-h for heat provided by an ASHP, so an ''income'' of £1,285 per year, for 7 years.

The Domestic RHI scheme scheme closes to new applications at the end of 31 March 2022.

Indicative cost for a complete ASHP system is £5,000-£10,000 see [https://www.cse.org.uk/downloads/file/cost-of-carbon-reduction-in-new-buildings.pdf Centre for Sustainable Energy] Appendix C. Taking the mid-value (£7,500) costs over a '''20 year''' period can be compared:

* Status quo (gas boiler); cost of gas = £10,800
* ASHP (equipment cost + electricity - RHI payments) = £17,445 (post 31 March 2022 £26,440)

== Conclusions ==

Air Source Heat Pump (ASHP) technology is a method for converting one unit of electrical energy to two - or more - units of heat energy.

Considering ASHP adoption is a central plank of the UK government's strategy for decarbonising home heating, ASHP application in Britain's cold, wet maritime climate has NOT been well studied

In original work by FLUKE performance test results (by BRE) for an ASHP were modelled with reasonable accuracy (R2 = 0.9268). The derived equation depends only on outside temperature, heat supply temperature and one empirically determined constant.

Using the equation, for the case study conditions described above the ASHP could deliver 12,000 kW-h of heat per year, as space heating and domestic hot water to the house for the expenditure of 5,150 kW-h electrical power. This would represent a COP value of 2.33 - rather less the figure 2.5 to 3 sometimes claimed for the technology

Even allowing for the RHI subsidy payments, ASHP is more expensive than a gas boiler. If the ASHP were supplied free-of-charge ''and'' RHI payments were received, the cost for ASHP is marginally less

Air Source Heat Pump

2021-09-21T12:46:59Z

Trevor:

== Basic principle of the Air Source Heat Pump (ASHP) ==

A Heat Pump is a mechanical device for extracting heat from a lower-temperature source and delivering it to a higher-temperature medium. The word 'pump' is used by analogy with that familiar device for raising water from a lower to higher elevation. In either case, mechanical energy is expended to reverse a natural, spontaneous flow of heat from hot to cold - or water from above to below. The operating principal for a heat pump is very similar to a refrigerator or an air conditioning unit; the main distinction being whether heating or cooling is regarded as the 'useful' task; the term heat pump is generally used where '''heating''' is the desired result. From the energy balance:

Heatextracted + Workinput = Heatoutput

it can be seen that output heat is always greater than the input work and the ratio of heat to work necessarily exceeds 1. This is sometimes referred to (inaccurately) as heat pumps having an efficiency greater than 100%; engineers prefer the term 'coefficient of performance' or COP:

COP = Heatoutput / Workinput

Under favourable conditions, an electric-powered ASHP with a HFC working-fluid operating to a reverse Rankine cycle may achieve COP values in the range 2.5 to 3; that is for every 1 kW-h of electricity consumed, 2.5-3 kW-h of heat is produced. The COP is not, however a fixed value. By extending the pump analogy the greater the head of water pumped, the more power is required. Likewise heat pumps perform less efficiently on cold days than mild ones - ''the opposite way to what might be desired''

A typical domestic ASHP, positioned outside the house, is a box-shaped housing containing fans plus the mechanisms to extract heat. Fans draw outdoor air over rows of tubes containing the cold '''working fluid''' which, being even colder than the outside air is 'warmed' by the air (relatively speaking); the air is simultaneously cooled. Through a somewhat complex closed-loop cycle the '''working fluid''' so warmed is first compressed, raising its temperature so it can provide 'useful' heat. It is then expanded, returning to its original cold state and ready to absorb more heat from the air.

Heat pumps of the air-to-air type extract heat from outdoor air to heat indoor air which is circulated for space heating only (like a convection heater). Air-to-water ''extract'' heat in exactly the same way but ''provide'' heat to the house in the form of hot water, which can be used for both space heating via the central heating system and domestic hot water, potentially replacing the gas boiler and the immersion heater

== Heat availability and performance in the UK climate ==
 
[[File:ASHP.png|800px|frameless|left]] 

In calm air conditions, the heat in a volume of air surrounding one individual property can be calculated from its dimensions, the density and specific heat capacity of air and the air's temperature before and after heat is extracted. So for a plot size of 12 metres by 18 to a height of 10 metres (2,160 m³), an initial temperature of 10°C and final temperature 1°C
Density of air @ 1 atmosphere / 10°C = 1.25 kg/m³
Specific heat capacity of air @ 1 atmosphere / 10°C = 1.00 kJ/kg/°C
Mass of air = 1.25 * 2160 = 2,700 kg
Heat content = 2,700 * 1.00 * (10 - 1) = 24,300 kJ (or 6.8 kW-h)
An ASHP operating at a COP of 3 would produce ~ 10.2 kW-h for the house (6.8 kW-h air-sourced heat plus 3.4 kW-h electricity = 10.2 kW-h; 10.2 / 3.4 = 3, the COP) which means the house could be heated at 2kW for 5 hours

10°C is the year-round average temperature (day & night, all seasons) for much of the UK and would be regarded as mild - in winter. ASHPs have been used successfully in Scandinavian climates with air temperatures -10°C or lower '''''- but this is dry air'''''. With the exception of this [http://www.davidstrong.co.uk/web_documents/air_source_heatpumps1.pdf Paper by Professor David Strong] FLUKE has seen little research on the practical application of ASHPs, under conditions which anyone with a passing familiarity with the British 'maritime' climate would recognise
* cold - say 1 to 5°C
* wet - rain, drizzle, mist etc.
under these conditions it is a near-certainty the ASHP will ice-up causing it not only to cease providing heat completely but actually require a heat '''input''' for the defrost cycle

Some real-life consumers' experiences are documented [https://www.carboncommentary.com/blog/2013/03/25/time-to-stop-promoting-air-source-heat-pumps-and-ask-why-they-dont-work-in-the-uk here]

If a large array of ASHPs are adopted as in the illustration resulting in the surrounding air temperature dropping from 10°C to 1°C, according to the 'degree-days' method of estimating heat demand, the rate of heat loss from a house might be expected to increase by a factor of (15.5-1)/(15.5-10) = 2.6 times

A layer of cold air close to the ground - when it occurs naturally - is called a temperature inversion, often associated with a low level layer of mist or fog. The phenomenon is also associated with trapping air pollutants.

=== The marketing view ===

[[File:Eonthumb.png|frameless|left|link=https://www.facebook.com/watch/?v=1644804825584998]]
 

=== The consumers' view ===

Some real-life consumers' experiences are documented [https://www.carboncommentary.com/blog/2013/03/25/time-to-stop-promoting-air-source-heat-pumps-and-ask-why-they-dont-work-in-the-uk at Carbon Commentary]

== A simple model for estimating Air Source Heat Pump performance ==

The Building Research Establishment carried out tests [http://web.archive.org/web/20181123111606/http://www.e-si.com/downloads/BRE%20Test%20Report%20Mitsi_W90.pdf BRE Test Report] on a Mitsubishi PUHZ-W90VHA air-to-water heat pump and the test results presented in table 3 of that document were analysed against a reverse-Carnot cycle ('''original work by FLUKE'''). The Carnot cycle describes the maximum theoretical efficiency of ''ANY'' thermodynamic process and has the advantage that it can be calculated without any knowledge of the device, but simply from two temperatures expressed in degrees Kelvin: the cold and hot limits of the process, in this case the outside air heat source temperature and the supply temperature to hot water for space heating. So the two equations are

COPACTUAL = Heat output (kW) / Electrical power input (kW) ''… as reported''

COPCARNOT = 1 / ( 1 - TCOLD / THOT ) ''… T in Kelvin''

which when expressed in Celsius and rearranged gives:

COPCARNOT = (tHOT + 273) / (tHOT - tCOLD) ''… t in Celsius''

The average value over 30 tests for COPACTUAL/COPCARNOT is 0.342 so the COP value for the Mitsubishi heat pump can be estimated simply from the outdoor air temperature and the hot water supply temperature from the equation:

COPCALC = 0.342 * (tHOT + 273) / (tHOT - tCOLD) ''… t in Celsius''

Other makes and models of ASHP may be expected to have factors slightly higher or lower than 0.342. To assess the validity of the model, calculated versus actual (test) values of COP are presented below:

[[File:ASHPmodel.png|480px|frameless|left]] 
== Application of the model to a case study ==

Armed with a simple equation to calculate COP and 'degree day' data averaged over 20 years (method discussed elsewhere) , a case study 'typical' house can be modelled based on providing heat for space heating and domestic hot water using the heat pump instead of a gas boiler that would otherwise have a 'medium' gas consumption of 12,000 kW-h per year (OFGEM). The supply temperature is 55°C so that the ASHP can be used as a retrofit to a normal central heating system for economy (compared to say, replacing with brand new low-temperature underfloor heating). The outside temperature is assumed to be constant at the monthly average and heat demand is weighted accordingly

{| class="wikitable"
|-
! Month !! 20-year average degree days !! Days/month !! Mean temperature below 15.5C !! Mean temperature !! THOT K !! TCOLD K !! COPCARNOT !! COPCALC !! Mean monthly heat demand kW !! Mean monthly motor power kW
|-
|A|| B|| C|| D=B/C || E=15.5-D || F || G=E+273 || H || I=0.342*H || J || K=J/I
|-
|January || 362 || 31 || 11.7 || 3.8 || 328 || 276.8 || 6.41 || 2.19 || 2.43 || 1.11
|-
|February || 318 || 28 || 11.4 || 4.1 || 328 || 277.1 || 6.45 || 2.21 || 2.13 || 0.97
|-
|March || 299 || 31 || 9.6 || 5.9 || 328 || 278.9 || 6.67 || 2.28 || 2.00 || 0.88
|-
|April || 235 || 30 || 7.8 || 7.7 || 328 || 280.7 || 6.93 || 2.37 || 1.57 || 0.66
|-
|May || 156 || 31 || 5.0 || 10.5 || 328 || 283.5 || 7.37 || 2.52 || 1.05 || 0.42
|-
|June || 90 || 30 || 3.0 || 12.5 || 328 || 285.5 || 7.72 || 2.64 || 0.60 || 0.23
|-
|July || 45 || 31 || 1.5 || 14.0 || 328 || 287.0 || 8.01 || 2.74 || 0.30 || 0.11
|-
|August || 52 || 31 || 1.7 || 13.8 || 328 || 286.8 || 7.97 || 2.72 || 0.35 || 0.13
|-
|September || 95 || 30 || 3.2 || 12.3 || 328 || 285.3 || 7.69 || 2.63 || 0.64 || 0.24
|-
|October || 183 || 31 || 5.9 || 9.6 || 328 || 282.6 || 7.22 || 2.47 || 1.23 || 0.50
|-
|November || 270 || 30 || 9.0 || 6.5 || 328 || 279.5 || 6.76 || 2.31 || 1.81 || 0.78
|-
|December || 348 || 31 || 11.2 || 4.3 || 328 || 277.3 || 6.47 || 2.21 || 2.33 || 1.05
|-
| '''Totals''' || '''2453''' || || || || || || || || '''11,967''' || '''5,147'''
|-
| || °day|| || || || || || || || kW-hth/year || kW-he/year
|}

== Economics ==

According to the [https://www.moneyadviceservice.org.uk/blog/how-much-is-the-average-gas-and-electricity-bill-per-month Money Advice Service] the average cost to the UK consumer in 2018 of gas was 4.5p per kW-h and of electricity 18.4p per kW-h. 12,000 kW-h of heat would therefore cost £540 from a conventional gas boiler compared to £947 from an ASHP. However, under the Renewable Heat Incentive (RHI) - a government subsidy scheme designed to encourage uptake of renewable technologies - applicants can claim 10.71p per kW-h for heat provided by an ASHP, so an ''income'' of £1,285 per year, for 7 years.

Indicative cost for a complete ASHP system is £5,000-£10,000 see [https://www.cse.org.uk/downloads/file/cost-of-carbon-reduction-in-new-buildings.pdf Centre for Sustainable Energy] Appendix C. Taking the mid-value (£7,500) costs over a 20 year period can be compared:

* Status quo (gas boiler); cost of gas = £10,800
* ASHP (equipment cost + electricity - RHI payments) = £17,445

== Conclusions ==

Air Source Heat Pump (ASHP) technology is a method for converting one unit of electrical energy to two - or more - units of heat energy.

Considering ASHP adoption is a central plank of the UK government's strategy for decarbonising home heating, ASHP application in Britain's cold, wet maritime climate has NOT been well studied

In original work by FLUKE performance test results (by BRE) for an ASHP were modelled with reasonable accuracy (R2 = 0.9268). The derived equation depends only on outside temperature, heat supply temperature and one empirically determined constant.

Using the equation, for the case study conditions described above the ASHP could deliver 12,000 kW-h of heat per year, as space heating and domestic hot water to the house for the expenditure of 5,150 kW-h electrical power. This would represent a COP value of 2.33 - rather less the figure 2.5 to 3 sometimes claimed for the technology

Even allowing for the RHI subsidy payments, ASHP is more expensive than a gas boiler. If the ASHP were supplied free-of-charge ''and'' RHI payments were received, the cost for ASHP is marginally less

Solar Power

2021-08-16T08:35:12Z

Trevor: Update link to RS datasheet

So how much sun do we get in the UK? Using this [http://re.jrc.ec.europa.eu/pvg_tools/en/tools.html tool] <ref>Photovoltaic Geographical Information System</ref> FLUKE has created graphics for the average mid-day intensity of sunlight month-by-month and also the total monthly sunlight received 
<gallery>
Noon.png
Monthly.png
</gallery>
The sunlight intensity around noon averaged 700 W/m² over May 2016 making it the sunniest month that year, although individual days had more intense noon sunshine. Sunlight intensity exceeded 1,000 W per square metre on 36 days; but on no day did it reach 1,100 W. Note that the ''rated'' power of a solar PV panel is based on it receiving 1,000 W/m² of sunlight. So for example a 150Wp Solar PV panel [https://docs.rs-online.com/5c48/0900766b815873b4.pdf RS Components Model 9046156]<ref> RS Pro Datasheet 12V Solar Panels</ref> measuring 1.49m x 0.67m (area of 1 square metre) is rated 150 Wp (p standing for 'peak') with an implied efficiency of 15% (although the brochure states 17%) 
The monthly figures are cumulative and also confirm May to be the sunniest in 2016 with 170 kW-h/m². At 15% efficiency this will have generated 25.5 kW-h/m² of electricity. Multiplying ''this'' figure by 1000 to convert to Watts and dividing by 31 days and by 24 hours the ''average'' power output over the whole month (sunniest of the year), day and night for a "150W" panel is 34W 
Another way to look at the figures: for 4 hours around noon, if the panel received the average 700W of sunlight and produced 15% as electricity (105 W / 0.105 kW) then 4 hours x 31 days x 0.105 W = 13 kW-h/m² which is half the monthly total. '''Half the electricity is produced over a four hour slot (1/6 of a day), the rest over the remaining 5/6.''' To effectively 'smooth' the power over 24 hours you would need to be storing approaching 50% of the energy produced at the peak period 
Compensating for the lack of sunlight at night by using battery storage is therefore technically possible although expensive. However the monthly graphic shows that across seasons there is a '''four-fold''' difference in the energy received from the sun (170 kW-h/m² in May compared to 40 kW-h/m² for December or January). Inclement weather (more dull days in winter) plays a role but the root cause is the geometry of the Earth's orbit about the sun. The 23.5° inclination of the Earth's axis means the North pole point towards the sun in summer and away in winter resulting in the:
* short winter days
* sun low in the sky during winter
we're all familiar with 
==In conclusion==
Solar PV can produce significant amounts of electricity under the most favourable conditions (sunny summer days a few hours either side of noon) but is subject to peaks and troughs (including zero output) across both 24 hours period and across the seasons.

==References==

Air Source Heat Pump

2020-11-17T12:50:43Z

Trevor:

== Basic principle of the Air Source Heat Pump (ASHP) ==

A Heat Pump is a mechanical device for extracting heat from a lower-temperature source and delivering it to a higher-temperature medium. The word 'pump' is used by analogy with that familiar device for raising water from a lower to higher elevation. In either case, mechanical energy is expended to reverse a natural, spontaneous flow of heat from hot to cold - or water from above to below. The operating principal for a heat pump is very similar to a refrigerator or an air conditioning unit; the main distinction being whether heating or cooling is regarded as the 'useful' task; the term heat pump is generally used where '''heating''' is the desired result. From the energy balance:

Heatextracted + Workinput = Heatoutput

it can be seen that output heat is always greater than the input work and the ratio of heat to work necessarily exceeds 1. This is sometimes referred to (inaccurately) as heat pumps having an efficiency greater than 100%; engineers prefer the term 'coefficient of performance' or COP:

COP = Heatoutput / Workinput

Under favourable conditions, an electric-powered ASHP with a HFC working-fluid operating to a reverse Rankine cycle may achieve COP values in the range 2.5 to 3; that is for every 1 kW-h of electricity consumed, 2.5-3 kW-h of heat is produced. The COP is not, however a fixed value. By extending the pump analogy the greater the head of water pumped, the more power is required. Likewise heat pumps perform less efficiently on cold days than mild ones - ''the opposite way to what might be desired''

A typical domestic ASHP, positioned outside the house, is a box-shaped housing containing fans plus the mechanisms to extract heat. Fans draw outdoor air over rows of tubes containing the cold '''working fluid''' which, being even colder than the outside air is 'warmed' by the air (relatively speaking); the air is simultaneously cooled. Through a somewhat complex closed-loop cycle the '''working fluid''' so warmed is first compressed, raising its temperature so it can provide 'useful' heat. It is then expanded, returning to its original cold state and ready to absorb more heat from the air.

Heat pumps of the air-to-air type extract heat from outdoor air to heat indoor air which is circulated for space heating only (like a convection heater). Air-to-water ''extract'' heat in exactly the same way but ''provide'' heat to the house in the form of hot water, which can be used for both space heating via the central heating system and domestic hot water, potentially replacing the gas boiler and the immersion heater

== Heat availability and performance in the UK climate ==
 
[[File:ASHP.png|800px|frameless|left]] 

In calm air conditions, the heat in a volume of air surrounding one individual property can be calculated from its dimensions, the density and specific heat capacity of air and the air's temperature before and after heat is extracted. So for a plot size of 12 metres by 18 to a height of 10 metres (2,160 m³), an initial temperature of 10°C and final temperature 1°C
Density of air @ 1 atmosphere / 10°C = 1.25 kg/m³
Specific heat capacity of air @ 1 atmosphere / 10°C = 1.00 kJ/kg/°C
Mass of air = 1.25 * 2160 = 2,700 kg
Heat content = 2,700 * 1.00 * (10 - 1) = 24,300 kJ (or 6.8 kW-h)
An ASHP operating at a COP of 3 would produce ~ 10.2 kW-h for the house (6.8 kW-h air-sourced heat plus 3.4 kW-h electricity = 10.2 kW-h; 10.2 / 3.4 = 3, the COP) which means the house could be heated at 2kW for 5 hours

10°C is the year-round average temperature (day & night, all seasons) for much of the UK and would be regarded as mild - in winter. ASHPs have been used successfully in Scandinavian climates with air temperatures -10°C or lower '''''- but this is dry air'''''. With the exception of this [http://www.davidstrong.co.uk/web_documents/air_source_heatpumps1.pdf Paper by Professor David Strong] FLUKE has seen little research on the practical application of ASHPs, under conditions which anyone with a passing familiarity with the British 'maritime' climate would recognise
* cold - say 1 to 5°C
* wet - rain, drizzle, mist etc.
under these conditions it is a near-certainty the ASHP will ice-up causing it not only to cease providing heat completely but actually require a heat '''input''' for the defrost cycle

Some real-life consumers' experiences are documented [https://www.carboncommentary.com/blog/2013/03/25/time-to-stop-promoting-air-source-heat-pumps-and-ask-why-they-dont-work-in-the-uk here]

If a large array of ASHPs are adopted as in the illustration resulting in the surrounding air temperature dropping from 10°C to 1°C, according to the 'degree-days' method of estimating heat demand, the rate of heat loss from a house might be expected to increase by a factor of (15.5-1)/(15.5-10) = 2.6 times

A layer of cold air close to the ground - when it occurs naturally - is called a temperature inversion, often associated with a low level layer of mist or fog. The phenomenon is also associated with trapping air pollutants.

=== The marketing view ===

[[File:Eonthumb.png|frameless|left|link=https://www.facebook.com/watch/?v=1644804825584998]]
 

=== The consumers' view ===

Some real-life consumers' experiences are documented [https://www.carboncommentary.com/blog/2013/03/25/time-to-stop-promoting-air-source-heat-pumps-and-ask-why-they-dont-work-in-the-uk at Carbon Commentary]

== A simple model for estimating Air Source Heat Pump performance ==

The Building Research Establishment carried out tests [http://www.e-si.com/downloads/BRE%20Test%20Report%20Mitsi_W90.pdf BRE Test Report] on a Mitsubishi PUHZ-W90VHA air-to-water heat pump and the test results presented in table 3 of that document were analysed against a reverse-Carnot cycle ('''original work by FLUKE'''). The Carnot cycle describes the maximum theoretical efficiency of ''ANY'' thermodynamic process and has the advantage that it can be calculated without any knowledge of the device, but simply from two temperatures expressed in degrees Kelvin: the cold and hot limits of the process, in this case the outside air heat source temperature and the supply temperature to hot water for space heating. So the two equations are

COPACTUAL = Heat output (kW) / Electrical power input (kW) ''… as reported''

COPCARNOT = 1 / ( 1 - TCOLD / THOT ) ''… T in Kelvin''

which when expressed in Celsius and rearranged gives:

COPCARNOT = (tHOT + 273) / (tHOT - tCOLD) ''… t in Celsius''

The average value over 30 tests for COPACTUAL/COPCARNOT is 0.342 so the COP value for the Mitsubishi heat pump can be estimated simply from the outdoor air temperature and the hot water supply temperature from the equation:

COPCALC = 0.342 * (tHOT + 273) / (tHOT - tCOLD) ''… t in Celsius''

Other makes and models of ASHP may be expected to have factors slightly higher or lower than 0.342. To assess the validity of the model, calculated versus actual (test) values of COP are presented below:

[[File:ASHPmodel.png|480px|frameless|left]] 
== Application of the model to a case study ==

Armed with a simple equation to calculate COP and 'degree day' data averaged over 20 years (method discussed elsewhere) , a case study 'typical' house can be modelled based on providing heat for space heating and domestic hot water using the heat pump instead of a gas boiler that would otherwise have a 'medium' gas consumption of 12,000 kW-h per year (OFGEM). The supply temperature is 55°C so that the ASHP can be used as a retrofit to a normal central heating system for economy (compared to say, replacing with brand new low-temperature underfloor heating). The outside temperature is assumed to be constant at the monthly average and heat demand is weighted accordingly

{| class="wikitable"
|-
! Month !! 20-year average degree days !! Days/month !! Mean temperature below 15.5C !! Mean temperature !! THOT K !! TCOLD K !! COPCARNOT !! COPCALC !! Mean monthly heat demand kW !! Mean monthly motor power kW
|-
|A|| B|| C|| D=B/C || E=15.5-D || F || G=E+273 || H || I=0.342*H || J || K=J/I
|-
|January || 362 || 31 || 11.7 || 3.8 || 328 || 276.8 || 6.41 || 2.19 || 2.43 || 1.11
|-
|February || 318 || 28 || 11.4 || 4.1 || 328 || 277.1 || 6.45 || 2.21 || 2.13 || 0.97
|-
|March || 299 || 31 || 9.6 || 5.9 || 328 || 278.9 || 6.67 || 2.28 || 2.00 || 0.88
|-
|April || 235 || 30 || 7.8 || 7.7 || 328 || 280.7 || 6.93 || 2.37 || 1.57 || 0.66
|-
|May || 156 || 31 || 5.0 || 10.5 || 328 || 283.5 || 7.37 || 2.52 || 1.05 || 0.42
|-
|June || 90 || 30 || 3.0 || 12.5 || 328 || 285.5 || 7.72 || 2.64 || 0.60 || 0.23
|-
|July || 45 || 31 || 1.5 || 14.0 || 328 || 287.0 || 8.01 || 2.74 || 0.30 || 0.11
|-
|August || 52 || 31 || 1.7 || 13.8 || 328 || 286.8 || 7.97 || 2.72 || 0.35 || 0.13
|-
|September || 95 || 30 || 3.2 || 12.3 || 328 || 285.3 || 7.69 || 2.63 || 0.64 || 0.24
|-
|October || 183 || 31 || 5.9 || 9.6 || 328 || 282.6 || 7.22 || 2.47 || 1.23 || 0.50
|-
|November || 270 || 30 || 9.0 || 6.5 || 328 || 279.5 || 6.76 || 2.31 || 1.81 || 0.78
|-
|December || 348 || 31 || 11.2 || 4.3 || 328 || 277.3 || 6.47 || 2.21 || 2.33 || 1.05
|-
| '''Totals''' || '''2453''' || || || || || || || || '''11,967''' || '''5,147'''
|-
| || °day|| || || || || || || || kW-hth/year || kW-he/year
|}

== Economics ==

According to the [https://www.moneyadviceservice.org.uk/blog/how-much-is-the-average-gas-and-electricity-bill-per-month Money Advice Service] the average cost to the UK consumer in 2018 of gas was 4.5p per kW-h and of electricity 18.4p per kW-h. 12,000 kW-h of heat would therefore cost £540 from a conventional gas boiler compared to £947 from an ASHP. However, under the Renewable Heat Incentive (RHI) - a government subsidy scheme designed to encourage uptake of renewable technologies - applicants can claim 10.71p per kW-h for heat provided by an ASHP, so an ''income'' of £1,285 per year, for 7 years.

Indicative cost for a complete ASHP system is £5,000-£10,000 see [https://www.cse.org.uk/downloads/file/cost-of-carbon-reduction-in-new-buildings.pdf Centre for Sustainable Energy] Appendix C. Taking the mid-value (£7,500) costs over a 20 year period can be compared:

* Status quo (gas boiler); cost of gas = £10,800
* ASHP (equipment cost + electricity - RHI payments) = £17,445

== Conclusions ==

Air Source Heat Pump (ASHP) technology is a method for converting one unit of electrical energy to two - or more - units of heat energy.

Considering ASHP adoption is a central plank of the UK government's strategy for decarbonising home heating, ASHP application in Britain's cold, wet maritime climate has NOT been well studied

In original work by FLUKE performance test results (by BRE) for an ASHP were modelled with reasonable accuracy (R2 = 0.9268). The derived equation depends only on outside temperature, heat supply temperature and one empirically determined constant.

Using the equation, for the case study conditions described above the ASHP could deliver 12,000 kW-h of heat per year, as space heating and domestic hot water to the house for the expenditure of 5,150 kW-h electrical power. This would represent a COP value of 2.33 - rather less the figure 2.5 to 3 sometimes claimed for the technology

Even allowing for the RHI subsidy payments, ASHP is more expensive than a gas boiler. If the ASHP were supplied free-of-charge ''and'' RHI payments were received, the cost for ASHP is marginally less