Sizing and Coordination Strategies of Battery Energy Storage System Co-Located with Wind Farm: The UK Perspective

Fulin Fan, Giorgio Zorzi, David Campos-Gaona, Graeme Burt, Olimpo Anaya-Lara, John Nwobu and Ander Madariaga
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Fulin Fan: Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK
Giorgio Zorzi: Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK
David Campos-Gaona: Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK
Graeme Burt: Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK
Olimpo Anaya-Lara: Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK
John Nwobu: Offshore Renewable Energy Catapult, Glasgow G1 1RD, UK
Ander Madariaga: Offshore Renewable Energy Catapult, Glasgow G1 1RD, UK

Energies, 2021, vol. 14, issue 5, 1-21

Abstract: The rapid development and growth of battery storage have heightened an interest in the co-location of battery energy storage systems (BESS) with renewable energy projects which enables the stacking of multiple revenue streams while reducing connection charges of BESS. To help wind energy industries better understand the coordinated operation of BESS and wind farms and its associated profits, this paper develops a simulation model to implement a number of coordination strategies where the BESS supplies enhanced frequency response (EFR) service and enables the time shift of wind generation based on the UK perspective. The proposed model also simulates the degradation of Lithium-Ion battery and incorporates a state of charge (SOC) dependent limit on the charge rate derived from a constant current-constant voltage charging profile. In addition, a particle swarm optimisation-based battery sizing algorithm is developed here on the basis of the simulation model to determine the optimal size of the co-located BESS along with SOC-related strategy variables that maximise the net present value of the wind + BESS system at the end of the EFR contract.

Keywords: battery energy storage system; co-located system; coordination strategy; frequency response; particle swarm optimisation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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