Headroom - Whole System Thinking

Objectives 

• Develop a methodology to calculate the whole system value of network headroom.
• Produce representative headroom archetypes that demonstrate where headroom provides value to the energy system.
• Quantitatively understand what parts of the network added headroom has the most significant financial benefit to the whole energy system. This will be discussed in terms of voltage level, types of connected generation, and types of connected demand.
• Understand the constituent parts of customer bills which are most impacted by added headroom, i.e. wholesale price savings, balancing market savings, carbon savings.
• Collated information to give values for £/MWh and CO2/MWh headroom whole system value, which will vary depending on archetype grouping.

Problem(s) 

The move towards increased use of the electricity vector will mean that whole electricity system [1] costs will have a higher dependency on distribution connected assets that can provide flexibility. As the rate of electrification increases, distribution network constraints are expected to have a higher impact on the optimisation of the costs, and carbon intensity of the whole electricity system.

Currently two models from the ENA, co-developed with Baringa, are used as part of operational decision-making on investment for network capacity. In their current form there is little consideration for the value of headroom on the distribution network.

• Common Evaluation Methodology (CEM): A methodology and MS Excel model to allow the GB Distribution Network Operators (DNOs) to evaluate the use of novel network management’s solutions, e.g. including Demand Flexibility, against conventional network solutions, e.g. reinforcement.
•  Whole Energy System CBA: A methodology and MS Excel model to reflect the costs and benefits of different interventions to a range of stakeholders, e.g. DNOs, TOs, ESO, Gas Distribution Networks (GDNs), Local Authorities and wider society.

It is expected that over time, distribution network headroom constraints will limit the extent to which demand side response can benefit the whole electricity system. An example might be where V2G services are blocked from providing benefit to wholesale markets due to headroom constraints on the LV or HV networks.

We want to address this challenge more effectively, but to do so we need to understand the value of distribution network headroom to the whole system. Understanding this value will allow us to drive targeted innovation and provide a metric to support investment decisions in Business as Usual.

[1] For the purposes of this report, the whole electricity system comprises wholesale electricity markets, transmission system constraint management, and distribution network constraint management, system balancing (the balancing mechanism and ESO ancillary services).

Method(s) 

To understand the benefit per unit of headroom, we will explore the difference between two scenarios - one where networks have sufficient headroom to allow distribution-connected assets to connect and dispatch freely, and one where there is a headroom shortfall that results in curtailed dispatch and - potentially - reduced or delayed connections.

• Consideration will be made of the voltage level and different constraint scenarios, including critical times of year when constraints are likely.
• We shall look across our network to identify illustrative instances (voltages, locations, network topologies, generation mixes) that we can study to understand the impact of headroom reduction, and to provide insights about how this varies across voltage levels.
• To quantify the benefit, the impact of headroom reduction on the capacity and dispatch behaviour of distribution-connected assets (generation, storage, demand) will be reflected as an input in PLEXOS and a Balancing Mechanism model, which will be run to model the impact on system prices and system carbon emissions.
• We shall review this benefit across two different time periods to be selected between today and 2035 that have different generation mixes and demand profiles.

The project consists of three stages with analysis from each stage increasing in detail and granularity.

Stage 1: Theoretical development of project and initial modelling while modelling the whole system as a single GB block.

Baringa will lead the work, drawing on data and insight from National Grid, and expertise from EA Technology.

Baringa 

• Lead the work, drawing on data and insight from NGED, and expertise from EA Technology.
• Key objectives are to define an approach to represent headroom reduction, and translate it into installed capacity and generation impacts, to assess the impact on prices and carbon emissions, and to understand the impact on Ancillary Service participation.
• Conduct two PLEXOS runs, with and without the headroom adjustment, to establish the order of magnitude of the headroom benefit to the whole system. Each asset class (e.g. solar) will be represented as a single GB block, with no distinction between T- or D- connected, or its location. Constraint availability factor will be applied to that block to represent the impact of network headroom informed by the modelling produced by EATL.
• Constraint information for each case study will input from the excel table produced by EATL.

EA Technology Ltd 

• Responsible for receiving asset, constraint and planning data from NGED.
• Update the GB transform model to include Wind Generation uptake and profiles, HV and EHV connected demand and generation, update seasons used in the analysis to cover more than just worst case. i.e. maximum demand (winter peak), typical winter, minimum demand (summer minimum), typical summer, solar peak, intermediate warm, intermediate cool.
• Review of ratings and topology for HV and EHV networks.
• Identify the volume of constrained LV generation or demand due to LV network constraints.
• Identify the volume of constrained LV and HV generation or demand due to HV network constraints.
• Identify the volume of constrained EHV generation due to EHV constraints.
• Provide outputs to Baringa in tabular form.

National Grid 

• Responsible for providing the asset, constraint and planning data to the project team.
• Available to discuss the modelling approach and confirm way forward.
• Provide clarity on how the resulting numbers are to be used (e.g. in justifying innovation) and verify the approach is consistent with that objective.
• Provide clarity on how the resulting numbers are to be used (e.g. in justifying innovation) and verify the approach is consistent with that objective.

Stage 2: Understand value of headroom to Distribution Network connected demand and generation assets that provide flexibility.

Key difference from Stage 1:

Baringa 

• PLEXOS will be augmented to represent the constraint availability factor likely for distribution-connected assets separately from transmission-connected. This is different to Stage 1 where the GB system was modelled as a single block.
• Within this stage, we begin to understand the impact headroom has on the distribution network will have on the whole system.
• Greater granularity from the network study is included, to quantify the extent to which different classes of demand and generation are limited by distribution vs transmission network constraints.
• We plan for more PLEXOS runs to test the impact of different magnitudes of headroom shortfall, at different voltage levels, and with different market solutions (e.g. ANM). Case studies will be informed by the early workshops, but may include aspects such as clustering of specific types of generation.

EA Technology Ltd 

• Transmission bottlenecks modelled, GSP bottlenecks not modelled.
• Generic distribution network archetype constraint modelling on a non-geographic basis. Based on nominal numbers of archetypes per licence.
• Refine headroom treatment at different voltage levels.
• Provide insights into effect of constraints on asset curtailment e.g. through ANM.
• Following the GB wide analysis performed in Stage 1, the NGED Licence Area specific Transform models will be used to obtain more geographical granularity.

National Grid 

• Provide data (as available and permissible) on ANM curtailment of existing assets.
• Engage in discussions with the project team e.g. on the impact at different voltage levels, and curtailment market mechanisms.

Stage 3: Detailed zonal model development and consolidation

Key difference from Stage 2:

Baringa 

• The difference between Stage 2 and Stage 3 is not the resolution of the constraint modelling but how assets are defined to match geographic resource availability. Stage 3 builds on the archetypical Stage 2 by skewing the amount of dispatchable load and generation by considering renewable wind and solar availability, or land availability for batteries or EV chargers.
• Baringa’s separate GB Zonal Model will be used to show zonal representation of generation, batteries and demand across different geographic aspects of the network, in contrast to the more singular GB block based models used in previous stages.
• The specific case studies built will be refined in the highest granularity tailored to the NGED network.
• Further refinement of curtailment logic is likely as our understanding of the dynamics improve.
• Describe the potential impact of how locational marginal pricing may impact the modelling employed in this project. Identify how different wholesale market structures would vary the extent to which headroom benefits the wholesale market.
• Study the effect of headroom if the DSO/ESO were to adopt flex dispatch that maximises the consumption of electricity when the grid is at least carbon intensity.

EA Technology Ltd 

• Support any further refinement of the curtailment logic.
•  Transform models will be run again, with outputs being given to cover each of the 11 LV and 5 HV archetypes.

National Grid 

•  Continue to provide timely review of proposed approaches and interim deliverables.
• Organise project workshop sessions.

• Scope

  Stage 1: Theoretical development of project and initial modelling.

  D1.1: Conceptual Translation of Headroom on generation, storage, and demand (Baringa)

  • Slides presenting case studies of where headroom provides benefit to generation, storage, and demand within a national network. D1.2a: Confirmed Headroom Archetypes for PLEXOS (EATL)
  • Completion of stage 1 workshops and agreement of modelling parameters for updates to Transform analysis. D1.2b: Outputs from Headroom Analysis for PLEXOS (EATL)
  • Tabulated data outputs from the analysis as set out for Stage 1 PLEXOS analysis.
  • Short report providing an overview of the approach and any key assumptions or data inputs necessary to carry out the analysis for Stage.
  • Existing asset curtailment/turn-down volume and timing (MWh per asset class per hour of year).
  • New asset installed capacity restrictions (MW) if applicable.
  • More granular description of individual assets to feed into non-PLEXOS impacts.

  D1.3: Stage 1 Report (Baringa)

  • Provide a breakdown of an example energy bill and explain how the markets and price mechanisms may be affected by distribution headroom availability.
  • Qualitatively describe the endogenous variables limited by network headroom availability both now, and with the levels of LCT and DER forecast to connect to the distribution network, linking to the breakdown of a customer bill.
  • Describe how higher-cost and higher-carbon alternatives may be required to maintain system balance and stability when distributed connected Low Carbon alternatives are blocked, due to headroom issues.
  • Using the theoretical framework and initial modelling, explain the magnitude of benefit available from headroom increases at the national scale.
  • Detailed report explaining conceptually how headroom creates whole system value
  • Research/modelling plan defining the way that headroom is to be modelled. Stage Gate Review Stage 2: Understand value of headroom to National Grid connected DER. D2.1: Updated theoretical understanding of headroom (Baringa)
  • Draft slides detailing conceptually how headroom creates whole system value.
  • Research/modelling plan defining the way that headroom is to be modelled. D2.2a: Updated Headroom archetypes for PLEXOS (EATL)
  • Completion of stage 2 workshops and agreement of modelling parameters for updates to Transform analysis. D2.2b: Outputs from Headroom analysis for PLEXOS (EATL)
  • Tabulated data outputs from the analysis as set out for Stage 2 PLEXOS analysis.
  • Updated short report highlighting any key changes in assumptions or data inputs necessary to carry out the analysis for Stage 2.
  • Existing asset curtailment/turn-down volume and timing (MWh per asset class per hour of year).
  • New asset installed capacity restrictions (MW) if applicable.
  • More granular description of individual assets to feed into non-PLEXOS impacts.

  D2.3: Stage 2 Modelling Report (Baringa)

  •  PLEXOS modelling will represent NGED-connected assets separately from non-NGED-connected.
  • With- and without-headroom data including:

  - Hourly day-ahead and within-day prices for the modelled period (for 2028, 2035 and 2050).

  - System carbon emissions.

  - Ancillary Service participation and cost to ESO.

  • Collated information to give a £/MWh headroom whole system value, which will vary depending on archetype grouping.

  Stage Gate Review D3.1: Updated translation of Headroom on generation, storage, and demand (Baringa)

  • Slides presenting updated case studies.
  • Following a successful stage gate review, develop the scenarios adding greater. depth and detail using zonal modelling.

  D3.2a: Agreed Headroom archetypes for NGED PLEXOS modelling (EATL)

  • Completion of stage 3 workshops and agreement of modelling parameters for updates to Transform analysis.

  D3.2b: Outputs from Headroom Analysis for PLEXOS (EATL)

  • Tabulated data outputs from the analysis as set out for Stage 3.
  • Updated short report highlighting any key changes in assumptions or data inputs necessary to carry out the analysis for Stage.
  •  Existing asset curtailment/turn-down volume and timing (MWh per asset class per hour of year).
  • New asset installed capacity restrictions (MW) if applicable.
  • More granular description of individual assets to feed into non-PLEXOS impact.

  D3.3: Stage 3 Modelling Report (Baringa)

  • PLEXOS will be rebuilt to show zonal representation of generation, batteries and demand.
  • Explain how increased distribution network headroom may allow key stakeholders in the energy system to deploy low carbon assets more freely.
  •  Explain the financial impact this may have on an average customer energy bill.
  • Outline the benefit additional headroom can offer the whole energy system both in terms of £/MWh and CO2/MWh, following a more detailed study.
  • Describe the potential impact of how locational marginal pricing may impact the modelling employed in this project. Identify how different wholesale market structures would vary the extent to which headroom benefits the wholesale market. Project Closedown and Implementation (National Grid)
  • Produce closedown report and publish to the ENA Smarter Network Portal.
  • Disseminate key project findings.
• Success Criteria

  The delivery of this project is split into three stages of increasing granularity. Results from Stage 1 will inform the project board whether there is value in continuing into Stage 2. Similarly, results from Stage 2 will inform the project board whether there is value in continuing into Stage 3. Therefore, the success criteria for this project is segmented per delivery stage. If all three stages are completed, the Stage 3 Success Criteria can be used to assess the value created by the project as a whole.

  Stage 1 Success Criteria

  • A successful expert workshop is held, with attendance from National Grid DSO, ESO, and project partners. The outcomes of the workshop have successfully directed the project towards maximum value.
  • A comprehensive methodology to understand the value of network headroom is produced. This should be completed in collaboration with National Grid, Baringa and EA Technology LTD. – A conceptual translation of headroom on generation, storage, and demand is produced in Stage 1, which helps understand exactly how to model headroom availability. – An understanding of how the value network headroom availability differs according to voltage level, and according to time-base scenarios. – Following detailed PLEXOS studies, understand how headroom availability changes the carbon intensity of the grid and consequently offers carbon savings.
  • Incorporate constraints based on a national view into PLEXOS to understand the proportion of available low carbon generation that is curtailed, which otherwise supports the merit order effect.
  • Develop an understanding of how the proportion of renewable generation affects the wholesale price. During Stage 1, this will be at a national level with only qualitative consideration of whether demand and generation assets are connected to the distribution network or transmission network.
  • Provide an understanding of the scale of benefit increased distribution headroom may have in terms of £/MWh, and CO2/MWh. At Stage 1, this will explore what times of the year the benefit is largest.
  • Detailed summary reports are produced for Stage 1 that outlines the methodology in detail, the sources of any data used, and presents key findings in a clear and understandable way. This should incorporate the effect additional network headroom has on other aspects of the customer bill, including balancing system costs, network costs, and carbon accounting costs.

  Stage 2 Success Criteria

  •  A successful expert workshop is held, with attendance from National Grid DSO, ESO, and project partners. The outcomes of the workshop have successfully directed the project towards maximum value.
  •  Incorporate constraints based on individual voltage levels into PLEXOS to understand the proportion of available low carbon distribution connected generation that is curtailed, which otherwise supports the merit order effect.
  • Develop an understanding of how the proportion of renewable generation affects the wholesale price. During Stage 2, this will be at a national level with detailed consideration of whether demand and generation assets are connected to the distribution network or transmission network. ·
  • Provide an understanding of the scale of benefit increased distribution headroom may have in terms of £/MWh, and CO2/MWh. At Stage 2, this will explore what times of the year the benefit is largest but also consider the relative split between GB wide free dispatch and the benefit gained from increased distribution network headroom.

  Detailed summary reports are produced for Stage 2 that outlines the methodology in detail, the sources of any data used, and presents key findings in a clear and understandable way. This should incorporate the effect additional network headroom has on other aspects of the customer bill, including balancing system costs, network costs, and carbon accounting costs.

  Stage 3 Success Criteria

  • A successful expert workshop is held, with attendance from National Grid DSO, ESO, and project partners. The outcomes of the workshop have successfully directed the project towards maximum value.
  •  Incorporate constraints based on geographic zones and voltage levels into PLEXOS to understand the proportion of available distribution connected generation that is curtailed, which otherwise supports the merit order effect.
  • Develop an understanding of how the proportion of renewable generation affects the wholesale price. During Stage 3, this will be at a zonal level with detailed consideration of whether demand and generation assets are connected to the distribution network or transmission network in different parts of Great Britain.
  • Provide an understanding of the scale of benefit increased headroom may have in terms of £/MWh, and CO2/MWh. At Stage 3, this will explore the impact of geographic differences as explored in the PLEXOS GB zonal model.
  • Detailed summary reports are produced for Stage 3 that outlines the methodology in detail, the sources of any data used, and presents key findings in a clear and understandable way. This should incorporate the effect additional network headroom has on other aspects of the customer bill, including balancing system costs, network costs, and carbon accounting costs.
  •  Describe the potential impact of how locational marginal pricing may impact the modelling employed in this project. Identify how different wholesale market structures would vary the extent to which headroom benefits the wholesale market.
  • Provide insight on how available distribution network headroom influences ESO/DSO dispatch strategies that seek to promote electricity consumption at least carbon intensive times.
• Potential for new learning

  The project provides a standardised methodology that enables improved decision-making when faced with multiple options for innovation spending or infrastructure projects and a fairer allocation of limited funds.

  This project creates a standardised methodology to determine the whole electricity system value of headroom and provides a value at different voltage levels. The application of the methodology and the model for other Network Licensees enables each to evaluate competing innovation projects or infrastructure projects on a fair and equitable basis across the industry.

  Understanding the value of headroom will allow us to innovate effectively to add capacity on our network that can facilitate decarbonisation and net zero. To date, our projects have helped shape critical areas of our business such as alternative connections, data and digitalisation, flexibility services and network management systems. This project aims to build on existing work to help understand the whole system benefit of network headroom, allowing us to justify further innovation activities in this space.

• Documents and links

  Project Registration and PEA document 

  End of Stage 1 Report

  Whole System Thinking - Phase 1 Network Modelling

  NIA Annual Report

• Monthly updates

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