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Work Stream 3 – Phase 2 Assessing the Impact of Low Carbon Technologies on Great Britain’s Power Distribution Network 1. Development and Considerations 12 th November 2012

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Work Stream 3 – Phase 2

Assessing the Impact of Low Carbon

Technologies on Great Britain’s

Power Distribution Network

1. Development and Considerations

12th November 2012

WS3-Ph2: A consortium-led approach on behalf of the GB Smart Grid Forum (Work Stream 3)

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Project Partners..

Working with..

Why WS3 initiated Phase 2

• GB network uncertainties

• The case for using innovative solutions to address the new challenges

• Irregular country-wide spread

• Different technologies pose different challenges to different networks

• Significant increase in number of potential solutions

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What best to use, and When to use it… ? WS3 - Phase 1 report

Two Smart Grid Forum workstreams focus on the evaluation of smart grids

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WS1: Assumptions and scenarios

Aims to establish the assumptions and scenarios necessary for the network companies to produce business plans that are consistent with DECC’s low carbon transition. Led by DECC.

WS1

WS2: Evaluation Framework

WS3: Developing Networks for Low Carbon

WS4: Closing Doors

WS5: Ways of Working

WS6: Commercial and Regulatory

Aims to develop an evaluation framework that can assess, at high level, alternative network development options. Led by Ofgem.

Aims to assess the network impacts of the assumptions and scenarios from WS1. Led by the DNOs.

Aims to identify credible risks to the development of smart grids as a consequence of forthcoming policy decisions which might fail to take full account of the necessary enablers for smart grid development.

Looks at how the Forum can best pursue its objectives and communicate effectively with stakeholders.

Brings together stakeholders to investigate the commercial and regulatory challenges of implementing the smart grid solutions.

WS3 builds on the framework developed in WS2

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WS2: Evaluation Framework

WS3: Developing Networks for Low Carbon

• Real options-based evaluation framework.

• Flexible and transparent model, available from Ofgem

• More network types and network technologies.

• DNO-specific modelling

• Real-options elements not included

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WS3 - Schematic Overview of Modelling

1. Networks (today)

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Not all networks are equal: The headroom of the networks differ throughout GB

Factors include:

Build specification

Customer type and customer density

Local geography

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There is no such thing as an ‘average’ network

• 6 x EHV • 7 x HV • 19 x LV

To increase the numbers and types of networks to make the model more representative of the GB system

Network Geographical Area

Customer Density

Network Construction

Topology

EHV 1 Urban High Underground Radial

EHV 2 Urban High Underground Meshed

EHV 3 Suburban Medium Mixed Radial

EHV 4 Suburban Medium Mixed Meshed

EHV 5 Rural Low Overhead Radial

EHV 6 Rural Low Mixed Radial

Network Geographical Area

Customer Density

Network Construction

Topology

HV 1 Urban High Underground Radial

HV 2 Urban High Underground Meshed

HV 3 Suburban Medium Underground Radial

HV 4 Suburban Medium Underground Meshed

HV 5 Suburban Medium Mixed Radial

HV 6 Rural Low Overhead Radial

HV 7 Rural Low Mixed Radial

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There is no such thing as an ‘average’ customer

CONSUMPTION PROFILE

ENVIRONMENT •Temperature •Solar Flux

BUILDING •Size •Heat loss •Glazing

APPLIANCES/EQUIPMENT •Power Rating

• On/Standby •Efficiency •Programme/Cycle

USERS •Number •Activity Profile •Energy Efficiency Attitude

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Domestic Heat Pump

Point load demand profiles differ according to in-home technology and geography

• Winter Peak, Winter & Summer Average • Weekday • Temperature Sensitivity • Appliance Type & Efficiency • Validation

Standard Tariff Domestic Domestic E7 Storage Heaters

Temperature Sensitivity

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Hence, the mix of customers along a feeder has a significant impact on its overall demand profile

LV feeder demand profile

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2. Scenarios

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An uncertain world: Different mixes of large-scale generation will place different challenges on the conventional network design and operation

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CCGT Coal CCGT CCS

Coal CCS Nuclear Onshore wind

Offshore wind Other renewable

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Installed capacity: medium decarbonisation scenario

Installed capacity: low decarbonisation scenario

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Source: Redpoint analysis for the ENA based on National Grid ‘Slow Progress’ scenario to 2030 and extrapolated to 2050

Source: Redpoint analysis for the ENA, based on National Grid ‘Gone Green’ scenario

With disruptive technologies having scope to create significant challenge to LV networks

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Heat Pumps

Photovoltaic

Electric Vehicles Source: SGF, WS1, DECC, Dec 2011

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PV uptake example

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MicroCHP pilot

Wind

Photovoltaics

Hydro

Anaerobic digestion

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PV = 0MW

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PV = 600+ MW

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There are clear differences between the technologies adopted in different parts of the UK

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Regional breakdown of installed capacity by

technology (MW)

Source: FiTs Annual Review 2010-11, Ofgem E-Serve, 2012

Regional breakdown of current wind projects

Regionalisation within the model

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• Regional variation in terms of housing stock and temperature allowances for different building loads

• “Attractiveness” of various LCTs differs across regions – PV can be selected to be more attractive in South and East

England than Scotland if desired, for example

Region 1 Scotland

Region 2

North West North East Yorkshire and the Humber West Midlands East Midlands

Region 3 Wales (incl Merseyside and Cheshire)

Region 4 South West South East East of England

Region 5 London

From GB to regional uptakes - examples

From national to regional uptakes

• Regionalisation performed for all technologies;

• Distinction between rural / suburban and urban areas

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The ‘new’ low carbon technologies produce very different demand profiles

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Mapping of technology uptakes by region and area character to the LV feeders • Multi-step approach based on DNO data, DECC projections, National Statistics and EE uptake models

DNO data

House Condition Survey & Rateable Value data

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PV installations have clustered in different parts of GB

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Percentage of network

Percentage of low-carbon technology installations

1% 9%

4% 17%

25% 48%

30% 22%

40% 5%

Number of domestic PV installations per 10,000 households by Local Authority, end of December 2011

Source: www.azure.eco.co.uk

Source: DECC

Clustering Levels

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% of Network

3. Solutions

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Fixing the problem: Selecting solutions with an increasing solution set

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Conventional Solutions Conventional

Solutions

‘Business-As-Usual’ Investment

‘Smart’ Investment

Smart Solutions

Solution Enablers

“Lumpy” - high upfront costs, minimal running costs, long lives, produce step change in headroom

“Flexible” - lower upfront costs, some running costs, shorter lifetimes, smaller impact on headroom

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Two methods to release headroom

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Demand constant Increase capacity

Increase headroom e.g. RTTR

Reduce demand Capacity constant Increase headroom

e.g. DSR

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Outlining the solution options, and making the link to LCN Fund projects

• Refined ‘conventional’ solution set • Expanded ‘smart’ solution set • Agreed a common language • Populated an initial digest of

solutions

Solution Category Count Representative 21 Variants 74 Enablers 108

Total: 203

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4. The Model

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Can consider up to four scenarios (present day to 2050)

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Scenario 1: Domestic decarbonisation to meet carbon budgets

Scenario 2: Domestic decarbonisation to meet carbon budgets, with less DSR

Scenario 3: Less domestic decarbonisation (purchase of credits)

● Medium transport electrification (WS1)

● High heat electrification (WS1)

● “Gone Green” generation mix (National Grid )

● Medium levels of customer engagement with DSR

● Medium transport electrification (WS1)

● High heat electrification (WS1)

● “Gone Green” generation mix (National Grid )

● Low levels of customer engagement with DSR

● Low transport electrification (WS1)

● Low heat electrification (WS1)

● “Slow Progression” generation mix (National Grid )

● Medium levels of customer engagement with DSR

As used for WS2

Scenario 0: High domestic decarbonisation

● High transport electrification (WS1)

● High heat electrification (WS1)

● “Gone Green” generation mix (National Grid )

● Medium levels of customer engagement with DSR

New for WS3

Three distribution network investment strategies

● Roll out of smart and conventional technologies, and associated control and communications architecture when required

Incremental smart grid investment

strategy

● Upfront investment in control and communications architecture

● Investment in smart and conventional technologies when required

Top-down smart grid investment

strategy

Key attributes

● High early investment ● Shorter asset lives

● Investments occur only when required ● Shorter asset lives

Description

The strategies determine the set of technologies available for deployment in each scenario

Under each scenario, technologies from each strategy will be deployed to fully accommodate supply and demand

Slide extracted from the SGF WS2 model 30

● Roll out of conventional technologies only, when required

Conventional investment

strategy

● Solutions tend to be more ‘lumpy’ (capital-intense and release more headroom)

● Longer asset lives

Solutions deployed on the basis of…

..headroom breaches:

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Low Volts Lower Statutory limits

High Volts Upper Statutory limits

High Thermal limits Thermal limits of plant and circuits

High Fault Level Design fault level limits

Power quality issues The model could be expanded to include PQ against EU standards

Two Models: Two different purposes

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Two models have been developed under this project, to reflect the different levels of granularity between GB and a DNO licence

*Transform™ is the supported framework developed by EA Technology to quantify the results described in the WS3-Ph2 report. It is available from EA Technology on a commercial basis; all funding Network Operators, DECC and Ofgem have a licence to use the software for future analysis

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WS3 - Schematic Overview of Modelling

Further Questions

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Dave A Roberts Future Networks Director EA Technology Ltd

e. [email protected] t. 0151 347 2318

Appendix

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Building on the foundations laid in WS2

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Network Element WS2 WS3

Network Topologies 3 (1x EHV, 1x HV, 3x LV) 100 most likely combinations

Clustering Groups 5 10

Daily load profiles 3 (summer mean, winter mean, winter peak) 3 (as per WS2 model)

Headroom spread 1 (average only) 3 (symmetrical : low/average/high)

LCT Technology Types 17 17 No. of solutions and variants c20 c200

CBA Wrapper WS2 WS3

Processed scenarios 3 (Low, Medium 1, Medium 2)

4* (Low, Medium 1, Medium 2,

High)

Investment strategies 3

(Incremental, Top-down, Counterfactual)

3 (Incremental, Top-down,

Counterfactual)

Real options analysis Yes No

*Model will be configured to calculate one scenario and three investment strategies at a time

Scope of model

WS 2 established a framework for the evaluation of smart grids

Networks Generation Demand

Real options CBA 2012-2050

1 Value drivers and scenarios 2

EVs

HPs

PV

Wind

Efficiency

Scenario 1 Scenario 2 Scenario 3

Investment strategies 4 Assessment of option value 5

Top-down smart grid

Incremental smart grid

Business as usual

Different lifetimes, lead

times and levels of sunk

costs

Decision 1: Before state of world is

known

Decision 2: Options

constrained by previous

decision Information

Time

Representative smart grid technologies 3

Electric Energy Storage

Dynamic Thermal Ratings

Enhanced Automatic Voltage Control

DSR Dynamic network reconfig.

Placeholders

WS2 found a significant net benefit associated with smart investments

• The net benefits in the smart strategies are almost entirely driven by distribution network investment savings

• The roll out of low-carbon technologies from the 2020s is the most important driver of net benefits

• The results are sensitive to assumptions on clustering

• Differences between strategies between up to 2023 are very small – the net benefits of smart strategies are delivered in the 2020s and beyond

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Detailed Network Model Schematic

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