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Role of innovative and smart solutions in future urban energy systems Marko Aunedi & Goran Strbac Imperial College London 28 November 2017


Background •  Context: •  Decarbonisation of energy supply (RES, electrification of heat and transport) •  Increased requirements for flexibility to enable cost-effective integration of low-carbon energy •  Innovation and cost reduction in smart flexible technologies (e.g. energy storage)

•  Key research topics: •  Impact of decarbonisation on urban energy infrastructure •  Use of innovative and smart technologies in delivering more cost-efficient decarbonisation •  Balancing local and national energy objectives •  Implications of local sources on resilience of energy supply in cities

2


Local vs. national benefits of flexibility – whole-system paradigm • 

Whole-system benefits of flexibility manifested across: •  Time: from years ahead (planning) to secondsahead (real-time operation) •  Space: from local to national & international infrastructure

• 

•  • 

System value of flexibility could be significant:

Split benefits occur across various segments of power system Transmission- or distribution-centric approaches miss out on part of the value

•  £8bn/yr in 2030 (NIC) •  £17-40bn NPV by 2050 (BEIS)

National level services

Local level services

3


Relevant projects •  Low Carbon London (LCNF innovation, £28.3m, 2011-2014) •  Cutting-edge trials and demonstrations of innovative smart solutions using London’s network as test bed •  First UK dynamic Time-of-Use tariff trial •  Large-scale trials for EVs, heat pumps and industrial and commercial DSR •  Key question: how to operate and design future smart urban distribution networks?

•  Sharing Cities (Horizon 2020, ongoing) •  Taking advantage of digital technologies in cities to improve urban mobility, increase energy efficiency of buildings and reduce carbon emissions •  Focus on 3 strategic locations: London, Lisbon and Milan

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LCL EV trials: characterising residential and commercial EV charging demand Residential

Charging power  (kW)

0.4

0.38

Weekday

Weekend

Total

Thursday

Saturday

Sunday

6

12 Hour

0.33 0.30

0.3

0.2

0.1

0 0

18

Commercial 1-phase 0.3

Commercial 3-phase

Weekday

Weekend

Total

Tuesday

Saturday

Sunday

Weekday Tuesday Sunday

3

0.24

0.2

0.18 0.15

Weekend Friday

Total Saturday 2.37

Charging power  (kW)

Charging power  (kW)

0.25

24

0.13

0.1 0.05

2

1.99

1.81

1.48 1

0.03 0

0 0

6

12 Hour

18

24

0

6

12 Hour

18

24

5


Vehicle usage patterns and potential for smart charging • 

Average trip distance: ~6.5 km • 

•  • 

95% of trips were below 25 km for residential and below 20 km for commercial users

User mostly charged their batteries to the full Potential for applying innovative charging schemes (incl. V2G) to support local grid and wider system

100

80

EV demand Non-­‐controlled Controlled Baseline

60

Total demand  (kW)

End SoC  (%)

40

40

Residential EVs 20

30

40.4

30.0

20

10

0

0 0

20

40

60 Start SoC  (%)

80

100

0

6

12 Hour

18

24

6


Electrification of London taxies and buses: Impact on the London electricity infrastructure

7


First UK dynamic Time of Use tariff trial

High price: 67.20 pence/kWh Base price: 11.76 pence/kWh Low price: 3.99 pence/kWh dToU: 922 households non-dToU: 3,437 households

8


LCL Dynamic Time of Use tariff trial findings Demand-supply balancing challenge: •  Supply following (SF) trials: increasing or decreasing demand at various times of day to reflect variability of renewable generation.

Degradation in asset utilisation challenge •  Constraint management (CM) trials: reducing peak loads – to defer or reduce distribution network reinforcement costs.

Full year mean Demand Response by settlement block

Potential conflict between network and system management 9


Industrial and commercial DSR trials

Hotel Demand Response Event 160 Data logger readings Baseline fit

140

120

Chiller load (kW)

100

80

60

40

20

0 10am

11am

12pm

1pm

2pm

3pm

4pm

Time of day

10


Impact of weather conditions on peak demand contribution from HPs E.g. average temperature of -4⁰C and a penetration level of 20% of household owning heat pumps increases peak daily load by 72% above baseline

Source: LCL Report B4*

*M. Bilton, N. E. Chike, M. Woolf, P. Djapic, M. Wilcox, G. Strbac, “Impact of low voltage – connected low carbon technologies on network utilisation”, Report B4 for the “Low Carbon London” LCNF project: Imperial College London, 2014.

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Impact of energy efficiency on daily profiles

500KVA

Winter weekday  demand  profiles  for  all  interven5ons     Scenario   Cold  efficiency   Wet  efficiency   CFL  light  efficiency   LED  light  efficiency   Efficiency  total  

Energy reduction   5.5%   1.9%   4.8%   3.8%   16.0%  

Peak reduction     2.9%   1.9%   8.6%   6.0%   18.8%  

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Benefits of combined mitigation measures in London distribution grid •  Measures include: •  •  •  •  • 

Smart EV charging Smart HP operation I&C DSR dToU tariffs Energy Efficiency

•  Potential for massive savings over the next decades

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Resilience of urban energy supply: Can you trust smart when it comes to security? Redundancy & robustness Same Risk

D+ΔD

~

DSR

D+ΔD

•  Comprehensive risk assessment of smart solutions •  Conflicts between local and national objectives if the same smart asset provides reliability both locally and nationally •  Use of local resources to provide flexibility and resilience: storage, DSR, CHPs, backup generators, microgrids...

independent sites required

20

overcontracting required

15

10 0.9

5

0.99 0

0.999 0

5

10

15

20

desired response (contract units)

14


Non-­‐ smart EVs HPs dToU I&C DSR

60

50

40

30

20

10

0

Fully smart

EV HP dToU I&C DSR

Bal. +  Freq.

I&C DSR

Balancing

100%

50%

dToU

25%

75%

HP

50%

EV

25%

Fully smart

Smart/FR

80

Smart

90

Smart/FR

100

Smart

110

Bal. +  Freq.

Balancing

100%

50%

25%

75%

50%

25%

Smart/FR

Smart

Smart/FR

Smart

Avoided emissions  through  DSR   (g/kWh)

Bal. +  Freq.

Balancing

100%

50%

25%

75%

50%

25%

Smart/FR

Smart

Smart/FR

Smart

System average  CO2 emissions  (g/kWh)

2030 GW 120

Avoided emissions  through  DSR   (g/kWh)

Bal. +  Freq.

I&C DSR

Balancing

100%

dToU

50%

25%

75%

HPs

50%

25%

Smart/FR

EVs

Smart

Non-­‐ smart

Smart/FR

Smart

System average  CO2 emissions  (g/kWh)

2050 HR

Average system emissions and carbon benefits of smart demand 200

150

100 50 0

Fully smart

200

150

100 50 0

Fully smart

15


Impact of smart heat-electricity coupling on low-carbon heat technologies •  Decoupled: •  Low uptake of DH schemes, hybrid HPs dominant •  Higher capacity of firm but more costly low-carbon generation (nuclear and CCS)

•  Integrated: •  Higher uptake of DH schemes in higher density (urban) areas •  Higher volume of variable RES (wind and PV) and CHP

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Future challenges and opportunities

•  Opportunities for innovation in deriving smart energy roadmaps for cities •  Understanding energy infrastructure resilience and security of supply of cities •  Need for whole system approach for assessing alternative pathways •  Capturing synergies and conflicts between local and national objectives 17


Role of innovative and smart solutions in future urban energy systems Marko Aunedi & Goran Strbac Imperial College London 28 November 2017

Profile for Ibex Earth

Imperial College London  

Dr Marko Aunedi from Imperial College London presented at Creating Sustainable Cities 2017, exploring the role of innovative and smart solut...

Imperial College London  

Dr Marko Aunedi from Imperial College London presented at Creating Sustainable Cities 2017, exploring the role of innovative and smart solut...

Profile for ibexearth
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