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| Reference Number | NIA2_NGESO053 | |
| Title | Exploring the Economic Benefits of Co-optimising Procurement of Energy, Response and Reserve | |
| Status | Completed | |
| Energy Categories | Other Power and Storage Technologies (Electricity transmission and distribution) 50%; Other Cross-Cutting Technologies or Research (Energy Economics) 50%; |
|
| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | SOCIAL SCIENCES (Economics and Econometrics) 50%; ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 50%; |
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| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Project Contact No email address given National Grid plc |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 September 2023 | |
| End Date | 31 March 2024 | |
| Duration | ENA months | |
| Total Grant Value | £500,000 | |
| Industrial Sectors | Power | |
| Region | London | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , National Grid plc (100.000%) |
| Industrial Collaborator | Project Contact , National Grid plc (0.000%) |
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| Web Site | https://smarter.energynetworks.org/projects/NIA2_NGESO053 |
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| Objectives | This project will consist of four Work Packages (WPs) and a mixed methodology of qualitative and quantitative approaches will be used. Qualitative assessments will provide additional knowledge on the advantages and disadvantages of a co-optimised system (see WP1 below).Quantitative modelling will be undertaken for WP2&3 to provide a robust assessment of the relative historic and future savings from co-optimising energy, reserve and response products. WP4 will build upon these models to assess the relative merits/shortfalls of implementing the same co-optimised procurement method but under a nodal pricing system. The following section outlines how this project will meet the measurement and data quality statement. WP1: Qualitative discussion on co-optimising energy and ancillary servicesThis is a qualitative work package and therefore does not require the collection, storage and analysis of data. WP2: Assessment of historical-cost savings upon co-optimisation In this WP operational data collected from both the public data portal and internal databases (such as the NED) and will be analysed and compared using FTI"s (project partner) PLEXOS model.The ESO has undertaken several steps to ensure that provided data is of a sufficient quality. Firstly, the Request for Proposal undertaken specified the datasets the project would require. Upon receiving this, the data asks were then refined through setting up several meetings between the project partner, the project leads and those familiar with the datasets. Identified public data from the ESO data portal could then be shared, with the confidential data being shared once the contract containing the confidentiality clause can be signed. The data will be shared via a SharePoint account and stored locally on an FTI server. The relevant confidentiality clauses will be adhered to. It is acknowledged that there is a level of uncertainty in trying to re-create the system outcomes in 2021 using available datasets. However, if the initial modelling outcomes differ from what was observed in 2021, the project team will perform informed amendments to their assumptions until they accurately re-create the conditions witnessed in 2021. In comparing the results, a robust estimate of the historical cost-savings from the co-optimisation of energy and ancillary services in GB across 2021 will be produced. WP3 & 4: Quantify the potential efficiency savings for GB from 2025 2035 (and under a nodal market design)The forecasted requirements for response and reserve services post-2025 (such as Slow Reserve) will be used to set the parameters of the model. Given how the GB energy system will evolve over this timescale, so too will requirements for services. It is therefore accepted that there is a level of uncertainty over these requirements. However, to mitigate against this where possible, internal Subject Matter Experts (SME"s) who are involved with the defining of these service requirements have been consulted with the most accurate representation being utilised in the project. WP4 is based on the same assumptions and therefore the same data quality measurements have been applied. In line with the ENA"s ENIP document, the risk rating is scored Low.TRL Steps = 2Cost = 1(£500k)Suppliers = 1 (1 Supplier)Data Assumptions = 1Total = 5 (Low) The project consists of four work packages. These will be delivered through both qualitative and quantitative assessments. This project is an initial exploration of co-optimisation in a GB context, and we expect more detailed phases of work would be needed before any introduction of a co-optimised system.Work package 1: Qualitative discussion of hypothesised pros and cons of co-optimising energy and ancillary services in the context of GB"s wider market reform work. This work will consider potential issues such as computation complexity and cross-border trading in a co-optimised model.Work package 2: Assessment of the historical-cost savings of co-optimised day-ahead and/or real time procurement of energy and ancillary services in the GB market.By modelling a reliable representation of the GB electricity market, the model then considers the counterfactual scenario wherein energy and Ancillary Services (AS) have been co-optimised. This in turn will provide a historic assessment of cost savings for a specific year. Work package 3: Quantify the potential efficiency savings for GB from 2025 2035 co-optimising procurement of energy and ancillary services. In taking the current electricity market as the counterfactual, this work package would compare this against a fully co-optimised system. Doing so returns a future cost saving. Work package 4: Quantitative assessment of the potential efficiency savings from the co-optimised procurement of energy and AS in a GB nodal market from 2025 2035.This work package tests the hypothesis that the procurement and utilisation of resources would be more optimal in a more locational pricing system as market participants would consider the physical realities and constraints of the transmission network and reflect this knowledge in their day-ahead and real-time bids and offers. If this project finds substantial potential benefits from co-optimisation, next steps may include developing the work into a further phase to understand the design/deliverability challenges in more depth. The key objectives are to: Enhance understanding of the advantages and disadvantages of implementing a co-optimised system within GB. Assess historic and future efficiency savings which stem from co-optimising across energy, response and reserve products.Explore the relative merits of locational pricing for optimised ancillary service procurement.Disseminate key findings to stakeholders and inform the debate on the role of a co-optimised. electricity system, informing the wider REMA discussion about future dispatch mechanism options | |
| Abstract | Energy and balancing services are currently procured sequentially in separate markets. This means service providers must guess which market will bring them the most value and which market they are most likely to clear in. The result is likely to be suboptimal for several reasons, including inflated prices across wholesale and balancing markets as service providers add opportunity costs into their bids in each market.There have been no quantitative studies to date that explore the theoretical historic and future efficiency savings when energy, reserve and response are co-optimised within GB. The outcome of this project will help inform the wider debate on future market reforms. | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 02/10/24 | |
