Projects: |
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Reference Number | EP/Y005376/1 | |
Title | Virtual Power Plant with Artificial Intelligence for Resilience and Decarbonisation (VPP-WARD) | |
Status | Started | |
Energy Categories | Renewable Energy Sources 40%; Other Cross-Cutting Technologies or Research(Energy system analysis) 20%; Other Power and Storage Technologies(Electricity transmission and distribution) 40%; |
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Research Types | Basic and strategic applied research 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 70%; Systems Analysis related to energy R&D 10%; Sociological economical and environmental impact of energy 20%; |
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Principal Investigator |
Dr H Sun No email address given Engineering Durham University |
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Award Type | Standard | |
Funding Source | EPSRC | |
Start Date | 01 May 2023 | |
End Date | 31 January 2026 | |
Duration | 33 months | |
Total Grant Value | £1,845,327 | |
Industrial Sectors | Energy | |
Region | North East | |
Programme | Technology Missions Fund | |
Investigators | Principal Investigator | Dr H Sun , Engineering, Durham University (99.985%) |
Other Investigator | Dr N Metje , Civil Engineering, University of Birmingham (0.001%) Dr A Faramarzi , Civil Engineering, University of Birmingham (0.001%) Dr B Kazemtabrizi , Engineering, Durham University (0.001%) Dr AS Osman , Engineering, Durham University (0.001%) Dr PC Matthews , Engineering, Durham University (0.001%) Dr M Shahbazi , Engineering, Durham University (0.001%) Dr A Kiprakis , Sch of Engineering and Electronics, University of Edinburgh (0.001%) Dr D Kirli , Sch of Engineering and Electronics, University of Edinburgh (0.001%) Professor S Tsaftaris , Sch of Engineering and Electronics, University of Edinburgh (0.001%) Dr H Du , Mathematical Sciences, Durham University (0.001%) Dr M Mahmud , Fac of Engineering and Environment, Northumbria University (0.001%) Dr J Jiang , Fac of Engineering and Environment, Northumbria University (0.001%) Dr A Jindal , Computer Scienc, Durham University (0.001%) Dr G Aujla , Computer Scienc, Durham University (0.001%) Professor S Xiao , Management and Marketing, Durham University (0.001%) |
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Industrial Collaborator | Project Contact , Northumbrian Water Ltd (0.000%) Project Contact , National Grid plc (0.000%) Project Contact , Durham County Council (0.000%) Project Contact , TNEI Services Limited (0.000%) Project Contact , Northern Powergrid (0.000%) Project Contact , Siemens plc (0.000%) Project Contact , CFMS Services Limited (0.000%) Project Contact , Det Norske Veritas DNV GL UK Limited (0.000%) Project Contact , Equinor UK Ltd (0.000%) Project Contact , Kinewell Energy (0.000%) Project Contact , Mithrasol ltd (0.000%) |
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Web Site | ||
Objectives | ||
Abstract | Distributed Energy Resources (DERs) are small, modular energy generation and storage units, e.g., wind turbines, photovoltaics, batteries, and electric vehicles, that could be connected directly to the power distribution network. DERs play a critical role in achieving Net Zero. Presently there are over 1 million homes with solar panels in the UK. With the green energy transition well under way in the UK, by 2050 there could be tens of millions of DERs connected to the UK power grid.Although DERs have many benefits, e.g., a reduced carbon footprint and improved energy affordability, they present complex challenges for network operators (e.g., low DER visibility, bi-directional power flow, and voltage anomalies), creating a major barrier to Net Zero. Meanwhile, natural hazards and extreme events are an increasing threat not only to humans but also power grid resilience - a direct impact is the power cuts, e.g., Storms "Dudley", "Eunice" and "Franklin" in February 2022 left over a million homes without electricity.How best to manage millions of DERs is still an open question, especially for improving the grid resilience to natural hazards and extreme events, e.g., storms and heatwaves. This project will develop innovative physics-informed Artificial Intelligence (AI) solutions for enabling Virtual Power Plants (VPP), capable of aggregating and managing many diverse DERs; not only improving decision-making for network operators but also enhancing the grid resilience to natural hazards and extreme events. These could also lead to reduced energy bills for millions of UK energy consumers, less power cuts during extreme events, to greater adoption and more efficient management of DERs, and ultimately to enable rapid progress towards Net Zero. | |
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 | 03/05/23 |