UWE_BEng Disseration_An Investigation into Low Carbon DH in Low-density Urban Areas_2013-2014

A N I NVESTIGATION

INTO

L OW C ARBON D ISTRICT H EATING

IN

L O W - DENSITY U RBAN A REAS Are biomass-fuelled district heating systems a viable solution for low carbon heating in new, low-density residential developments?

Michaela Mallia 11006373

An Investigation into Low Carbon District Heating in Low-density Areas

The University of the West of England BEng (Hons) Architecture and Environmental Engineering April 2013

Main Body Word Count: 10,966 Total Word Count: 16,057

This study was completed as part of the BEng (Hons) Architecture and Environmental Engineering Programme at the University of the West of England. The work is my own.

Where the work of others is used or drawn on, it is attributed to the relevant source.

Michaela Mallia

This dissertation is protected by copyright. Do not copy any part of it for any purpose other than personal academic study without the permission of the author.

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An Investigation into Low Carbon District Heating in Low-density Areas

A C KN O W L E D G E M E N T S I would like to thank all who have supported me throughout this dissertation, with particular acknowledgement to the following who have continuously helped me throughout my research and writing.

Firstly to my dissertation tutor Patrick O’Flynn for his support, guidance and endless patience with my indecisiveness.

To Martin Longhurst, who generously gave up his time to pass on his knowledge and aided in refining my research.

To Faye Restall, who kindly assisted me with proof reading in spite of her very busy schedule.

To Jim Agnew for always listening, constantly motivating me to do my best and giving me perspective.

Finally, to my family who have always been a voice of encouragement and reassurance in challenging times. I am entirely indebted to your love and support.

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An Investigation into Low Carbon District Heating in Low-density Areas

ABSTRACT This dissertation has been stimulated by the potential DH has in de-carbonising the UK’s heat supply. The development of environmentally sustainable heat networks considers the use of low carbon fuels and efficient heat distribution. The energy efficiency of DH systems is dependent on the thermal demand density of the supplied urban area. It is, therefore, imperative that their development is limited to areas that have a high enough heat demand density.

This relationship has been explored to determine the energy efficiency of a wood pellet LTDH system and MTDH system supplying a new, residential development with a low heat demand density. An assessment of each system’s CO2 emissions has also been undertaken. The study is comparative by nature; the results have been compared to the seasonal efficiency and carbon performance of domestic condensing boilers, connected to the central gas supply.

A conceptual mathematical model has been developed to firstly quantitatively asses the annual heat demand of the chosen dwellings. This data was then used to calculate the energy and carbon efficiencies of the proposed LTDH and MTDH networks, along with the carbon emissions of the existing heating systems.

The research showed that the MTDH system has the lower energy efficiency of the two DH systems, and that the domestic condensing boilers perform at significantly higher energy efficiencies. Both DH networks largely reduce carbon emission compared to the condensing boilers, with LTDH having the smallest carbon footprint. The results conclude that MTDH is not a viable low-carbon solution in low-density areas as energy efficiency performance is too low. Further research is required to determine whether LTDH is a viable low carbon heating solution.

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An Investigation into Low Carbon District Heating in Low-density Areas

1

C ONTENT S

1

2

Acknowledgements

iii

Abstract

iv

Contents 1.1 List of Figures

ix

1.2 List of Tables

x

1.3 List of Abbreviations

xi

1.4 List of Nomenclature

xii

Introduction 2.1 A Context for the Research

1 1

2.1.1 Heating and Global Warming

1

2.1.2 District Heating and Urbanisation

2

2.1.3 Contemporary Architecture

2

2.2 Hypothesis and the Central Research Question 2.2.1 Research Aims

3

v

Literature Review

2 3

5

3.1 District Heating in the UK

5

3.1.1 Beyond Modernism

5

3.1.2 The Argument for District Heating

5

3.1.3 Limitations of District Heating

6

3.1.4 District Heating in Bristol

7

3.2 Technology Overview

8

3.2.1 Introduction

8

3.2.2 Thermal Production

9

3.2.3 Thermal Distribution

11

3.2.4 Heat Emitters

13

3.2.5 Hoathly Hill Community Case Study

14

3.3 Energy Losses

15

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An Investigation into Low Carbon District Heating in Low-density Areas

4

5

3.3.1 Introduction

15

3.3.2 Boiler Seasonal Efficiency

15

3.3.3 Accumulator Heat Loss

16

3.3.4 Primary Network Heat Loss

16

3.3.5 Parasitic Losses

17

3.4 The Urban Environment

18

3.4.1 Introduction

18

3.4.2 Urban Density

18

3.4.3 Heat Demand Density

19

3.5 Thermal Principles in Architecture

20

3.5.1 Introduction

20

3.5.2 The Coefficient of Building Heat Loss

21

3.5.3 Solar Gains

22

A Case Study

23

4.1 Introduction

23

4.2 Establishing the Area’s Thermal Demand Density

23

4.3 Network Overview

24

The Research Model

26

5.1 Introduction

26

5.2 Domestic Hot Water

26

5.3 Space Heating

27

5.3.1 Volume

27

5.3.2 U-values

27

5.3.3 Thermal Bridging

28

5.3.4 Infiltration

29

5.3.5 The Annual Space Heating Demand

29

5.4 District Heating: Energy Efficiency

29

5.4.1 Thermal Production

30

5.4.2 Thermal Distribution

30

5.4.3 Overall System Efficiency

31

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An Investigation into Low Carbon District Heating in Low-density Areas

5.5 Domestic Condensing Boilers: Energy Efficiency

31

5.6 District Heating: Carbon Emissions

31

5.6.1 Fuel Lifecycle Emissions

32

5.6.2 Pumping Emissions

32

5.7 Domestic Condensing Boilers: Carbon Emissions

6

Discussion and Findings

34

6.1 Introduction

34

6.2 Annual Domestic Hot Water Demand

34

6.3 Annual Space Heating Demand

35

6.4 District Heating: Energy Efficiency

36

6.4.1 Thermal Production

36

6.4.2 Thermal Distribution

37

6.4.3 Overall System Efficiency

37

6.5 Carbon Emissions

40

6.6 Research Limitations and Areas of Improvement

41

6.6.1 Domestic Hot Water Demand Modelling

41

6.6.2 Space Heating Demand Modelling

41

6.6.3 Carbon Efficiency Modelling

41

6.7 Model Applicability

7

33

Conclusion

42

44

7.1 An Overview

44

7.2 Viability of Integration

45

7.3 Further Research

45

7.3.1 Thermal Demand Densities

45

7.3.2 System Improvements

46

7.3.3 Climate Change

46

8

References

47

9

Bibliography

54

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An Investigation into Low Carbon District Heating in Low-density Areas

Appendix A

56

Appendix B

58

Appendix C

59

Appendix D

62

Appendix E

69

Appendix F

72

Appendix G

74

Appendix H

75

Appendix I

76

Appendix J

102

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An Investigation into Low Carbon District Heating in Low-density Areas

1.1

LIST

OF

F I GU R E S

Figure 2.1

Direct CO2 emissions in 2006 (MtCO2)

1

Figure 3.1

Heating and cooling from renewable resources

6

Figure 3.2

District heating system schematic

8

Figure 3.3

Typical heating requirements supplied by wood fired boilers

10

Figure 3.4

Biomass plant with heat store and fossil fuel stand-by/back-up

11

Figure 3.5

District heating pipes

12

Figure 3.6

Overview of district heating system

14

Figure 3.7

Flow and return pipes join to the interface unit

15

Figure 3.8

Heat mains losses from Danish DH statistics

16

Figure 3.9

Electricity used in Danish DH schemes

17

Figure 3.10

Housing types and heat density

19

Figure 4.1

National Heat Map

24

Figure 4.2

Overlay of Heat Map and Digimap of chosen dwellings

24

Figure 4.3

Overview of district heating system

25

Figure 6.1

Monthly variation in hot water use

34

Figure 6.2

Total annual heating profile in MWh

35

Figure 6.3

Comparison of results and SAP

36

Figure 6.4

Seasonal efficiencies

36

Figure 6.5

Overall system energy efficiency

38

Figure 6.6

LTDH system Sankey diagram

39

Figure 6.7

MTDH system Sankey diagram

39

Figure 6.8

Annual carbon emissions in kgCO2 from relative fuels

40

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An Investigation into Low Carbon District Heating in Low-density Areas

1.2

LIST

OF

T ABL E S

Table 3.1

Carbon savings of different heat technologies

9

Table 3.2

Heat loss coefficients of an 80mm (nominal) distribution pipe

17

Table 3.3

Seasonal solar gain through windows

22

Table 5.1

Default U-Values (W/m2K)

28

Table 5.2

Mean monthly and annual heating degree-day totals (1976-1995)

29

Table 5.3

Typical fan and motor peak-load efficiencies

33

Table 6.1

Efficiency breakdown

39

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An Investigation into Low Carbon District Heating in Low-density Areas

1.3

LIST

OF

A B BR E VI AT I O N S

ACH

Air changes per hour

CHP

Combined heat and power

CIBSE

Chartered Institution of Building Services Engineers

CO2

Carbon dioxide

DCLG

Department for Communities and Local Government

DECC

Department of Energy and Climate Change

DH

District heating

DHW

Domestic hot water

GCV

Gross calorific value

GHG

Greenhouse gases

HDD

Heating degree days

LF

Load factor

LTDH

Low temperature district heating

MTDH

Medium temperature district heating

SAP

Standard Assessment Procedure

SEDBUK

Seasonal Efficiency of Domestic Boilers in the UK

TPL

Target pressure loss

UK

United Kingdom

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An Investigation into Low Carbon District Heating in Low-density Areas

1.4

LIST

OF

N O ME N C L AT U R E

A

Area

AS

Total surface area

ATF

Total floor area

AW

Area of windows

AWE

Area of east windows

AWN

Area of north windows

AWS

Area of south windows

AWT

Area of total windows

AWW

Area of west windows

c

Specific heat capacity

Cf

Fabric heat loss coefficient

Ctb

Thermal bridging heat loss coefficient

Cv

Ventilation heat loss coefficient

h

Height

Iᾊ

Average solar flux

L

Length

n

Air changes per hour

N

Number of occupants

Nannual

Number of days in the year

P

Air permeability

Pelectric

Electrical power

QA-annual

Annual accumulator heat loss

QDHW-annual

Annual DHW energy demand

Qe

Electrical energy

QH-annual

Annual space heating energy demand

QIN

Heat energy delivered by fuel

QLTDH-annual

Annual LTDH primary network heat loss

QMTDH-annual

Annual MTDH primary network heat loss

Qsys

Useful heat energy delivered to system

Qdwellings

Useful heat energy delivered to dwellings

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An Investigation into Low Carbon District Heating in Low-density Areas

T1

Supply temperature

T2

Return temperature

Tg

Ground temperature

U11

Supply pipe heat loss coefficient

U12

Heat flow from supply pipe to return pipe

v

Velocity

V

Volume

Vbuilding

Volume of building

Vday

Volume per day

y

Additional heat loss rate

τglass

Transmittance coefficient

ƞ

Efficiency

ƞBn-se

Boiler seasonal efficiency

ƞLTDH-D

Total LTDH distribution network efficiency

ƞLTDH-tot

Overall LTDH efficiency

ƞm

Motor efficiency

ƞMTDH-t

Total MTDH distribution network efficiency

ƞMTDH-tot

Overall MTDH efficiency

ƞp

Pump efficiency

ƞs-se

Multiple boiler seasonal efficiency

ρ

Density

λ

Coefficient of friction

θannaul

Annual temperature difference

ø

Diameter

∆P

Pressure drop

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

2

I NTRO DUCTION 2.1

A CONTEXT 2.1.1

FOR THE

H E AT I N G

AN D

R E S E AR C H G L O B AL W AR MI N G

Human society is fundamentally dependent on heat. In 2011, 906 TWh of natural gas was consumed in the UK, 52% of which was used to provide heat for buildings and industry (DECC, 2013, p. 1). Heating is responsible for approximately 33% of the country’s GHG emissions (DECC, 2013, p. 1); the former’s demand is dominated by the residential sector.

10.78 11.2

Residential Commercial Public 81.95

Figure 2.1 Direct CO2 emissions in 2006 (MtCO2) Source DECC, 2010 (1), p. 94

The UK’s ambition to cute 80% of its GHG emissions by 2050 is challenged by the country’s “historic failure to get to grips with one enormous part of the energy jigsaw; the supply of low carbon heat” (DECC, 2013, p. 1). In order to balance the energy budget (MacKay, 2009) and meet long-term emission reduction targets, the country must reform the way it generates, distributes and consumes heat in the built environment. Further to this, “the most recent economic modelling on the future scenarios for heat supply suggests a much more diversified range of heat technologies in the future” (DECC, 2013, p. 7).

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

2.1.2 D I S T R I C T H E AT I N G AN D U R B AN I S AT I O N “District heating is well known in other countries for providing [...] low-carbon energy to local populations” (Finney et al., 2012, p. 183)

The development of DH networks in urban areas is increasingly receiving attention in the UK; cities such as Nottingham and Sheffield already have large DH systems to provide warmth to homes (DECC, 2012, p. 1). This is predominantly because “it can be less costly and more [energy] efficient to connect buildings to a low carbon source through heat networks than to install individual building-level systems” (DECC, 2012, p. 19), in the right conditions.

Half of the globe’s population reside in urban areas and this phenomenon is predicted to grow (Keirstead and Shah, 2013, p. 3). Predictions suggest that urban areas will be directly responsible for 73% of energy use by 2030 (UN 2011, IEA 2008b), largely impacting the patterns of energy use within the next few decades. This stimulates a symbiotic relationship with the development of DH systems, as their efficiency is proportional to heat demand growth.

2.1.3 C O N T E MP O R AR Y A R C H I T E C T U R E Architectural form and fabric determine the thermal state of a building. As energy performance requirements for new constructions become increasingly tight, the amount of energy required to heat new homes will continue to fall (Jangsten et al., 2011, p. 3); as such, so will the heat demand of new, residential developments in urban areas. This questions the appropriateness of integrating DH systems into newly built, low-density areas.

2.2

H YP O T H E S I S

AND

C E N T R AL R E S E AR C H Q U E S T I O N

The goal of this dissertation is to determine if biomass-fuelled DH is an environmentally sustainable method of supplying low carbon heat in new, low-density residential areas.

The term ‘environmentally sustainable technology’ shall signify a heating system that performs at a high energy efficiency while simultaneously emitting low CO 2 emissions. The success of the systems shall be evaluated by developing a conceptual, mathematical

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

model. Its use is aimed at architectural designers, enabling them with a tool to investigate the viability of integrating low carbon LTDH and MTDH networks into new housing schemes at the early stages of development.

The model quantitatively assesses three areas of investigation. Firstly, the total annual heat demand of a chosen urban area will be determined. Secondly, the energy efficiency of the proposed LTDH and MTDH systems, which will satisfy the area’s DHW and space heating demands, will be calculated. Lastly, model application will determine the systems’ carbon emissions. The results will enable a comparison of the systems’ performances to domestic gas-fuelled condensing boilers; the traditional heating practise in the UK.

The systems will be considered successful if significant carbon savings can be made while maintaining high energy efficiency. Therefore, the model’s results will indicate whether DH is a clearly viable option for low carbon heating, whether it is not or if further research will be required to effectively determine this. The following research question endeavours to encapsulate the scope of this dissertation:

Are biomass-fuelled district heating systems a viable solution for low carbon heating in new, low-density residential developments?

2.2.1

R E S E AR C H A I MS

The following research aims have been set out to effectively address the central research question:

Aim One: Establish a residential area with an appropriate thermal demand density for the investigation.

The literature review shall enable an understanding of the relationship between DH network energy losses and thermal demand densities. The ‘benchmark’ thermal demand density, which signifies whether areas can be feasibly supplied by DH, shall be used as a basis for determining an appropriate area to investigate.

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Aim Two: Develop an understanding of architectural thermal principles to determine the annual heat demand of the investigated area.

This aim shall be addressed in the first section of the research model, whereby the combined yearly DHW and space heating demands of the chosen dwellings will be evaluated. Insight into the nature of static heat losses and gains in a building shall be gained from the literature review.

Aim Three: Evaluate the energy and carbon efficiencies of a biomass LTDH system, a biomass MTDH system and the existing heating systems.

This aim will be achieved by carrying out the second aim, as it will inform the proposed DH setups. The literature review shall explore the thermal production efficiency of wood pellet boilers and the key areas in distribution networks that suffer heat losses. The results will be compared to the seasonal efficiency of condensing boilers. System factors contributing to annual CO2 emissions in DH networks shall also be investigated in the literature review.

Aim Four: Compare the performance of both DH systems with the existing heating technology to determine whether the former is an environmentally sustainable solution in low-density residential areas.

The results from aim three shall allow for a comparative performance assessment of the wood pellet DH systems and the domestic condensing boilers. DH will be classed as an environmentally sustainable solution if it displays relatively high energy efficiency and effectively reduces CO2 emissions.

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

3

L ITERATURE R EVI EW 3.1

D I S T R I C T H E AT I N G 3.1.1

IN THE

UK

B E YO N D M O DE R N I S M

Although well established in other countries, particularly in continental Europe, DH currently provides the UK with less than 2% of its heat demand (Gov.uk, 2013 (1)).

However, it was in fact an increasingly popular heating method during the Modernist period; its use peaked in the ‘council house building boom’ from the 1950s to the 1970s (Jangsten et al., 2011, p. 3).

However, due to failures in meeting demands and

unsatisfactory performance, many of the systems were decommissioned. Jangsten explains that this was the result of poor installation and maintenance, often causing pipe corrosion and water leaks (Jangsten et al., 2011, p. 3).

Today, large scale DH systems can be found in a handful of cities, such as Southampton, Sheffield, Birmingham and Nottingham. The Olympic Park DH network in London has been classed as a “recent successful heat network” (Gov.uk, 2013 (2)), predicted to annually reduce 11,000 tonnes of carbon emissions by 2015. Current legislative policies, such as the Renewable Heat Incentive (Finney and Sharifi et al., 2012, p. 175) and the government’s “£6 million grant funding programme” (Gov.uk, 2013 (2)), are promoting the development and expansion of heat networks.

3.1.2 T H E A R G U M E N T F O R D I S T R I C T H E A T I N G “It is now widely recognised in the UK that the underlying rationale of DH is sound, and that it can be a key component in delivering environmental objectives” (Jangsten et al., 2011, p.

3).

A key advantage of DH is its ability to supply low carbon heat at high efficiencies if used in the right conditions. DH plants are flexibile with regard to fuel source and are, therefore, easily adaptable to fuel change depending on availability (Jangsten et al., 2011, p. 3). The need to introduce low carbon heating in the UK can be recognised in the following graph:

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure 3.1 Heating and cooling from renewable resources Source DECC, 2013, p. 5

DECC have established that UK conditions are favourable for DH to supply 14% of the county’s heat demand (Routledge and Williams, 2012, p. 11). Therefore, it is imperative to realise that its integration will only be successful if it is controlled to this 14%. As such, DH’s performance peaks in high-density urban areas. Even though the electrical grid is predicted to decarbonise, the inherently inefficient nature of electricity may render DH to be a favourable low carbon heat supply in such areas.

3.1.3 L I MI T A T I O N S O F D I S T R I C T H E A T I N G In order to successfully implement DH, practical barriers challenging its development must be considered. The primary obstacle to the uptake of this technology is the high capital investment needed to set up these major infrastructures (Jangsten et al., 2011, p. 3).

As with any technology, DH’s success depends on financial feasibility; this stresses the importance of developing DH in urban areas which capacitate high efficiency performance, and thus, a return on investment.

A lack of skills and knowledge with regard to the heating’s technology in the UK follows from the previous argument (BRE, University of Edinburgh and the Centre for Sustainable Energy, 2013, p. 4). The need for “in-house staff resources” (BRE, University of Edinburgh and the Centre for Sustainable Energy, 2013, p. 4) has been highlighted as a barrier to the effective expansion of these systems. Lacking the required skill set to efficiently design

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

and maintain networks will result in large heat losses, subsequently affecting its financial feasibility.

Utilising biomass as a fuel source introduces further limitations; the fuel’s uptake may be hindered by “issues associated with air quality, delivery, technology risk and fuel sourcing” (BRE, University of Edinburgh and the Centre for Sustainable Energy, 2013, p. 38). The large area required for fuel storage and delivery makes biomass-fuelled district heating difficult to implement in dense area. However, the dissertation’s interest in low-density urban areas lessens the significance of this issue.

Finally, the social implications of DH should be considered. A dominant social concern is consumer unease towards inconsistent pricing of heat. Ineffective use of heat metering, or the lack of its use, can lead to over or underpaid heating bills. It is therefore beneficial to integrate heat metering with the hydraulic interface unit at the consumer end of the technology (BRE, University of Edinburgh and the Centre for Sustainable Energy, 2013, p.

40).

3.1.4 D I S T R I C T H E AT I N G I N B R I S T O L Bristol is the sixth largest city in England with a population of over 430,000, significantly contributing to the country’s heat demand and GHG emissions (Carbon Trust, n.d.).

Named the Green Capitol for 2015 and described as a “laboratory for change” (Ferguson, et. al, 2013), George Ferguson is committed to reforming Bristol into a low carbon city and reduce its carbon footprint by 40% by 2020 (Carbon Trust, n.d.). In order to meet these targets, the city council has been working with the Carbon Trust to develop heat networks around the city, with the ambition of reducing carbon emissions, cutting energy costs and providing a secure energy supply by eliminating the possibility of fuel shortages and price volatility (Carbon Trust, n.d.). This has encouraged this dissertation to investigate whether it is viable to include Bristol’s low-density, residential areas in this scheme.

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

3.2

T E C H N O L O G Y O VE R VI E W 3.2.1

INTRODUCTION

The main concept behind DH is that a central energy centre distributes heat for DHW and/or space-heating to multiple buildings via a distribution network (Jangsten et al., 2011, p. 2). The entire heat system can be seen to consist of three phases:  Thermal production and containment in the energy centre.  Thermal distribution in a primary pipe network which connects the energy centre to the end consumers.  The buildings’ heat exchanger interfaces, secondary distribution circuit and heat emitters (Vallios et al., 2008, p. 661).

The dissertation shall consider the thermal production and distribution stage of DH, as these are the stages that witness the majority of heat loss and are predominately responsible for CO2 emissions. These two phases comprise of the fuels that the urban environments utilise, the technologies that convert the fuels into usable energy and finally the network that supplies it (Keirstead and Shah, 2013).

The following diagram illustrates a general system setup, whereby heat is transported to consumers via large supply pipes, and a cooler return feed circulates the heating medium back to the energy centre (channel6ada, 2010):

Figure 3.2 District heating system schematic

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

3.2.2 T H E R M AL P R O DU C T I O N 3.2.2.1

LOW CARBON FUELS

For DH to be successful in the current environmental climate, the choice of low-carbon fuel should depend on resource availability in the area. Sustainable fuels may be set into three categories:  Electricity-based using heat pumps or, if the grid decarbonises, using direct electric heating (Woods and Zdaniuk, 2011, p. 13) or nuclear power.  CHP or waste heat extraction from industrial plants that would otherwise dump excess heat.  Direct renewable heat generation using bioenergy, deep geothermal heat, fuel cells or solar thermal heat (Jangsten et al., 2011, p. 3).

This dissertation shall focus on wood pellet-fuelled district heating. Though a number of biomass fuels exist, woodchip and wood pellet boilers are most commonly used by DH (Energy Savings Trust, 2008, p. 19) as they are characterised as quick response boilers. The following table illustrates that using a biomass boiler results in larger carbon savings in comparison with biomass CHP and ground-source heat pumps:

Renewable Heating Technology

Lifetime (yrs)

Carbon Savings

Household Costs

Annual (kg of CO2)

Lifetime (t of CO2)

Annual Energy Cost Savings (£)

Installation Cost (£)

Wood chip CHP

30

3438.12

96.5-107.1

443.17-491.80

9463-9579

Community groundsource heat pump

40

545.61

20.4-22.7

7.87-8.74

4463-4486

Community wood chip boiler

30

3791.73

106.4-118.1

142.90-158.58

418-430

Table 3.1 Carbon savings of different heat technologies Source reproduced from Finney et al., 2012, p. 177)

3.2.2.2

B O I L E R O P E R A T IO N

DH systems can cope with the variable nature of heat demand profiles efficiently. This is because they tend to operate using multiple boilers rather a single large boiler (Harvey,

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

2006, pp. 577-578); the amount of boilers that operate can be controlled to fluctuate with the heat demand. This is advantageous because it minimises part loading and encourages higher seasonal efficiencies (Harvey, 2006, pp. 577-578).

Further to this, the Energy Saving Trust state that “biomass boilers usually work with some top-up boiler to provide winter peak demands� (Energy Saving Trust, 2008, p. 20). Top-up boilers generally operate off natural gas. According to the Energy Saving Trust, typical biomass boiler sizing ranges between 50-70% of the peak heat demand and can supply around 70-80% of the total heat requirement (Energy Saving Trust, 2008, p. 20).

Figure 3.3 Typical heating requirements supplied by wood fired boilers Source Energy Savings Trust, 2008, p. 20

3.2.2.3

THERMAL STORAGE

The variable nature of heat demand profiles could threaten production of surplus of heat.

This is combated by the use of large well-insulated water tanks, or accumulators, which allow the thermal production facility to produce heat periodically (channel6ada, 2010).

Thus, fluctuating demand profiles can be smoothed out using an accumulator to manage the heat until it is needed (Energy Saving Trust, n.d.). If accumulators are used to support the biomass boilers, higher levels of biomass penetration would be achievable (Energy Saving Trust, 2008, p. 20) as the primary boilers would not be as dependent on the backup boiler when the energy demands increase. A well insulated accumulator can store between 500 to 5000 litres of water for multiple days (Energy Saving Trust, n.d.).

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure 3.4 Biomass plant with heat store and fossil fuel stand-by/back-up Source Carbon Trust, 2009, 47

3.2.3 T H E R M AL D I S T R I BU T I O N 3.2.3.1

WATER AND STEAM SYSTEMS

DH can supply heat via hot water or steam. Harvey (2006, p. 576) classes hydronic systems as “high-temperature (>150°C), medium-temperature (90-150°C) [or] low-temperature (<90°C)”, all of which having a feed pressure ranging from 8-16bar and a return pressure of 5bar. On the other hand, “steam systems have been classified as high pressure (>8.6 bar), medium pressure (2.0-8.6 bar) and low pressure (<2.0 bar)” (Harvey, 2006, p. 576).

While older systems, such as the network in New York City, mostly use steam, contemporary networks tend to be hydronic (Harvey, 2006, p. 576). Even though “steam has a much higher thermal energy density than hot water” (Harvey, 2006, p. 576), hydronic systems pose efficiency advantages over the former. The main advantage is the possibility of using a feed temperature as low as 60°C, dramatically reducing distribution losses. As a result, a hydronic system shall be considered in this dissertation.

3.2.3.2

PRIMARY NETWORK

A primary network consists of a supply pipe, which transports hot water to the consumers, and a return pipe which redelivers the cooler water to the thermal production facility. The majority of energy losses in DH systems occur due to the conductive heat lost throughout the primary network. As a result, it is considered the most crucial part of DH design (Jangsten et al., 2011, p. 7); the large scale of primary networks means that “even the smallest problem with pipework design can have wide ramifications” (Blackwell, 2013, p.

33), therefore, it is imperative to design pipework efficiently.

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

The literature reviewed has revealed three main principles to achieve a high performance pipeline. Firstly, contemporary systems emphasis the use of high performance, preinsulated pipes. Previous DH schemes in the UK traditionally consisted of single pipe systems (Jangsten et al., 2011, p. 7). However, Jangsten suggests that the use of preinsulated twin pipes in new DH networks “can reduce heat distribution losses by 20-30%” (Jangsten et al., 2011, p. 7). This is supported by Dalla Rosa et al., who conclude that “twin pipes for DH distribution and service piping should be preferred in urban areas” (Dalla Rosa et al., 2012, p. 973), especially in low heat demand density areas (Zinko et al., 2008).

The following image illustrates a pair of single pipes (A), horizontal and vertical twin pipes (B and C) and an egg-shaped twin pipe (D):

Figure 3.5 District heating pipes Source Kristjansson, H. and Bøhm, B., 2006, p. 3

Secondly, reducing the flow and return temperatures and, therefore, the temperature difference between the pipes and the surroundings, results in less heat transfer from the water to the external environment (Harvey, 2006, p. 576). The loss of heat to the surroundings, generally the ground distribution pipes are embedded in, is called the distribution loss. Through computational modelling, Dalla Rosa et al. (2012, 960) concluded that a “MTDH had better energy delivery performance than high-temperature district heating, decreasing heat loss by approximately 40%”. LTDH achieves even lower losses (Dalla Rosa et al., 2012, p. 960). A return temperature as low as 40°C is achievable for new build schemes (Woods and Zdaniuk, 2011, p. 8).

Lastly, using smaller pipe diameters reduces the amount of surface for heat to transfer through, but, it also reduces the system flow rate; this would “have an impact on pressure loss in DH and consequently on the electrical energy consumption of pumps” (Pirouti, et al., 2013, p. 150). However, an increased temperature difference between flow and return

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

would allow for this reduction in flow velocity and still deliver the required amount of heat (Jangsten et al., 2011, p. 9).

3.2.3.3

PUMPING

DH networks require electrical energy input to pump water through the primary network, referred to as parasitic losses. In order to determine the amount of pumping power that is required, the TPL per unit length needs to be considered, whereby a larger pressure drop demands more energy. In practise, “searching algorithms” (Pirouti, et al., 2013, p. 150) through computational modelling are used to balance the smallest possible pipe diameter with the maximum allowable TPL that is appropriate to minimise heat loss. The electrical input required for pumping may also be reduced by minimising the number of bends in the pipe line and specifying a pipe material with minimal friction (Harvey, 2006, pp. 304305).

It is important to note the relationship between pressure, temperature and velocity flow rates. Using warmer feed temperatures will increase distribution losses but lower pumping requirements, as a lower flow rate will be needed for the required rate of heat delivery (Harvey, 2006, p. 308). Therefore, using LTDH would induce a lower flow rate and intensify pumping demands (Jangsten et al., 2011, p. 9) but reduce heat losses. In their study, Pirouti et al. (2013, p. 158) deduce that energy efficiency is improved by “[reducing the] system flow rate by increasing temperature difference between supply and return pipes”.

3.2.4 H E AT E MI T T E R S Even though the secondary heat distribution system used in dwellings will not appear in the research, mention shall be given to the type of heat emitter used in accordance with the temperature of the heat supply. In the case of LTDH, the heat emitter must be able to effectively deliver heat at lower feed temperatures; underfloor heating systems should be considered in such a scenario as they can operate with feed temperatures as low as 40°C. Alternatively, larger radiators would be appropriate with LTDH than would be used with MTDH (Jangsten et al., 2011, p. 9).

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

3.2.5 H O AT H L Y H I L L C O M MU N I T Y C AS E S T U D Y The Hoathly Hill Community generates its entire heat demand using a wood fired district heating system. In 2006, a “low maintenance woodchip boiler system” (Chapman, 2007, p.

3) was installed in the community, supplying 27 building units (Chapman, 2007, p. 3). The report states that “there have been some difficulties a few which would have not been expected, but [...] usually a solution has been found” (Chapman, 2007, p. 6). These obstacles have not been described in the report.

Figure 3.6 Overview of district heating system Source Chapman, 2007, p. 5

The total heat load of the site was calculated at just over 750 MWh per year (Chapman, 2007, p. 6); the site utilises a 300kW Binder boiler, “with high efficiency flow and return pipes” (Chapman, 2007, p. 7). The report states that the primary network has a high thermal performance and loses 0.01°C every 100m (Chapman, 2007, p. 7). The twin pipe insulation is bonded to the plastic media pipes to prevent water penetrating from the ground into the feed and return supplies. This measure reduces the chances of additional heat losses or leakages. Lastly, the system utilises two 4,000 litre accumulator tanks, sized to supply the peak load demand as the woodchip boiler is designed to deliver 70% of the peak heat load (Chapman, 2007, p. 6).

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure 3.7 Flow and return pipes join to the interface unit Source Chapman, 2007, p. 5

3.3

ENERGY LOSSES 3.3.1

INTRODUCTION

A large portion of this dissertation’s research agenda is centred on the energy losses that occur throughout a DH system. The technology’s overall performance depends on the efficiency of heat production and distribution in relation to the buildings’ heat demands (Verda et al., 2012, p. 40). This section shall discuss the established efficiencies of woodchip/wood pellet boilers and how heat losses occur in accumulators and distribution networks.

3.3.2 B O I L E R S E AS O N AL E F F I C I E N C Y The seasonal efficiency of a boiler is its average energy efficiency throughout the heating season, that is, its average annual efficiency. It is worth noting that seasonal efficiencies based on GCVs should be used, as this takes the heat lost in water vapour into consideration. The benchmark value for energy efficient biomass boilers is 75% (DCLG, 2011, p. 31). Kirk argues that it is possible to assume a seasonal efficiency of 85% for “a newly installed well running system” (Kirk, 2011, 56). This is supported by Arca53 (2014), which suggests that modern wood pellet boilers can achieve efficiencies between 80-90%,

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

and Olesen (n.d.) who specifies a seasonal efficiency of 80.4% for a larger 22.4 kW wood pellet boiler.

3.3.3 A C C U MU L AT O R H E AT L O S S Even though accumulators are well insulated, limited amounts of heat still travel from the water to the surrounding environment. According to The Government's Standard Assessment Procedure for Energy Rating of Dwellings, it may be assumed that a 110 litre accumulator will be used in DH networks and account for a loss of 0.0152kWh/litre/day (DECC, 2010, The Government's Standard Assessment Procedure for Energy Rating of Dwellings, p. 20).

3.3.4 P R I M AR Y N E T WO R K H E AT L O S S Due to the small number of heating networks in the UK, extensive data from the Danish District Heating Association can be seen in figure 3.8. The latter displays an analysis of the annual heat losses that occur in established primary networks of schemes providing 100GWh p.a. (Woods and Zdaniuk, 2011, p. 10). The graph depicts a wide range of results with an average of heat loss of 17% (Woods and Zdaniuk, 2011, p. 10). This is attributed to the â&#x20AC;&#x153;range of heat densities supplied and the variation in age of the networkâ&#x20AC;?, whereby larger systems may service highly dense areas in cities, resulting in a higher performance.

Figure 3.8 Heat mains losses from Danish DH statistics Source Woods and Zdaniuk, 2011, p. 10

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Danfoss, a major manufacturer of distribution pipes, published a calculation procedure to determine the heat loss from circular twin pipes. Kristjansson and Bøhm (2006, p. 2), provide the following equation, used for a “ø80/80/250 circular twin pipe”:

Table 3.2 Heat loss coefficients of an 80mm (nominal) distribution pipe Source Kristjansson and Bøhm, 2006, p. 5

3.3.5 P AR AS I T I C L O S S E S The electrical input required for pumping water along the primary network represents the majority of the parasitic losses in a DH system (Woods and Zdaniuk, 2011, p. 10). Wood and Zdaniuk (2011, p. 11) also analysed the annual electricity used by a number of Danish DH systems, as seen in figure 3.9. The results show some scattering, however, a trend appears where smaller systems require less electricity.

Figure 3.9 Electricity used in Danish DH schemes Source Woods and Zdaniuk, 2011, p. 11

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

As mentioned in section 3.2.3.3, the pumping energy needed is primarily determined by the TPL (∆P) in the pipes. The D’arcy-Weisbach equation makes it possible to mathematically determine “the pressure drop along a circular pipe for fully turbulent flow” (Harvey, 2006, p. 304):

However, Pirouti et al. (2013, p. 150) suggest that “as a rule of thumb many DH networks in Denmark and in other European countries have been designed using TPL of 100Pa/m”.

Once the pressure drop has been determined, it is possible to determine the power required to maintain water motion using the following equation (Harvey, 2006, p. 304):

ƞ ƞ

3.4

ƞ ƞ

T H E U R B AN E N VI R O N ME N T 3.4.1 I N T R O D U C T I O N

An effective urban heating system is designed in response to the heating requirements of the urban form and density, resident energy use patterns and the area’s climate. As previously mentioned, the amount of heat lost in the primary network of a DH system has a direct relationship to the urban density of the area being supplied. This section of the literature review shall investigate this relationship.

3.4.2 U R BAN D E N S I T Y As distribution networks require large capital investment, DH is made feasible depending on maximising the heat sales per unit of capital investment, that is minimising pipe length per unit (Jangsten et al., 2011, p. 3). In the same way, higher densities are advantageous for DH as they improvement the distribution efficiency; where you have an increased concentration of people living in an urban area, rather than the same amount of people living in a more scattered environment, the distance required to transfer heat is reduced.

This is because higher population densities result in shorter pipe-work distances, which in turn results in less surface area for heat to transfer from the feed water to the external

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

surroundings (Thomas and Ritchie, 2009, p. 47); this is why DH’s potential is realised in urban rather than rural areas.

Pirouti et al. (2013, p. 149) argue that 50% of English heating demands have the appropriate concentration to make district heating a viable option for the country. It is important to determine what 50% is not suitable to be supplied by DH, as integration in these areas would result in poorer energy performance. As such, urban densities are crudely reflected in the urban form; “as heat density falls, the number of semi-detached houses becomes significant at the expense of terrace houses” (Pöyry Energy Consulting, 2009, p. 28). Thus higher demand densities are associated with multistory or multiunit buildings, while lower densities with detached and semi-detached housing.

Figure 3.10 Housing types and heat density Source Pöyry Energy Consulting, 2009, p. 28

3.4.3 H E AT D E M AN D D E N S I T Y Previous residential DH studies in the UK have been evaluated on the basis of the dwelling density, which Jangsten argues is only appropriate for early indication of sustainability efficiency (Jangsten et al., 2011, p. 4). This is because dwelling density does not factor an important parameter – the magnitude of heat requirements of a specified urban area. Heat demand densities incorporate this information, which may be expressed in two ways: area heat demand density or linear heat density (Jangsten et al., 2011, p. 4).

The thermal demand “per unit area of land” (Jangsten et al., 2011, p. 4) describes the area

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

heat demand density, while linear heat densities “[determine] heat area demand per length of trench of the heat network” (Jangsten et al., 2011, p. 4). According to Jangsten (2011, p. 4), area heat densities are typically used in the UK, where 3000kW/km2 is the benchmark area heat demand density that makes the system economically feasible (Pirouti, et al., 2013, p. 149). This value is supported by Pöyry Energy Consulting (2009, p.

28), specifying the same benchmark density.

The IEA’s District Heating and Cooling Programme is undertaking a series of research projects which look at the use of DH to supply heat to areas of low heat demand density.

Understanding the concept of thermal demand density stimulates the realisation that newly built areas would have a smaller thermal demand density than areas characterised by older architecture. As new buildings are built to higher specifications, less heat energy is lost to the external environment and therefore lowers heating demands. This would therefore affect higher “heat distribution loss per unit of heat delivered by a DH network” (Jangsten et al., 2011, p. 3), rendering a less energy efficient system. There are a limited number of ways to sensibly increase the heat demand density, such as shifting some of the electricity demand of washing machines to DH (Jangsten et al., 2011, p. 7).

3.5

T H E R MAL P R I N C I P L E S 3.5.1

IN

ARCHITECTURE

INTRODUCTION

A DH plant can only be sized if the heat demand of the dwellings is known. This requires an understanding of architectural thermal principles and how they affect the space heating demand (Steemers, 2003, p. 5). Architectural form informs the thermal state of a building as heat exchanges occur across the thermal envelope; Harvey describes its function “as [being] a barrier to the loss of interior heat or to the penetration of unwanted outside heat into the building” (Harvey, 2006, p. 36). While architectural form represents the amount of surface for heat to transfer through, its fabric dictates how much heat permeates across the building envelop.

The Government's Standard Assessment Procedure for Energy Rating of Dwellings (DECC, 2010) identifies the key parameters that should be taken into account when establishing

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

the heat demand of a building. The review shall only consider static state modelling, that is, thermal losses and gains that are stimulated by temperature differences.

3.5.2 T H E C O E F F I C I E N T O F B U I L DI N G H E A T L O S S The coefficient of building heat loss (Cb) describes the heat losses that are stimulated by the temperature difference between the internal and external environments. It is the sum of three different coefficients (O’Flynn, 2013):  Fabric heat transfer coefficient (Cf)  Thermal bridging heat transfer coefficient (Ctb)  And the ventilation heat transfer coefficient (Cv).

The first coefficient considers a building’s U-values and the area of each building element: external walls, roof, ground floor and openings. The U-value describes the rate of heat transfer in W/m2K (Harvey, 2006, p. 39). Highly conductive elements, such as glazing, will have higher U-values than materials with high thermal resistance, such as insulation. The following equation suggests how to calculate the total Cf for a building (O’Flynn, 2013, p.

2):

Thermal bridging heat losses occur through the physical gaps that result “at junctions between elements and around openings” (DECC, 2010 (2), p. 18). Due to the difficulty in determining the location and size of these gaps, the exact values for thermal bridging are difficult to calculate. Thus, estimations can be attempted by “including an allowance based on the total exposed surface area” (DECC, 2010 (2), p. 18). O’Flynn (2013, p. 2) suggests using a y value of 0.08W/m2K for buildings constructed under the Accredited Construction Details quality scheme or a value of 0.15 W/m2K for regular construction in the following equation:

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

The last principle to consider is that of infiltration. During the heating season, warm indoor is displaced by cooler outdoor air as it travels to the colder external environment via incompleteness in the building envelop. In order to calculate this heat loss, the building volume and the number of ACH must be known (O’Flynn, 2013, p. 3):

3.5.3 S O L AR G AI N S Heat gains occur through a building’s openings, that is its glazed elements, due to the sun’s radiative heat transfer. The amount of solar gain depends on the intensity of the radiation, the transmission allowance of the glass (τglass) and the area of the opening (O’Flynn, 2013, p. 4):

The average solar flux (Iᵩ) can be determined from the following table: Type of window (vertical unobstructed)

Average Solar Flux (W/m2)

South-facing windows

72

East and west-facing windows

48

North-facing windows

29

Table 3.3 Seasonal solar gain through windows Source reproduced from Mcmullan, 2007, p. 58

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

4

A C ASE S T UDY 4.1

I N T R O DU C T I O N

In the literature reviewed, established thresholds of thermal demand densities relate to cost feasibility, as seen in section 3.4.3. The first step of the research method is to choose an urban area that lies on this threshold density, addressing the first research aim This shall be done to determine whether biomass DH be more or less energy efficient than traditional heating systems in the lowest possible feasible density.

4.2

E S T AB L I S H I N G

THE

A R E A â&#x20AC;&#x2122; S T H E R M AL D E M AN D D E N S I T Y

As mentioned, 3000kW/km2 is the benchmark heat demand density that makes heating networks economically feasible Pirouti et al. (2013, p. 149). A Heat Density Map published by the UK government (Gov.uk, 2013 (1)), shall be used to identify an area which corresponds with this thermal heating density. However, due to the units used in the mapâ&#x20AC;&#x2122;s heat legend, this value shall be converted into kWh/m2:

Thus, the chosen site must lie within the heat density range of 8.7 kWh/m2 to 22 kWh/m2 range on the map.

The area chosen for investigation is part of the newly built (2012) Redrow Development site in Bristol. At this point, it is important to mention that the research model outlined in the next section is aimed to be applied to new builds (further explanation is given in section 5.1). However, a newly built development rather than a site that is currently under construction has been chosen because of the availability of data required on the housing.

The cluster of housing that will be used in the investigation is shown in Figure 4.2.

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure 4.1 National Heat Map Source Gov.uk, 2013 (1)

Figure 4.2 Overlay of Heat Map and Digimap of chosen dwellings Sources Gov.uk, 2013 (1) and Digimap, 2014

4.3

N E T WO R K O VE R VI E W

The proposed network layout has been based on the case study reviewed in section 3.2.5.

The aim of this dissertation is to try and estimate the performance of DH in the chosen area; the system has not been set out to achieve the lowest possible pressure drop, as a

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

further in-depth understanding of the principles of fluid mechanics would be needed to do this to effect. The boiler has been located in an open area which is easily accessible to allow straight forward delivery of fuels and has enough space for wood pellet storage. The proposed setup is approximately 218m in length.

Figure 4.3 Overview of district heating system

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

5

T HE R ESEARCH M ODEL

5.1

I N T R O DU C T I O N

The research model constitutes the second part of the research method. It shall outline the development of a conceptual, mathematical model designed to quantitatively assess the energy efficiency and carbon emissions of a proposed wood pellet LTDH system, a proposed wood pellet MTDH system and gas-fuelled domestic condensing boilers. The model shall be applied to the case study outlined in section 4. The hypothetical DH systems shall be informed by the literature reviewed; its purpose is to provide data for the model rather than to determine the optimum system for this case study.

Quantitative data required to set up the efficiency models model shall be derived from secondary resources. A number of journals which informed the literature review and background

reading

demonstrated

efficiency

modelling

through

computational

optimisation, as described in section 3.2.3.2. However, this dissertation shall see the development of a simpler and more conceptual mathematical model. Its purpose is to provide a robust tool for architectural designers to identify which heating method would be more appropriate for a new residential development. The model aims to determine whether a DH network would be clearly more energy and carbon efficient than the traditional condensing boilers, clearly less so or identify if further research will be required to establish this. Thus, the results will inform the discussion surrounding the final research aim.

5.2

DOMESTIC HOT WATER

This portion of the research contributes towards establishing the second research aim.

The annual DHW base load shall be assumed to remain constant throughout the year due to the minimal variation of energy requirement each month. The demand of each dwelling shall be calculated using the calculation outlined in Analysis of ESTâ&#x20AC;&#x2122;s domestic hot water trails and their implications for amendments to BREDEM and SAP (Shorrock, 2009, p.

10). The first step calculates the average litres per day of hot water required:

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

The number of occupants for each household shall be determined by a question survey targeted at the case study residents. If it is not possible to obtain an occupancy number for any of the dwellings, values shall be estimated according to the buildingâ&#x20AC;&#x2122;s total floor area as provided in the SAP Energy Performance Certificates (EPC Register, n.d.)

(Appendix I). The second step determines the annual energy content of the hot water used (QW) which will then be converted into kWh (Shorrock, 2009, p. 10). Assumed values for the constants in the equation below can be found in Table B1, Appendix B.

5.3

S P AC E H E AT I N G

This section of the model describes the information required to determine the total space heating demand during the heating season, addressing the rest of the second research aim. The building shape and glazing areas shall be established through primary research during a site visit; due to the private nature of the property, dimensions shall be estimated by eye. Any additional information that is required shall be derived using secondary resources, namely the energy performance certificates (EPC Register, n.d.). The equations outlined in section 3.5.2 and 3.5.3 shall be used to determine the following values.

5.3.1

V O L U ME

The total floor area of each dwelling shall be established from the Energy Performance Certificates provided by SAP. In order to determine the volume, a standard floor to ceiling height of 2.4m shall be assumed for each dwelling (Home Building, 2014).

5.3.2 U- V AL U E S The thermal transmittance of the dwellings shall be determined using their respective energy performance certificates. The certificates lack U-Values for the glazed elements of the building. In order to overcome this, an assumed valve shall be derived from table 5.1.

A value of 1.7 W/m2K shall be used as a mid-point value from the table, due to â&#x20AC;&#x2DC;very goodâ&#x20AC;&#x2122;

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

ratings on Energy Performance Certificates. The wall and floor areas will be calculated using Digimap Roam and an average floor height of 2.4m.

2

Table 5.1 Default U-Values (W/m K) Source DECC, 2010, The Government's Standard Assessment Procedure for Energy Rating of Dwellings, p. 189

5.3.3 T H E R M AL B R I D GI N G In line with Oâ&#x20AC;&#x2122;Flynn (2013, p. 2), it shall be assumed that the Redrow housing does not satisfy the Accredited Construction Details Quality Scheme, as no information has be found suggesting its use. As a result, an additional heat loss rate (y) of 0.15 W/m2K shall be using to calculate the thermal bridging heat loss coefficient.

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

5.3.4 I N F I L T R AT I O N According to the equation in section 3.5.2, the number of ACH is required to calculate the heat loss through infiltration, however, the energy performance certificates provide air permeability rates in m3/h.m2 @ 50Pa. In response, an average value of 0.6 ACH shall be assumed (EPB, 2014 and Leeds Metropolitan University, 2013).

5.3.5 T H E A N N U AL S P AC E H E AT I N G D E M AN D The annual space heating demand shall be determined as follows (CIBSE, 2006, p. 7):

Using HDD is a simple and relatively accurate method of determining the average annual heating requirements in different cities in the UK (CIBSE, 2008, p. 10). Using a base temperature of 15.5°C, gives the average annual and monthly HDDs over 20 years:

Table 5.2 Mean monthly and annual heating degree-day totals (1976-1995) Source CIBSE, 2008, p. 10

5.4

D I S T R I C T H E AT I N G : E N E R G Y E F F I C I E N C Y

This section of the methodology describes the proposed DH setup and seeks to estimate the heat losses that will occur in the thermal production and distribution stages of the systems. From this, the combined system efficiency of the boilers and primary network will be calculated. The entirety of this section is based on the secondary resources, including the literature discussed in section 3.3. This section partially addresses the third research

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

aim outlined in the introduction, the results from which will inform the discussion surrounding the fourth aim.

5.4.1 T H E R M AL P R O DU C T I O N A multiple boiler setup consisting of two wood pellet boilers and a gas condensing boiler shall be assumed. DHW shall be supplied by the first wood pellet boiler (B1) which will consistently run throughout the year, while 80% of the space heating demands during heating season shall be satisfied by the second wood pellet boiler (B2) and the final 20% by a top-up gas boiler (B3). A 110 litre accumulator will be used to minimise part loading and support the use of higher seasonal efficiencies.

The accumulator shall assume a standardised heat loss of 0.0152kWh/litre/day (DECC, 2010, The Government's Standard Assessment Procedure for Energy Rating of Dwellings, p.

20). An 85% seasonal efficiency shall be assumed for the wood pellet boilers, along with a combustion efficiency of 100%. The gas top-up boiler’s seasonal efficiency shall be derived using the SAP2005 SEDBUK ratings (Boilers, 2014) table of results; very similar boiler ratings are demonstrated and will be averaged to 91% (Table H1, Appendix H). Assumed values based on secondary resources shall be used because of the dissertations agenda to determine the effectiveness of the overall DH system rather than undertake an in-depth study of combustion technology. Hayton and Shiret (2009, p. 4) provide the following equation to establish the combined efficiency of multiple boilers:

5.4.2 T H E R M AL D I S T R I BU T I O N Based on the information gathered in the literature review, the proposed primary network system shall consist of ø80/80/250 twin pipes (section 3.5.3). The energy efficiency of both a LTDH and a MTDH system shall be evaluated, whereby the former shall have a supply and return temperature of 60°C and 40°C respectively, while the MTDH network shall supply heat at 110°C and have a return temperature of 80°C.

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

According to Woods and Zdaniuk (2011, p. 8), “network heat losses do not vary significantly throughout the year”; therefore, the annual heat loss shall be calculated assuming that the heat loss per month is constant. The equation provided in section 3.3.4 shall be used to determine the annual heat loss in the primary distribution network. A ground temperature (Tg) of 11°C shall assumed (Centre for Sustainable Energy, 2014). The combined efficiency of the accumulator and the primary network will then be calculated for each system using the following equation (Longhurst, 2012, p. 17):

5.4.3 O VE R AL L S YS T E M E F F I C I E N C Y The combined boiler and distribution efficiency for each DH system will be used as a comparison to the seasonal efficiency of the individual condensing boilers. Overall system efficiency shall be calculated by means of the following equation (Vallios et al., 2008, p.

666):

5.5

D O M E S T I C C O N DE N S I N G B O I L E R S : E N E R G Y E F F I C I E N C Y

Combination condensing boilers are instantaneous heaters, therefore “’primary’ and ‘cylinder’ losses [shall] not [be] used in the calculation” (DECC, 2010, The Government's Standard Assessment Procedure for Energy Rating of Dwellings, p. 19). An average seasonal efficiency of 91% (section 5.4.1) shall be assumed for all 13 boilers as they were installed within the same year.

5.6

D I S T R I C T H E AT I N G : C AR BO N E MI S S I O N S

This section of the model addresses the second part of the third research aim; it will quantitatively estimate the annual carbon lifecycle emissions of wood pellets and gas using secondary sources. Secondly, it shall estimate the electrical power required to pump water using the equations outlined in the literature review (section 3.3.5), where any

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

additional data required shall be gathered from secondary sources. The annual CO2 emissions from the pump shall then be estimated.

5.6.1

F U E L L I F E C Y C L E E MI S S I O N S

In order to estimate the embodied carbon of wood pellets and natural gas, it will first be necessary to determine the annual energy delivered by the each fuel before boiler efficiency losses:

Even though combustion emissions from wood pellets are considered CO2 neutral (Conversion Factors, 2013, p. 3), all forms of woody biomass possess embodied carbon due to material processing and transportation. Approximate values for lifecycle CO2 emissions were assumed for wood pellets (20.57 kgCO2/MWh) and natural gas (225.54 kgCO2/MWh), based on data provided by Forever Fuels (2014) whereby transport emissions are included. The annual CO2 content of each fuel shall be calculated by multiplying the CO2 lifecycle emissions by its associated EIN.

5.6.2 P U MP I N G E MI S S I O N S In order to determine the CO2 emissions associated with electrical pumping, the rule of thumb TPL of 100Pa/m shall be assumed (Pirouti et al., 2013, p. 150) and multiplied by the length of the primary pipework. Even though this introduces a margin of error as this value does not accommodate for increased pressure losses at bends, an estimated value will need to be used to determine the velocity of flow (Harvey, 2006, p. 304):

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

A coefficient of friction (λ) shall need to be established for the media pipes using secondary resources, which will be assumed to be made from PEX; a λ value of 0.16 shall be used (PEX Tubing Technical Information, 2012, p. 3). The following equation shall be carried out for each pipe, calculating the electric power required to compensate for parasitic losses (Harvey, 2006, p. 304):

Figure 3.6 provides pump and motor efficiencies, which can be based on the product of Av. The result shall be converted to kWh in order to determine the carbon emissions of grid electricity at 0.44548 kgCO2eq/kWh (Conversion Factors, 2013, p. 3).

Table 5.3 Typical fan and motor peak-load efficiencies Source Harvey, 2006, p. 305

5.7

D O M E S T I C C O N DE N S I N G B O I L E R S : C A R BO N E M I S S I O N S

The total lifecycle carbon emissions from the existing 13 gas-fuelled condensing boilers shall be determined using secondary resources; this represents the last portion of the third research aim. In order to determine the energy delivered by the natural gas, the same steps shall be allowed as described in section 5.6.1, except that the annual heat delivered for DHW and space heating shall be multiplied by an estimated value of the fuel’s lifecycle carbon emissions - 225.54 kgCO2/MWh (Forever Fuels, 2014).

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6

D ISCUSSION

6.1

AND

F INDINGS

I N T R O DU C T I O N

Though the model has been applied to the existing house scheme described in section 4, its use is aimed at new builds, as mentioned. This is because the model does not consider any social or contextual factors that would need to be regarded in the case of integrating DH within an existing site, such as those discussed in section 3.1.3. The modelâ&#x20AC;&#x2122;s primary aim is to determine whether DH is a viable low-carbon heating solution (that is if it performs in an energy efficient manner and significantly reduces carbon emissions) in the specified urban density. An existing site was used in the research method in order to have access to data required to determine the annual heat demand. The model calculations can be found in the attached Appendices.

6.2

A N N U AL D O ME S T I C H O T W A T E R D E M AN D

The model determined an average annual DHW demand of 26.22MWh â&#x20AC;&#x201C; 31% of the total heat demand. Flattening the annual energy profile created a negligible error as the DHW demand varies slightly each month:

Figure 6.1 Monthly variation in hot water use Source Shorrock, 2009, p. 3

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

The dotted lines represent a +/- 10% variation in hot water use throughout the year. This supports the argument that the small seasonal variation in DHW use (Shorrock, 2009, p. 3) would not dramatically affect the total heat demand profile and, thus, the annual heat demand.

6.3

A N N U AL S P AC E H E A T I N G D E M AN D

The total annual space heating demand was calculated to be 58.05 MWh, representing 69% of the total annual heat demand; this percentage seems like a typical DHW to space heating demand ratio.

90 80 70 60 50

Space Heating

40

DHW

30 20 10 0 Heating Profile (MWh)

Figure 6.2 Total annual heating profile in MWh

A selection of dwellings have been used to compare the model results with the annual energy use recorded in the SAP certificates. The households used for the comparison are those which have an accurate number of occupants. Figure 6.3 shows a relatively constant relationship, whereby the model results suggest marginally less energy use than the energy certificates. This is to be expected as the SAP data includes the annual energy used for low energy lighting, as specified in the certificates.

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

12000 10000 8000 6000

Results (kWh) SAP Data (kWh)

4000 2000 0 2, Home Leas Close

8, Home Leas Close

77, Long Down 83, Long Down Avenue Avenue

Figure 6.3 Comparison of results and SAP

6.4

D I S T R I C T H E AT I N G : E N E R G Y E F F I C I E N C Y 6.4.1 T H E R M AL P R O DU C T I O N

The combined seasonal efficiency of the two wood pellet boilers and the gas boilers was calculated to be 86%. The assumed 85% seasonal efficiency for the wood pellet boilers may be seen as an optimistic value, however, since the boilers would be newly installed and assuming an efficient boiler setup, Kirk (2011, 56) argues that this value is achievable.

92 91 90

Wood pellet boiler B1

89 88

Wood pellet boiler B2

87 86

Gas condensing boiler B3

85 84

Combined

83 82 Efficiency % Figure 6.4 Seasonal efficiencies

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6.4.2 T H E R M AL D I S T R I BU T I O N In both the MTDH and LTDH systems, an almost negligible value of 0.6 MWh of heat is lost via the accumulator, representing less than 1% of the total heat supplied by the fuel in both DH scenarios. The primary pipework in the MTDH system accounts for the largest losses in the entire system - 56 MWh, 34% of the total energy supplied by the fuels. This resulted in a thermal distribution network efficiency of 60%. Heat losses in the LTDH primary network are also the largest in the system, estimated at 20% of the overall heat supplied by the fuels - 26 MWh. The combined thermal distribution and accumulator efficiency was calculated to be 76%. This 16% difference in efficiency supports Zinko et al.

(2008) in section 3.2.3.2, who states that LTDH systems should be used in low demand areas.

The high loss from the network is partly due to the length of the distribution network. The boiler plant was chosen to be housed where vehicle access is possible to deliver volumes of wood pellets. These results indicate that locating the energy centre as close to the dwellings as possible in areas of this thermal demand density would be in the communityâ&#x20AC;&#x2122;s best interest, due to the high percentage of distribution losses. Further to this, the high heat losses in the primary pipework would suggest that the use of more advanced pipe technologies, such as triple pipes or egg-shaped pipes, is appropriate in areas of this thermal demand density.

6.4.3 O VE R AL L S YS T E M E F F I C I E N C Y The overall MTDH system efficiency was calculated to be 51%, 40% less than the 91% efficiency of the existing heating systems. Since the LTDH system suffers less primary network losses due to the lower supply temperature, an overall system efficiency of 65% was estimated, establishing that LTDH performance would surpass MTDH by 14% and fall short of achieving the same efficiency as the condensing boilers by 26%.

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100 90 80 70 60

MTDH

50

LTDH

40

Individual Condensing Boilers

30 20 10 0 Efficiency % Figure 6.5 Overall System Energy Efficiency

Table 6.1, figure 6.5 and figure 6.6 illustrate the quantity and location of heat losses that occurred throughout the systems. The heat losses in the MTDH system are too large for it to be considered an energy efficient system in the specified context, especially when compared to the 91% efficiency of the condensing boilers. At first glance, LTDH may also seem to not perform well. However, considering the possibility of a system improvement of 5%-10%, the system would then perform at 70%-75%.

As no set benchmark value for ‘high efficiency’ could be established in the review of literature and, considering that a maximum efficiency of 86% is achievable due to the seasonal efficiencies of the boilers, it may be argued that this would be relatively efficient.

This argument is further supported using directly comparing the benchmark value for energy efficient biomass boilers – 75% (DCLG, 2011, p. 31). If this were achievable, it would be appropriate to consider a comparison of the LTDH system with other competitive low carbon technologies, such as ground source heat pumps.

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LTDH MWh

LTDH ƞ%

MTDH MWh

MTDH ƞ%

Input

129

100

164

100

Boiler losses

18

14

23

14

Accumulator losses

0.61

1

0.61

1

Primary network losses

26

20

56

34

84 MWh

65%

84 MWh

51%

Output

Table 6.1 Efficiency breakdown

Figure 6.6 LTDH system Sankey diagram

Figure 6.7 MTDH system Sankey diagram

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6.5

C AR BO N E MI S S I O N S

The proposed DH systems emit significantly less CO2 when compared to the existing boilers. Results suggest that the LTDH system would reduce emissions by 67%, whereby the wood pellets annually emit 2304 kgCO2 and gas combustion emits 3841 kgCO2 per year. On the other hand, due to the increased fuel requirement in the MTDH, CO2 emissions are reduced by 59%; the wood pellets and natural gas give off 2924 kgCO2 and 3841 kgCO2 annually, respectively. On the other hand, the sum of annual CO2 emissions from the dwellingsâ&#x20AC;&#x2122; gas boilers is 20883 kgCO2. Thus, both systems have the potential to successfully reduce carbon savings.

A 21.8 kPA pressure drop was calculated in each media pipe with a flow velocity of 0.316m/s, resulting in annual parasitic losses of 1518 kWh of electrical energy. This translates into annual pumping CO2 emissions of 676 kgCO2. The pumping and fuel lifecycle emissions of both DH systems were added and directly compared to the fuel lifecycle emissions of the domestic condensing boilers, as described below:

25000

20000

15000

Electricity Gas

10000

Wood pellets

5000

0 MTDH

LTDH

Individual Boilers

Figure 6.8 Annual carbon emissions in kgCO2 from relative fuels

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6.6

R E S E AR C H L I MI T AT I O N S 6.6.1

AN D

A R E AS

O F I MP R O VE ME N T

D O ME S T I C H O T W AT E R D E M AN D M O DE L L I N G

In order to determine the number of occupants in each house, it was necessary to visit the site and ask a member of each household about its number of occupants. However, it was not possible to attain exact data for all the dwellings as some inhabitants were not available for questioning. As a result, the quantity of occupants in the vacant households was estimated based on the total floor area provided in the SAP Energy Performance Certificates, giving a negligible error. The red cells in Table B2 (Appendix B) describe the accurate occupant numbers, while the blue cells denote assumed occupant values.

6.6.2 S P A C E H E AT I N G D E M A N DI N G M O DE L L I N G Due to the private nature of Redrow Estate, the dimensions of window glazing and building shapes were determined from visual examination while visiting the site. As a result, the fabric heat loss and thermal bridging coefficients demonstrate inaccuracies.

Further to this, assuming a standard heat loss rate of 0.15 W/m2K when calculating the thermal bridging coefficient introduces a margin of error.

Initially, the ACH were calculated using a 1/20 rule of thumb conversion to convert the air permeability (provided in the energy performance certificates) from 50 Pa to 4Pa. The results rendered very tight values, averaging at 0.2 ACH. This value was unexpected as it describes a very low infiltration rate; PassivHaus standards specify 0.6 at 50Pa (Passivhaus, 2014). Therefore the calculation was revisited whereby an estimated value of 0.6 ACH at normal pressure was used (Leeds Metropolitan University, 2013 and EPB, 2014). This introduces a margin of error.

The equation used to determine the annual space heating demand is limited in that it could not take solar gain into account as it is independent of temperature. This occurred due to the inability to convert the equationâ&#x20AC;&#x2122;s units from kW to kW/K, and thus unable to multiply it by the HDD. This will result in a higher theoretical annual thermal demand than will actually be required. However, the margin of error this introduces may be moderate as solar gains predominantly occur during the summer months which shall not be considered in this method, as the heating season ranges from October to April.

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Table 5.2 takes the HDD average from 1976-1995 which introduces a margin of error.

According the CIBSE, “the rise of atmospheric temperatures due to climate change may mean that historic 20-year averages will not be appropriate. [...] In the period 1976–1995, annual heating degree-days in London and Edinburgh fell by around 10%” (CIBSE, 2006, p. 5). However, it was only possible to find more recent HDDs which averaged over five years. In view of this and the fact that, “the rate of temperature rise in the near future will dictate how reliable these values will be for setting energy budgets” (CIBSE, 2006, p. 5), an area of improvement would be to utilise computational thermal modelling software, such as IES Virtual Environment. Dynamic modelling would also rectify the majority of the previous mentioned errors, allowing for more a more accurate evaluation of annual heat demands.

6.6.3 C AR BO N E F F I C I E N C Y M O DE L L I N G Using an estimate for the TPL introduces a margin of error; this value does not account for the increased pressure loss that occurs at bends in the pipeline. However, the pressure drop does not need to be entirely accurate to effectively compare the carbon efficiencies of the two heating systems. Furthermore, parasitic losses in the individual condensing boilers were not considered. Moreover, the values used for fuel lifecycle emissions are estimated values. It would be impossible to determine the embedded carbon of fuel transportation unless a fuel source was established. It is, therefore, suggested that a supplier is researched or decided upon prior to model application.

6.7

M O DE L A D AP T A BI L I T Y

As the demand for sustainable heating technologies intensifies, so will the need to design building services to efficiently perform and adapt to climate change. Thus, it is important that the research can be applied to different urban contexts.

The model’s simplicity makes it easy to apply to various types of urban scenarios; the basic calculations aim to provide indicative results for proposed DH systems, that is, indicative energy and carbon efficiencies. This will allow architectural designers to determine whether the technology is worth considering. A major source of information in the research was the SAP energy performance certificates which would not be available

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for projects that are under construction. As a result, the model would be effectively utilised when information regarding buildingsâ&#x20AC;&#x2122; forms and constructions would be available.

The modelâ&#x20AC;&#x2122;s application to existing developments would still be effective in the way of determining carbon emissions and energy efficiencies if SAP performance certificates were available. If the housing stock in question did not have SAP certificates, then there would be a gap in the secondary resources required to determine the annual heat demands. As a result, data concerning the heat loss calculations would have to be assumed or further research would be required. Moreover, the model would be limited in that it does not take contextual factors, such as space availability and the location of surrounding services into account.

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7

C ONCLUSION

7.1

A N O VE R VI E W From the outset, the intention of this study was to determine whether a biomass district heating system would be an environmentally sustainable, low carbon heating solution in areas of low thermal demand density (the term ‘environmentally sustainable technology’ has been characterised as being both energy and carbon efficient). This would be achieved by comparing the estimated energy and carbon efficiency of a wood pellet DH system with that of domestic condensing boilers supplied by gas from the grid. An urban area which has the ‘feasibility benchmark’ thermal demand density of 3000 kW/km2 has been investigated. The aim of investigating this demand density was to provide architectural designers with a quick tool to assess whether LTDH or MTDH would be an environmentally sustainable heating technology and what carbon savings could be made.

The first and second research aims do not directly answer the central research question.

Rather, the first aim allows for the contextual heat demand density to be determined for the research. The second aim’s function is to enable the calculation of the third aim; the energy and carbon efficiencies of the systems can only be calculated if the heat demand is known. The results from the third aim allow conclusions to be drawn to answer the dissertation’s fourth aim.

The review of literature provided an insight into DH technology and informed the proposed DH setup used in the research model. The importance of boiler operation and its implication on efficient thermal production were highlighted; further to this, an understanding of the different types of distribution pipes was discussed. The following section of the literature cemented an understanding of the energy losses that occur in DH systems, be they heat or pumping losses. It was found that the primary networks were responsible for the majority of the systems’ heat losses. The third section established the relationship between energy efficiency and thermal demand densities. Moreover, the heat demand implications of new construction regulations were discussed; it is less likely for new build areas to be efficiently supplied by DH networks. Finally, thermal principles in

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architecture were investigated, particularly static heat losses that occur between the internal and external environments. These principles allowed for the evaluation of the annual energy demand of the investigated area.

7.2

V I A BI L I T Y

O F I N T E GR AT I O N

The research suggests that, even though it is just economically feasible to utilise DH at a density of 10.8kWh/m2, it is not environmentally feasible to incorporate MTDH and it is not immediately clear whether LTDH is viable. Hence, LTDH systems should always be considered over MTDH systems in areas with this thermal demand density, even though the former are more cost intensive. MTDH would be more suitable in urban areas with higher heat demands; this may be achieved by servicing older buildings or more densely populated areas. LTDH performs at an energy efficiency of 65%, a 26% difference to the existing heating systems. This result does not clearly indicate whether LTDH would be viable or not; further research will be required to determine whether its performance could be improved.

As LTDH could potentially cut carbon emissions by 67%, it may be argued that a direct comparison between the latter and a 26% decrease in energy efficiency would suggest an environmentally sustainable solution. An effective shift to sustainable technologies should encourage the use of low-carbon fuels but, also, that the technologies used are efficient to reduce the fuel input required; biomass fuels are a finite resource thus their utilisation should be carried out responsibly and efficiently. Thus, a balance should try to be struck between the two principles.

7.3

F U R T H E R R E S E AR C H 7.3.1

T H E R M AL D E M AN D D E N S I T I E S

In order to determine if MTDH could be viable at a higher heat demand density, the research method should be reiterated in the next density band on the National Heat Map (22-27kW/km2); this band may be characterised by dwellings with higher population densities per unit area, that is, developments with more flats and less semi-detached housing. Furthermore, this density bracket may have been a more suitable area for

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investigation if it renders more accurate results with regard to LTDH and potential use for MTDH. 7.3.2 S YS T E M I MP R O VE ME N T S In line with the previous suggestion, it would be beneficial to research further improvements that could be made to the primary network. This would be achieved by using better performance U-values; the values used were from a paper published in 2006 and newer technologies would pose better thermal performance. Moreover, conducting the research using recent developments in piping technology, such as triple pipes or asymmetrical egg-shaped piping, will again reduce heat losses and render higher a energy efficiency. Further investigation into these types of piping systems would be necessary to determine if urban areas with a thermal demand density of 10.8kWh/m2 could be efficiently supplied by LTDH. If the research shows favourable results for LTDH, then it would be fitting to compare its energy and carbon efficiency to other competitive low carbon technologies, such as ground source heat pumps.

Additionally, the vicinity of the thermal production facility contributes greatly to heat losses so reducing the network length would be a straight forward way of combating this.

Parameters that were not factored into the research would have to be considered in real application. Burning wood pellets would emit harmful particulates in the flue gas, which may introduce a limit as to how close the boiler house can be constructed to the residential dwellings. As such, this introduces an area for further research.

7.3.3 C L I M AT E C H AN GE CIBSE have predicted heating requirements to fall by 30%-40% by the 2080s (CIBSE, 2006, p. 5). Integration of DH is cost intensive and invasive, thus it is imperative that they continue to perform efficiently within the future climate. The Prometheus database uses â&#x20AC;&#x153;probabilistic climate change data to future-proof design decisions in the building sectorâ&#x20AC;?

(Robinson, 2014). It would be compelling to use such a database and integrate it into the research model to determine whether DH would be a viable low carbon heating solution for low-density urban areas in half a century, even if they prove to be so now.

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8

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Woods, P. S. and Zdaniuk, G. (2011). CHP and District Heating - how efficient are these technologies? [pdf] CIBSE. www.cibse.org/content/cibsesymposium2011/Paper089.pdf [Accessed: 5 Mar 2014].

Zinko, H., Bøhm, B., Kristjansson, H., Ottoson, U., Rämä, M. and Sipilä, K. (2008). District heating distribution in areas with low heat demand density. [report] IEA.

53

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

9

B IBLIOGRAPHY Arca53 (2014). Comparison of Fossil Fuels, Biomass and Electricity for Heating Homes. [online] Available at: http://www.arca53.dsl.pipex.com/index_files/fuel1.htm [Accessed: 6 March 2014].

Behnaz, R. and Rosen, M. A. (2011). District Heating and Cooling: Review of technology and potential enhancements. Applied Energy, 93 (2012), pp. 2-10. Available from: doi: 10.1016/j.apenergy.2011.04.020.

Boyle, G., Everett, B. and Ramage, J. (2004). Energy Systems and Sustainability â&#x20AC;&#x201C; Power for a sustainable future. Oxford: Oxford University Press, Oxford in association with The Open University, Milton Kenyes.

Carbon Trust (2012). Biomass fuel Procurement guide. [pdf] London: Carbon Trust. https://www.carbontrust.com/media/88607/ctg074-biomass-fuel-procurement-guide.pdf [Accessed: 13 Mar 2014].

Curtis, M. (2010). Woody Biomass: Environmental Friend or Foe? Undergraduate. University of the West of England.

DECC (2013). Summary Evidence on District Heating Networks in the UK. URN 13D 183. [report] London: DECC. Available at: https://www.gov.uk/government/publications/summary-evidence-on-district-heatingnetworks-in-the-uk [Accessed: 12 Jan 2014].

DECC (2013). The Future of Heating: Meeting the challenge (Evidence Annex). [report] London: DECC. Available at: https://www.gov.uk/government/publications/the-future-ofheating-meeting-the-challenge [Accessed: 12 Jan 2014].

Energy Saving Trust (2004). Community heating - a guide. [pdf] London: Energy Saving Trust. [Accessed: 9 Mar 2014].

54

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Finney, K. N., Sharifi, V. N., Swithenbank, J., Nolan, A., White, S. and Ogden, S. (2012).

Developments to an existing city-wide district energy network - Part I: Identification of potential expansions using heat mapping. Energy Conservation and Management, 62 (2012), pp. 165-175. Available from: doi: 10.1016/j.enconman.2012.03.006

Gov.uk (2013). Increasing the use of low-carbon technologies - Policy. [online] Available at: https://www.gov.uk/government/policies/increasing-the-use-of-low-carbon-technologies [Accessed: 12 Jan 2014].

Hui, S. C. M. (2001). Low energy building design in high density urban cities. Renewable Energy, 24 (2001), pp. 627-640. Available from: doi: S0960-1481(01)0 0049-0.

Joelsson, A. and Gustavsson, L. (2008). District heating and energy efficiency in detached houses of differing size and construction. Applied Energy, 86 (2009), pp. 126-134. Available from: doi: 10.1016/j.apenergy.2008.03.012.

Sjรถdin, J. and Henning, D. (2003). Calculating the marginal costs of a district-heating utility. Applied Energy, 78 (2004), pp. 1-18. Available from: doi: 10.1016/S03062619(03)00120-X.

Thyholt, M. and Hestnes, A. G. (2007). Heat supply to low-energy buildings in district heating areas. Analysis of CO2 emissions and electricity supply security. Energy and Buildings, 40 (2008), pp. 131-139. Available from: doi: 10.1016/j.enbuild.2007.01.016.

55

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

A PPENDIX A ETHICAL REVIEW CHECKLIST

56

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

57

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

A PPENDIX B A N N U A L DHW D E M A N D C A L C U L A T I O N S S PR E A D S H E E T N.B. an electronic copy of the spreadsheet is available on the CD

Table B1 Constants ρ

1 kg/litre

c

4190 J/kgK

θannual

37 °C

Nannual

365 days

Table B2 Dwelling Address

N

Vday (ltr/day)

QDHW-annual (J)

QDHW-annual (MWh)

2, Home Leas Close

4

136

7695689200

2137.69

4, Home Leas Close

4

136

7695689200

2137.69

6, Home Leas Close

4

136

7695689200

2137.69

8, Home Leas Close

3

111

6281040450

1744.73

18, Home Leas Close

3

111

6281040450

1744.73

20, Home Leas Close

3

111

6281040450

1744.73

22, Home Leas Close

2

86

4866391700

1351.78

24, Home Leas Close

3

111

6281040450

1744.73

75, Long Down Avenue

5

161

9110337950

2530.65

77, Long Down Avenue

6

186

10524986700

2923.61

79, Long Down Avenue

4

136

7695689200

2137.69

81, Long Down Avenue

5

161

9110337950

2530.65

83, Long Down Avenue

2

86

4866391700

1351.78

Total

26218.16

Total

26.22

58

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

A PPENDIX C WINDOW DIMENSIONS SURVEY N.B. an electronic copy of the spreadsheet is available on the CD

Table C1 Dwelling Address 2, Home Leas Close

AWN (m2)

AWS (m2)

AWE (m2)

AWW (m2)

2.8

1.54

0.99

0.4

1.54

2.64

0.4

3.08

1.12

AWT (m2)

0.99 3.6

-

7.15

4.75

1.54

0.99

1.54

2.64

3.08

1.12

0.99

2.8

7.15

7.55

1.54

0.99

1.54

2.64

3.08

1.12

0.99

2.8

-

7.15

7.55

2.8

1.54

0.99

0.4

1.54

2.64

0.4

3.08

1.12

4, Home Leas Close

-

-

6, Home Leas Close

8, Home Leas Close

15.5

14.7

14.7

0.99 18, Home Leas Close

3.6

7.15

4.75

0.99

3

1.54

0.99

3.08

0.99

1.54

1.12

15.5

2.8 1.98

-

7.62

6.45

16.05

59

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

20, Home Leas Close

3

1.54

3.08

0.99

1.54

1.12 2.8

-

-

22, Home Leas Close

7.62

6.45

3

1.54

3.08

0.99

1.54

1.12

14.07

2.8 24, Home Leas Close

-

7.62

6.45

0.99

3

1.54

0.99

3.08

0.99

1.54

1.12

14.07

2.8

75, Long Down Avenue

77, Long Down Avenue

-

1.98

7.62

6.45

1.82

1.8

1.98

1.82

0.8

2.2

3.8

0.8

2.2

3.8

2.64

2.8

3.8

2.64

2.8

0.99

17.84

9.67

-

1.82

1.8

1.98

1.82

0.8

2.2

3.8

0.8

2.2

3.8

2.64

3.8

2.64

16.05

9.18

36.69

6.38

-

33.89

-

-

13.63

0.99 2.8

79, Long Down Avenue

15.04

12.47

0.99

0.99

0.99

3.08

0.99

2.8

0.99 2.8 6.76

6.87

60

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

81, Long Down Avenue

0.99

0.99

0.99

3.08

0.99

2.8

0.99 2.8

83, Long Down Avenue

6.76

6.87

0.99

0.99

0.99

0.99

2.145

2.145

2.8

2.8

6.925

6.925

-

-

13.63

-

-

13.85

61

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

A PPENDIX D ANNUAL SPACE HEATING DEMAND CALCULATIONS SPREADSHEET N.B. an electronic copy of the spreadsheet is available on the CD

Table D1 Volume ATF (m2)

h (m)

V (m3)

2, Home Leas Close

76

2.4

182.4

4, Home Leas Close

76

2.4

182.4

6, Home Leas Close

76

2.4

182.4

8, Home Leas Close

76

2.4

182.4

18, Home Leas Close

63

2.4

151.2

20, Home Leas Close

63

2.4

151.2

22, Home Leas Close

63

2.4

151.2

24, Home Leas Close

63

2.4

151.2

75, Long Down Avenue

140

2.4

336

77, Long Down Avenue

140

2.4

336

79, Long Down Avenue

125

2.4

300

81, Long Down Avenue

125

2.4

300

83, Long Down Avenue

55

2.4

132

Dwelling Address

Table D2 Fabric Heat Transfer Coefficient (Cf) Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

110.50

29.84

Window

1.70

15.50

26.35

Floor

0.16

38.25

6.12

Roof

0.11

43.35

4.77

2, Home Leas Close

67.07 Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

28.50

7.70

Window

1.70

14.70

24.99

Floor

0.16

38.25

6.12

Roof

0.11

42.27

4.65

4, Home Leas Close

43.46

62

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

28.50

7.70

Window

1.70

14.70

24.99

Floor

0.16

38.25

6.12

Roof

0.11

42.27

4.65

6, Home Leas Close

43.46 Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

110.50

29.84

Window

1.70

15.50

26.35

Floor

0.16

38.25

6.12

Roof

0.11

43.35

4.77

8, Home Leas Close

67.07 Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

99.95

26.99

Window

1.70

16.05

27.29

Floor

0.17

40.00

6.80

Roof

0.11

46.65

5.13

18, Home Leas Close

66.20 Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

24.33

6.57

Window

1.70

14.07

23.92

Floor

0.17

40.00

6.80

Roof

0.11

35.09

3.86

20, Home Leas Close

41.15 Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

24.33

6.57

Window

1.70

14.07

23.92

Floor

0.17

40.00

6.80

Roof

0.11

35.09

3.86

22, Home Leas Close

41.15 Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

86.35

23.31

Window

1.70

16.05

27.29

Floor

0.17

32.00

5.44

24, Home Leas Close

63

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Roof

0.11

37.32

4.10 60.14

Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

107.31

28.97

Window

1.70

36.69

62.37

Floor

0.16

50.00

8.00

Roof

0.11

36.93

4.06

75, Long Down Avenue

103.41 Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

110.11

29.73

Window

1.70

33.89

57.61

Floor

0.16

50.00

8.00

Roof

0.11

36.93

4.06

77, Long Down Avenue

99.40 Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

100.67

27.18

Window

1.70

13.63

23.17

Floor

0.17

54.00

9.18

Roof

0.16

64.90

10.38

79, Long Down Avenue

69.92 Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

72.32

19.53

Window

1.70

13.63

23.17

Floor

0.17

54.00

9.18

Roof

0.16

64.90

10.38

81, Long Down Avenue

62.26 Average U Value (W/m2K)

A (m2)

Cf (W/K)

Walls

0.27

50.95

13.76

Window

1.70

13.85

23.55

Floor

0.18

52.25

9.41

Roof

0.11

64.13

7.05

83, Long Down Avenue

53.76

64

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Table D3 Thermal Bridging Heat Transfer Coefficient (Ctb) Constant y (W/m2K)

0.15

2, Home Leas Close

A (m2)

Ctb (W/K)

Walls

110.50

16.58

Window

15.50

2.33

Roof

43.35

6.50 25.40

4, Home Leas Close

A (m2)

Ctb (W/K)

Walls

28.50

4.28

Window

14.70

2.21

Roof

42.27

6.34 12.82

6, Home Leas Close

A (m2)

Ctb (W/K)

Walls

28.50

4.28

Window

14.70

2.21

Roof

42.27

6.34 12.82

8, Home Leas Close

A (m2)

Ctb (W/K)

Walls

110.50

16.58

Window

15.50

2.33

Roof

43.35

6.50 25.40

18, Home Leas Close

A (m2)

Ctb (W/K)

Walls

99.95

14.99

Window

16.05

2.41

Roof

46.65

7.00 24.40

20, Home Leas Close

A (m2)

Ctb (W/K)

Walls

24.33

3.65

Window

14.07

2.11

Roof

35.09

5.26 11.02

65

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

22, Home Leas Close

A (m2)

Ctb (W/K)

Walls

24.33

3.65

Window

14.07

2.11

Roof

35.09

5.26 11.02

24, Home Leas Close

A (m2)

Ctb (W/K)

Walls

86.35

12.95

Window

16.05

2.41

Roof

37.32

5.60 20.96

75, Long Down Avenue

A (m2)

Ctb (W/K)

Walls

107.31

16.10

Window

36.69

5.50

Roof

36.93

5.54 27.14

77, Long Down Avenue

A (m2)

Ctb (W/K)

Walls

110.11

16.52

Window

33.89

5.08

Roof

36.93

5.54 27.14

79, Long Down Avenue

A (m2)

Ctb (W/K)

Walls

100.67

15.10

Window

13.63

2.04

Roof

64.90

9.73 26.88

81, Long Down Avenue

A (m2)

Ctb (W/K)

Walls

72.32

10.85

Window

13.63

2.04

Roof

64.90

9.73 22.63

83, Long Down Avenue

A (m2)

Ctb (W/K)

Walls

50.95

7.64

Window

13.85

2.08

Roof

64.13

9.62 19.34

66

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Table D4 Ventilation Heat Transfer Coefficient Original Calculation Address

P (m3/h.m2)

As (m2)

n (ac/hr)

Cv (W/K)

2, Home Leas Close

6.0

169.35

0.279

16.935

4, Home Leas Close

5.0

85.47

0.117

7.123

6, Home Leas Close

5.0

85.47

0.117

7.123

8, Home Leas Close

6.0

169.35

0.279

16.935

18, Home Leas Close

6.0

162.65

0.323

16.265

20, Home Leas Close

6.0

73.49

0.146

7.349

22, Home Leas Close

6.0

73.49

0.146

7.349

24, Home Leas Close

6.0

139.72

0.277

13.972

75, Long Down Avenue

4.3

180.93

0.116

12.966

77, Long Down Avenue

4.9

180.93

0.132

14.776

79, Long Down Avenue

3.8

179.20

0.113

11.349

81, Long Down Avenue

4.9

150.85

0.123

12.319

83, Long Down Avenue

5.4

128.93

0.264

11.603

Address

As (m2)

n (ac/hr)

Cv (W/K)

2, Home Leas Close

169.35

0.600

33.870

4, Home Leas Close

85.47

0.600

17.095

6, Home Leas Close

85.47

0.600

17.095

8, Home Leas Close

169.35

0.600

33.870

18, Home Leas Close

162.65

0.600

32.529

20, Home Leas Close

73.49

0.600

14.698

22, Home Leas Close

73.49

0.600

14.698

24, Home Leas Close

139.72

0.600

27.944

75, Long Down Avenue

180.93

0.600

36.185

77, Long Down Avenue

180.93

0.600

36.185

79, Long Down Avenue

179.20

0.600

35.840

81, Long Down Avenue

150.85

0.600

30.170

83, Long Down Avenue

128.93

0.600

25.785

Revised Calculation

67

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Table D5 The Coefficient of Building Heat Loss (Cb) Dwelling Address

Cb (W/K)

2, Home Leas Close

126.35

4, Home Leas Close

73.37

6, Home Leas Close

73.37

8, Home Leas Close

126.35

18, Home Leas Close

123.13

20, Home Leas Close

66.87

22, Home Leas Close

66.87

24, Home Leas Close

115.23

75, Long Down Avenue

166.73

77, Long Down Avenue

162.73

79, Long Down Avenue

132.64

81, Long Down Avenue

115.06

83, Long Down Avenue

98.88 1447.569

Table D6 Heating Degree Days Month

HDD

January

312

February

286

March

253

April

189

October

129

November

217

December

285

Total

1671

Table D7 Annual Energy Demand QH-annual (MWh) 58.05

68

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

A PPENDIX E DISTRICT HEATING SYSTEM ENERGY EFFICIENCY SPREADSHEET N.B. an electronic copy of the spreadsheet is available on the CD

Table E1 Boiler Setup Heat Supply

LF

B1

DHW

0.31

B2

Space Heating

0.55

B3

Space Heating

0.14

Boiler

Table E2 Combined Boiler Efficiency LFB1

0.31

ƞB1-se

0.85

LFB2

0.55

ƞB2-se

0.85

LFB3

0.14

ƞB3-se

0.91

ƞs-se

0.86

ƞs-se (%)

86

Table E3 Accumulator Heat Loss Heat loss Rate (kWh) Volume (litres)

0.0152 110

Days

365

Hours

8760

QA-annual (MWh)

0.61028

69

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Table E4 LTDH Primary Network Heat Loss U11 (W/mK)

0.2517

U12 (W/mK)

0.0784

T1 (K)

333

T2 (K)

313

Tg (K)

284

L (m)

218

Q (W/m) QLTDH-annual (W) QLTDH-annual (MWh)

13.52 2946.79 25.81

Table E5 LTDH Distribution Network Efficiency Qsys (MWh)

110.69

Qdwellings (MWh)

84.27

ƞLTDH-D ƞLTDH-D (%)

0.7613 76

Table E6 LTDH Overall System Effiency ƞs-se

0.8584

ƞLTDH-D

0.7613

ƞLTDH-tot

0.6535

ƞLTDH-tot %

65

70

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Table E7 MTDH Primary Network Heat Loss U11 (W/mK)

0.2517

U12 (W/mK)

0.0784

T1 (K)

383

T2 (K)

353

Tg (K)

284

L (m)

218

Q (W/m) QMTDH-annual (W) QMTDH-annual (MWh)

29.11 6346.94 55.60

Table E8 MTDH Distribution Network Efficiency Qsys (MWh) Qdwellings (MWh) ƞMTDH-D ƞMTDH-D (%)

140.48 84.27 0.5999 60

Table E9 MTDH Overall System Efficiency ƞs-se

0.8584

ƞMTDH-D

0.5999

ƞMTDH-tot

0.5149

ƞMTDH-tot %

51

71

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

A PPENDIX F DISTRICT HEATING SYSTEM CARBON EMISSIONS SPREADSHEET N.B. an electronic copy of the spreadsheet is available on the CD

Table F1 LTDH Annual Energy Delivered by Fuel Fuel

LF

QSYS (MWh)

ƞ

QIN (MWh)

B1

Wood pellets

0.31

34.3139

0.85

40.37

B2

Wood pellets

0.55

60.8795

0.85

71.62

B3

Gas

0.14

15.4966

0.91

17.03

Boiler

Table F2 LTDH Lifecycle Emissions Fuel Emissions (kgCO2eq/MWh)

Annual Emissions (kgCO2eq)

Wood pellets

20.57

2303.68

Gas

225.54

3840.77

Fuel

Table F3 MTDH Annual Energy Delivered by Fuel Fuel

LF

ESYS (MWh)

ƞ

EIN (MWh)

B1

Wood pellets

0.31

43.5488

0.85

51.23

B2

Wood pellets

0.55

77.264

0.85

90.90

B3

Gas

0.14

19.6672

0.91

21.61

Boiler

Table F4 MTDH Lifecycle Emissions Fuel Emissions (kgCO2eq/MWh)

Annual Emissions (kgCO2eq)

Wood pellets

20.57

2923.67

Gas

225.54

4874.44

Fuel

72

An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Table F5 DH Pumping Emissions Pressure Drop TPL (Pa/m)

L (m)

∆P (Pa)

100

218

21800

∆P (Pa)

λ

L (m)

ρ (kg/m3)

ø (m)

v (m/s)

21800

0.16

218

1000

0.08

0.316228

A (m2)

v (m/s)

ƞm

ƞp

Qe (W)

Qe (kWh)

0.8

0.5

173

1517.75

Flow Velocity

Electrical Energy ∆P (Pa) 21800

0.005026548 0.316227766

Carbon Emissions Grid Electricity Emissions (kgCO2eq/kWh) 0.44548

Annual Emissions (kgCO2eq) 676.13

Table F6 LTDH Total Emissions (kgCO2eq) 6820.58

Table F7 MTDH Total Emissions (kgCO2eq) 8474.24

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A PPENDIX G D O M E S T I C C O N D E N S I N G B O I L E R S C A R B O N E M I S S I O N S S PR E A D S H E E T N.B. an electronic copy of the spreadsheet is available on the CD Table G1 Annual Energy Delivered by Fuel Boiler Gas Combi Boiler

QSYS (MWh)

Æ&#x17E;

QIN (MWh)

0.91

84.27

92.60

Fuel

QIN (MWh)

Fuel Emissions (kgCO2eq/MWh)

Annual Emissions (kgCO2eq)

Gas

92.60

225.54

20886

Table G2 Lifecycle Emissions

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

A PPENDIX H SEDBUK B O I L E R E F F I C I E N C Y T A B L E Available at: http://www.boilers.org.uk/cgi-local/result1.cgi Table H1

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

A PPENDIX I SAP E N E R G Y P E R F O R M A N C E C E R T I F I C A T E S N.B. the pages included are limited to those used. The full certificates are available at: https://www.epcregister.com/reportSearchAddressByPostcode.html

Figure I1

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I2

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I3

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I4

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I5

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I6

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I7

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I8

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I9

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I10

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I11

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I12

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I13

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I14

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I15

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I16

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I17

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I18

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I19

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I20

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I21

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I22

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I23

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I24

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I25

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

Figure I26

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An Investigation into the Integration of Low Carbon District Heating in Low-density Areas

A PPENDIX J SITE VISIT PHOTOS

Figure J1 18-22 Home Leas Close

Figure J2 2-8 Home Leas Close

Figure J3 75-83 Longdown Avenue

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