Coordinated Electric Vehicle Active and Reactive Power Control for Active Distribution Networks

Wang, Yi, Qiu, Dawei, Strbac, Goran and Gao, Zhiwei (2022) Coordinated Electric Vehicle Active and Reactive Power Control for Active Distribution Networks. IEEE Transactions on Industrial Informatics. pp. 1-11. ISSN 1551-3203 (In Press)

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Official URL: https://doi.org/10.1109/TII.2022.3169975

Abstract

The deployment of renewable energy in power systems may raise serious voltage instabilities. Electric vehicles (EVs), owing to their mobility and flexibility characteristics, can provide various ancillary services including active and reactive power. However, the distributed control of EVs under such scenarios is a complex decision-making problem with enormous dynamics and uncertainties. Most existing literature employs model-based approaches to formulate the active and reactive power control problems, which require full models and are time-consuming. This paper proposes a multi-agent reinforcement learning method featuring actor-critic networks and a parameter sharing framework to solve the EVs coordinated active and reactive power control problem towards both demand-side response and voltage regulations. The proposed method can further enhance the learning stability and scalability with privacy perseverance via the location marginal prices. Simulation results based on a modified IEEE 15-bus network are developed to validate its effectiveness in providing system charging and voltage regulation services.

Item Type: Article
Additional Information: Funding information: Economic and Social Research Council (Grant Number: ES/T000112/1), Engineering and Physical Sciences Research Council (Grant Number: EP/T021780/1).
Uncontrolled Keywords: Electric vehicles, active distribution networks, active and reactive power control, location marginal prices, multiagent reinforcement learning.
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: John Coen
Date Deposited: 17 May 2022 10:43
Last Modified: 17 May 2022 13:18
URI: http://nrl.northumbria.ac.uk/id/eprint/49140

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