Electric Vehicle Load Control Strategy Based on Improved Aquila Optimizer Algorithm-Reference-Cited by-同舟云学术

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Electric Vehicle Load Control Strategy Based on Improved Aquila Optimizer Algorithm

Published:2023-07-21 Issue: Volume: Page:
ISSN:
Container-title:2023 6th Asia Conference on Energy and Electrical Engineering (ACEEE)
language:
Short-container-title:

Author:

Meng Zijie¹,Jin Xin²,Liu Jiale¹,Cai Xinlei¹,Zhu Jinzhou¹,Pan Tingzhe²

Affiliation:

1. Power Dispatching and Controlling Center of Guangdong Power Grid Company Limited,Guangdong,China

2. Institute of Measurement Technology China Southern Power Grid Electric Power Research Institute Co., Ltd,Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid,Guangdong,China

Funder

China Southern Power Grid

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10239547/10239550/10239561.pdf?arnumber=10239561

Reference14 articles.

1. A Multi-Agent Reinforcement Learning-Based Data-Driven Method for Home Energy Management

2. Deep reinforcement learning based optimization method for charging of aggregated electricvehicles[J];xingyu;Power System Technology,2021

3. On-Line Building Energy Optimization Using Deep Reinforcement Learning

4. Large-scale electric vehicle charging and switching load optimization dispatching based on deep reinforcement learning[J];dunnan;Power System Automation,2022

5. Charging and discharging scheduling strategy of electric vehicles considering the demand on both sides of supply and demand in V2G mode[J];yiran;Electric Power Automation Equipment,2021

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