Projects
Projects: Projects for Investigator |
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| Reference Number | NIA2_NGESO0013 | |
| Title | Advanced Dispatch Optimisation | |
| Status | Completed | |
| Energy Categories | Other Cross-Cutting Technologies or Research(Energy system analysis) 20%; Other Power and Storage Technologies(Electricity transmission and distribution) 80%; |
|
| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 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 ESO |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 November 2021 | |
| End Date | 31 July 2022 | |
| Duration | ENA months | |
| Total Grant Value | £750,000 | |
| Industrial Sectors | Power | |
| Region | London | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , National Grid ESO (100.000%) |
| Industrial Collaborator | Project Contact , National Grid plc (0.000%) |
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| Web Site | https://smarter.energynetworks.org/projects/NIA2_NGESO0013 |
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| Objectives | This study will split the project into two parts, an initial feasibility work package, and a more technical work package to deliver a comprehensive report on how a future dispatch optimisation toolset could be scoped and developed to optimise increasingly complex balancing actions on the GB system. Risk AssessmentIn line with the ENAs ENIP document, the risk rating is scored Low.TRL Steps = 1 (2 TRL steps)Cost = 2 (£750k)Suppliers = 1 (1 suppliers)Data Assumption = 2 (data supplied by suppliers for analysis) This study will evaluate the inputs and elements necessary to inform the optimization algorithms, and the approach to optimization, with a report that will set out the development pathway for this tool. The Report will address the following:recommendations for the approach to purpose driven modellingcontemplation of use-case specific technology recommendation including simulation and modelling recommendationscontemplation of inputs and approaches to data gapscontemplation of optimization approaches Objective 1: to understand what could be possible with existing, or new data and optimisation techniques to improve the way actions are taken in the Balancing Mechanism, through development of new tools.Objective 2: have a clear view of what other work and research has been developed in similar use cases and other sectors (e.g. Digital Twins), which would establish a best practice approach to optimisation the BM for the GB energy system, and help quantify the benefits which could be delivered for end consumers. Objective 3: use the understanding developed in this study to set out the next steps, and a roadmap for how innovative new tools would be delivered for the ENCC in future. | |
| Abstract | This project will research best practices globally and advanced technologies available (or being developed), to assess the feasibility of developing an advanced dispatch optimisation tool for the Balancing Mechanism (BM), scope this tool, and set out a roadmap for how this, and other comprehensive optimisation tools could be developed for system operators. It is hoped these tools will evaluate extraneous variables and be future proof for a rapidly changing energy landscape, which includes more diverse providers, services and dynamic parameters across the system. The project will also be an initial use-case for the wider Virtual Energy System (VES) programme, and inform the capabilities and considerations of how interconnected digital twins could provide substantial benefits for consumers and the whole energy system. | |
| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 14/10/22 | |
