Profit maximization for large-scale energy storage systems to enable fast EV charging infrastructure in distribution networks

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dc.contributor.authorLai, Chun Sing
dc.contributor.authorChen, Dashen
dc.contributor.authorZhang, Jinning
dc.contributor.authorZhang, Xin
dc.contributor.authorXu, Xu
dc.contributor.authorTaylor, Gareth A.
dc.contributor.authorLai, Loi Lei
dc.date.accessioned2022-08-19T13:07:41Z
dc.date.available2022-08-19T13:07:41Z
dc.date.issued2022-11-15
dc.description.abstractLarge-scale integration of battery energy storage systems (BESS) in distribution networks has the potential to enhance the utilization of photovoltaic (PV) power generation and mitigate the negative effects caused by electric vehicles (EV) fast charging behavior. This paper presents a novel deep reinforcement learning-based power scheduling strategy for BESS which is installed in an active distribution network. The network includes fast EV charging demand, PV power generation, and electricity arbitrage from main grid. The aim is to maximize the profit of BESS operator whilst maintaining voltage limits. The novel strategy adopts a Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm and requires forecasted PV power generation and EV smart charging demand. The proposed strategy is compared with Deep Deterministic Policy Gradient (DDPG), Particle Swarm Optimization and Simulated Annealing algorithms to verify its effectiveness. Case studies are conducted with smart EV charging dataset from Project Shift (UK Power Networks Innovation) and the UK photovoltaic dataset. The Internal Rate of Return results with TD3 and DDPG algorithms are 9.46% and 8.69%, respectively, which show that the proposed strategy can enhance power scheduling and outperforms the mainstream methods in terms of reduced levelized cost of storage and increased net present value.en_UK
dc.identifier.citationLai CS, Chen D, Zhang J, et al., (2022) Profit maximization for large-scale energy storage systems to enable fast EV charging infrastructure in distribution networks. Energy, Volume 259, November 2022, Article number 124852en_UK
dc.identifier.issn0360-5442
dc.identifier.urihttps://doi.org/10.1016/j.energy.2022.124852
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18341
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectDistribution network optimizationen_UK
dc.subjectFast EV charging Demanden_UK
dc.subjectDeep reinforcement learningen_UK
dc.subjectBattery energy storage systemsen_UK
dc.titleProfit maximization for large-scale energy storage systems to enable fast EV charging infrastructure in distribution networksen_UK
dc.typeArticleen_UK

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