Projects
Projects: Projects for Investigator |
||
| Reference Number | NIA2_NGESO032 | |
| Title | Course-correction Dispatch Instructor | |
| Status | Completed | |
| Energy Categories | Other Cross-Cutting Technologies or Research(Energy system analysis) 10%; Other Power and Storage Technologies(Electricity transmission and distribution) 90%; |
|
| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 100% | |
| 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 February 2023 | |
| End Date | 31 March 2024 | |
| Duration | ENA months | |
| Total Grant Value | £1,700,000 | |
| 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%) |
|
| Web Site | https://smarter.energynetworks.org/projects/NIA2_NGESO032 |
|
| Objectives | "Phase 1 of this project aims to use advanced optimisation techniques and data-driven approaches to develop course-correction models for dispatch decision-support problems, creating scenarios to test scalability of developed methods. The development and testing of models will be desktop-based research delivered in a single work package across 14 months, consisting of the following tasks: Task 1.1 – Identification of the main components of course-correctionTask 1.2 – Determining a method to select a small set of units for instructionTask 1.3 – Implementation of the course-correction toolTask 1.4 – Credible operational scenarios for testing, including data needs for scalability test of the methodTask 1.5 – Pilot testing of the approach Following completion of the first phase, this project will then consider scoping the following work packages in more detail for phase 2: WP2: Short-term dispatch (within 90mins)WP3: Long-term dispatch (90mins – 4hrs)WP4: Explanation of optimisation advice tool The project will cover workshops with the ESO Balancing Programme throughout, and a dissemination event including key industry stakeholders identified. In line with the ENAs ENIP document, the risk rating is scored Low: TRL Steps = 1 (1 TRL steps)Cost = 3 (>£1mk)Suppliers = 1 (1 supplier)Data Assumptions = 1Total = 6 (Low) " "This project aims to discover, develop, and test a world first course-correction methodology to balance an electricity system. The project will deliver proof-of-concept (PoC) capabilities for course correction dispatch decision support, aiming to release operators of manual tasks and ensure timely decisions are made for economic and reliable operation of the system. The PoC tool will be developed and tested using advanced optimisation techniques and data-driven approaches, including development and implementation of a mathematical model, demonstrating the model performance on selected real-world data examples. Following successful delivery of the course-correction methodology and PoC, this project will then explore further dispatch support tools covering short-term and long-term energy dispatch, as well as further work to provide explainable solutions within the advice tools developed. " "Identify the main components of course correctionDefine a method to select a small set of units for instructionDevelop a PoC course correction tool and demonstrate the method on selected examples identifiedDefine data needs to test the scalability of the course correction method, including scenarios with a larger number of balancing unitsRefine the PoC tool and complete performance tests of the developed course correction methodology " | |
| Abstract | The Electricity National Control Centres (ENCC) current approach of manual instructions is limiting the number of units that can be instructed in real-time operation of the GB electricity system. With an increasing number of units to dispatch across multiple services, this approach is not sustainable for future economic and reliable operation of the system. The project will deliver a proof-of-concept decision-support tool to the ENCC, aiming to release operators of manual tasks and enabling them to focus on validating results and ensuring timely decisions are made. While control room decisions within-day span operational planning, scheduling and dispatch, the project will first focus on course-correction for dispatch decision-support problems. The tool will be developed and tested using advanced optimisation techniques and data-driven approaches, including development and implementation of a mathematical model, demonstrating the model performance on selected real-world data examples. | |
| Publications | (none) |
|
| Final Report | (none) |
|
| Added to Database | 12/10/23 | |
