Projects
Projects: Projects for Investigator |
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| Reference Number | NIA_SHET_0037 | |
| Title | Probabilistic Modelling for Connection Studies | |
| Status | Completed | |
| Energy Categories | Other Cross-Cutting Technologies or Research(Energy Models) 50%; Other Power and Storage Technologies(Electricity transmission and distribution) 50%; |
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| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Statistics and Operational Research) 25%; ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 75%; |
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| UKERC Cross Cutting Characterisation | Systems Analysis related to energy R&D (Energy modelling) 100% | |
| Principal Investigator |
Project Contact No email address given SSEN Scottish Hydro Electric Transmission |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 March 2022 | |
| End Date | 31 October 2023 | |
| Duration | ENA months | |
| Total Grant Value | £400,000 | |
| Industrial Sectors | Power | |
| Region | Scotland | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , SSEN Scottish Hydro Electric Transmission (100.000%) |
| Industrial Collaborator | Project Contact , Scottish and Southern Energy plc (0.000%) |
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| Web Site | https://smarter.energynetworks.org/projects/NIA_SHET_0037 |
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| Objectives | • Develop a probabilistic planning process for transmission connection studies that models the random characteristics of generation and demand over a longer period based on probabilistic models.• Carry out a case study to quantify and demonstrate potential efficiency benefits and any risks of using the new process.• Subject to successful demonstration of benefits, provide a prototype probabilistic planning toolkit of datasets and data analysis techniques to carry out this process. The main deliverable of this project is a prototype probabilistic planning toolkit and study process to apply to connection studies. The toolkit will generate statistics and visualisations to provide a detailed picture of network capacity under uncertainty. It will consist of a dataset and automated calculation processes. The toolkit will be developed with an architecture to achieve the computation requirements of the complex modelling whilst ensuring it runs in reasonable time, important for connection studies against the clock.The prototype probabilistic planning toolkit will be made up of a series of components:• Probabilistic models of generation, storage and load that represent the stochastic nature of each.• A tool to sample from the probabilistic models to give an envelope of network dispatches.• An interface to power system analysis software to generate a power system model for each sample.• Search and optimisation algorithms to calculate network capacity on the sample, such as generation headroom, boundary capability, and expected energy curtailed.• Tools to support iteration over multiple scenarios and reinforcement options to create a bespoke analysis process, to understand the need for projects across a range of uncertainty, such as generation scenarios, or the completion of different packages of projects.• Tools to generate results summary tables and visualisations.• Case studies to demonstrate the use of this approach compared to the deterministic approach currently in use and assess the benefit of wider adoption as business-as-usual.Estimated Benefits:This project is an investment in the planning processes used to define a capital investment programme of hundreds of millions of pounds over the current regulatory period alone. Improvement in investment decision making could result in substantial benefits in cost and in efficiency of connecting renewable generation and flexibility assets. The project will carry out a case study to quantify the benefit of adopting this approach as business-as-usual compared with the current deterministic approach. This project has the following objectives:1. Develop a probabilistic planning process for transmission connection studies.2. Evaluate the potential benefits of the probabilistic planning process when compared to existing BAU deterministic processes.3. Create a prototype probabilistic planning toolkit of datasets and data analysis techniques to carry out this process.4. Capture and disseminate the learning from this project and draft recommendations for future work. | |
| Abstract | This project will explore how more dynamic “probabilistic” modelling could be used by Transmission network planners to account for complex factors which could yield more efficient development and connection processes. This would allow the connection of more renewable generation and flexibility assets and seeks to enable more efficient operation of the electricity system.The main deliverable of this project is a prototype probabilistic planning toolkit and study process to apply to connection studies. | |
| Publications | (none) |
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| Final Report | (none) |
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| Added to Database | 14/10/22 | |
