Buildings and Storage

Natalia Wisniewska Joseph Juan

Akash GoenkaLara TarasewiczMauricio RiverosMatteo Silvestri

Introduction

2

3

Assessing policy measures for energy

efficiency in UK homes

Natalia Wisniewska

Problem

4

How to boost energy efficiency in domestic

households?

Which policy could achieve that?

5

Variable Council Tax

Variable Stamp Duty

Help to Heat Framework

Green Mortgage

Demand ReductionObligation

FiT for energy efficiency

1

2

4

3

5

6

Challenge

6

How to assess the potential of policy prior to its launch?

Policy assessment tool

7

Policy proposals

Solution

Socio-technicalsystems analysis

Economic appraisal

Rank

Assess

ank

A

Solution: what will work?

8

Political vision

Customer demand

Supply chain

Carrot-and-stick approach

Variable Council Tax

Green Mortgage

Variable Stamp Duty

9

POSTER 18

My sincere thanks to my supervisors Chris Mazur, Jeff Hardy and James Luger, but also Simon McGreehin,

my interviewees and everyone else who supported this work.

10

Solar-Combined Cooling, Heating and Power (S-CCHP)

A Techno-economic Assessment

Joseph Juan

Polygeneration Energy System

11

Focus on combining cooling and power part, called as solar combined cooling and

power (S-CCP) system:

Power unit

Cooler unit

Solar Thermal Collector

Aim: To assess the technical and economic feasibility for a typical

house in London

System Performanc

e

Control strategie

s

System Performance

12

System performan

ce

The amount of electricity

saving

The amount of electricity

demand coverage

System Combinations

13

Direct flow collector

Heat pipe collector

Evacuated flat collector

Organic Rankine Cycle (ORC)

Diffusion Absorption Refrigerator (DAR)

Single effect absorption refrigerator

Double effect absorption refrigerator

Prioritising cooling

Prioritising electricity

Which combinations give higher electricity saving?

Results: Technical Assessment

14

Direct flow collector

Heat pipe collector2

1

3

Evacuated flat collector

Electricity saving (kWeh/ year)

Diffusion Absorption Refrigerator (DAR)

Single effect absorption2

1

3

Double effect absorption

Electricity saving (kWeh/ year)

1

2 Prioritising cooling

Prioritising electricity

Electricity saving (kWeh/ year) However, the systems only cover 5 – 12% annual electricity demand because of thelow solar resource inLondon

Results: Economic Assessment

15

Net present value of S-CCP system after 20 years investment period

Conclusions

16

• The considered solar combined cooling and power (S-CCP) system is not feasible to provide energy for a typical house in London

• However, installing the system in sunnier location or applying hybrid system can be considered further

17

POSTER 16

My sincere thanks to Dr. Christos Markides, Dr. Antonio Marco Pantaleo, Dr. Robert Edwards and James Freeman for their valuable helps in this project.

18

A Design Environment to Enable Smart

Buildings

Akash Goenka

Setting the scene

19

• Can the enormity of energy consumption by buildings be ignored?

• Why do buildings underperform (energy-wise)?

HVAC

Others

Equipment

Lighting

Turn up the heat!

20

• Takes note and learnsyour schedule• 7 am: A warm welcome• 8 am: Off to work

• Slashes bills and energyuse

• This is smart!

Aim

21

What is the impact of controls on HVAC energyconsumption and indoor comfort?

The Faculty Building model

22

Trench heaters Chilled Beams

A 3D Reconstruction

23

Simulation Results

24

%Saving on energy consumption

%Compromise on thermal comfort

• Greater thermal comfort Greater energy consumption

25

POSTER 15

My sincere thanks to my supervisors, Dr Bianca Howard,

Dr Salvador Acha and Prof John Polak.

26

An Olympian Challenge:

How do we address retrofitting commercial buildings?

Lara Tarasewicz

Focus: Soft Barriers

27

Commercial Buildings

Energy Efficient

Overcome soft barriers to retrofitting

Why do soft barriers matter?

28

So why aren’t all commercial buildings energy efficient yet?

We have the technology…

E.g. Insulation, LED lighting

Novel Methodology

29 29

INP UTS S O C IO -TE C HNIC AL S Y S TE MS

E C O NO MIC & C arbon

General Case Case Study

30

38 barriers1. S plit Incentives

2. Management

3. B us ines s cas e

17 Solutions, e.g.Individual R es pons ible

D emons tration E xample

F inance Team L ead

30Key Findings

G eneral C as e

Greenwich Leisure Limited

Key Findings

31 31

Motivated individuals

Methodology:

Toolkit of B arriers and S olutions

POSITIVES

S S D support

NEEDED

P ayback > 3 years

Assurance on energy savings

G overnment policy

G ood communication

32

POSTER 17

My sincere thanks to my supervisors Dr Christoph Mazur,

Dr Koen van Dam and Pelumi Solaru.

33

Carbon Arbitrage with Electrical

Energy Storage

Mauricio Riveros

Arbitrage

34

Time

£/kWhh

Arbitrage

35

Time

£/kWh

Charge Discharge

£

h

Arbitrage

36

Time

Charge Discharge

tCO2/kWhCO2

CO2

Methodology

37

Emission INSTALATION

Emissions OPERATION

Total Emissions

Optimization Problem

Capacity

CO2Capacity

INSTALATION OPERATION

Case Study

38

Li-ion

FB

Technology

Generation Mix Distributed Generation

50% Wind

80% Nuclear

DG-1

DG-2

Mix 2015

CHP

Results: Emissions Savings

39

Li-ion

1,2041,552

171

3,444

7,924

MI X 2015 WI N D 50% N UC LEA R 80% D G_1 D G_2

90 160 37 90 90

Capacity(MWh)

Emission Savings(tCO2)

111666000 33377 999000 9990009900

CHP

Results: Is it profitable?

40

Price forecasted for the UK more optimistic case in 2030

17 13 648

110

0

100

200

300

400

500

600

700

800

Mix 2015 Wind 50% Nuclear 80% DG_1 DG_2

£/kW

h117

£/tCO2

Li-ion

Value Cost

CO2

CHP

Results: Is it profitable?

41

117£/tCO2

Li-ion

Value Cost

230£/tCO2CO2

CHP

30 23 11

87

199

0

100

200

300

400

500

600

700

800

Mix 2015 Wind 50% Nuclear 80% DG_1 DG_2

£/kW

h

Conclusions

42

•A significant capacity is needed to maximis e the s avings in all the s cenarios s tudied.

• Savings are mainly defined by the carbon intensity of the grid more than the demand patterns .

•T he emissions reduction is not high enough to pay the inves tment at the current carbon price and inves tment cos ts .

•T hat s ugges t the need to mix the Carbon Arbitrage with another application to increas e the value.

43

POSTER 19

My sincere thanks to my supervisors Dr Miao Guo, Dr Koen Van Dam, Professor Nigel Brandon and Gonzalo Bustos.

44

The value of energy storage for industrial

sites in the UK

Matteo Silvestri

Background & Research Question

45

Battery cost vs. benefits Electricity Price

£/kW

h Capex

Revenues

Savings on electricitybill

Congestion reliefservice to DNO

CO2 savings

0

20

40

60

80

100

2000 2005 2010 2015 2020 2025

Transmission tariffsNorth East region

Historical data

£/kW

Forecastdata

Can a battery system generate net savings on the electricity bills?

Ancillaryservices to National Grid

Savings on electricitybill

?

Electricity Bill: Saving Opportunities

46

0

2

4

6

8

10

12

14

p/kW

h

48 Half hours

Distribution tariffElectricity spot price

Intra-day Arbitrage £ =

Regionaltariff

Power demandduring the 3

annual half hours of highest

national demand

Transmission Charge

£Commodity

price

Distributioncharge

Transmissioncharge

Case Study

47

Li-ion

FB

NaS

Electricity PricingScenarios

BatteryTechnologies

IndustrialSite

Different combination of trends for:

Transmission tariffDistribution tariffVolatility of electricity price

Barnard CastleDurham County

TIME

£

Results

48

FB

Li-ion

NaSLi-ion: annual NPV in the range of 1-2% of

the electricity billexpenditure acrossvarious scenarios

Net Savings on ElectricityBill

Optimal battery size: energy/power

capacities ratio ≈ 0.5 hours

Share of savings for Li-

ion and FB

0

2%

1%

Sensitivity Analysis

49

Transmission ChargesRegional Variation

Effect on Net Present

Value

< 50 £/kW

50-55 £/kW

55-60 £/kW

>60 £/kW

Northern

Southern

AverageTransmissiontariffs forecast(2016-20)

-200 -100 0 100 200 300 400 500

FB

Li-ion

NPV (£ x 1000)

Northern

NaS*

*

*

(*) Technologies not to be comparedeach other due to different lifetimes

Conclusions

50

2 1 3

Li-ionFB

NaS

There is a business case for properly designed and operated battery systems considering just the savings on

electricity bills

ionionion

Li-ion

FBNaSNaS

51

POSTER 20

My sincere thanks to my supervisorsProfessor Nigel Brandon and Mr. Adrien

Lebrun.

MatteoNatalia Joseph Akash Lara Mauricio

Thank you!

18 16 15 17 19 20

53

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References

Question: <div>Icons made by <a href="http://www.freepik.com" title="Freepik">Freepik</a> from <a href="http://www.flaticon.com" title="Flaticon">www.flaticon.com</a> is licensed by <a href="http://creativecommons.org/licenses/by/3.0/" title="Creative Commons BY 3.0" target="_blank">CC 3.0 BY</a></div>

Model IT50 ROT ORC Waste Heat Turbine AC Generator 50hz 60hz Organic Rankine Cycle System. (2016). Available from: http://www.infinityturbine.com/it50.html [Accessed 14/09/2016].

Baxi . (2008) Evacuated Tube Collector Installation Guide.

54

References

SPF Institute for Solar Technology. (2016) SPF Online Collector Catalogue. Available from: http://www.spf.ch/Collectors.111.0.html?&L=6 [Accessed 17/08/2016].

TVP Solar Product Datasheet. (2016). Available from: http://www.tvpsolar.com/files/pagine/1464011780_MT-Power%20Datasheet%20(v4.2x)(ver5).pdf [Accessed 14/09/2016].

Smiley Sun: <div>Icons made by <a href="http://www.flaticon.com/authors/roundicons" title="Roundicons">Roundicons</a> from <a href="http://www.flaticon.com" title="Flaticon">www.flaticon.com</a> is licensed by <a href="http://creativecommons.org/licenses/by/3.0/" title="Creative Commons BY 3.0" target="_blank">CC 3.0 BY</a></div>

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55

Council tax Stamp Duty FiT DRO Green Mortgage Help to HeatCustomer issues STS approach weighting

boosts customer demand 4 4 2 2 4 3 90%reduces costs of retrofit per household 3 2 3 3 5 5 73%generates reasonable payback periods for customers 2 1 3 3 4 4 60%reduces customer 'hassle factor' 3 3 3 4 3 4 90%reflects retrofit uptake in property capital value 5 5 2 2 4 3 60%causes less risk of 'rebound effect' 2 2 4 4 2 2 80%ensures trust among customers 4 4 3 2 3 2 70%

Political/Economic issuesprioritises fuel poor households 3 4 1 1 1 5 100%cost-neutral to Treasury 2 2 1 3 4 1 85%compatible with other policies 4 4 3 3 4 3 100%introduces complemetary minimum standards/regulations 5 4 2 2 4 2 60%CO2 abatement potential 4 3 2 2 3 2 100%

Supply chain issuesdevelops expertise of the supply chain 4 4 2 2 4 3 60%mobilizes the SWI market 2 2 2 2 3 3 100%improves information base of existing building stock 3 3 2 2 3 3 69%improves quality of home energy surveys 2 2 2 2 2 2 66%ensures coordination of stakeholders within the supply chain 4 4 2 2 4 3 60%compliance with business models of delivery organisations 5 5 2 2 4 3 84%ensures resident engagement initiatives 4 2 2 2 2 4 80%

50 47 33 35 48 45

1 3 6 5 2 4

Total

Ranking

56

System Collector types

Total Annual Electrical

Output (kWhe)

Total Annual Cooling Output

(kWhc)

Electrical demand coverage (not

including refrigerator)

Cooling demand coverage

Electrical demand coverage

Solar collector +

ORC + DAR using control

strategy-1

Direct flow collector 122.8 94.3 3.3% 9.8% 4.6%

Heat pipe collector 172.7 121 4.7% 12.6% 6.3%

Evacuated flat collector 224.2 125.9 6.1% 13.1% 7.8%

Solar collector +

ORC + DAR using control

strategy-2

Direct flow collector 128.6 127.1 3.5% 13.3% 5.2%

Heat pipe collector 198.3 140.4 5.4% 14.7% 7.3%

Evacuated flat collector 269.7 146.2 7.3% 15.3% 9.3%

Solar collector +

ORC + DAR using control

strategy-3

Direct flow collector 202.5 9.1 5.5% 1% 5.6%

Heat pipe collector 256.8 32.7 7% 3.4% 7.4%

Evacuated flat collector 330.6 37.8 9% 3.9% 9.5%

Solar collector +

ORC + Single effect

absorption refrigerator

Direct flow collector 157.9 97.4 4.3% 20.3% 7.1%

Heat pipe collector 207.4 116.8 5.6% 24.4% 9%

Evacuated flat collector 277.2 139.3 7.5% 29.1% 11.4%

Solar collector +

ORC + Double effect

absorption refrigerator

Direct flow collector 162.3 98 4.4% 20.5% 7.4%

Heat pipe collector 211.7 119.6 5.8% 25% 9.3%

Evacuated flat collector 278.9 151.2 7.6% 31.6% 11.8%