发电技术2024，Vol.45Issue(4)：734-743,10.DOI:10.12096/j.2096-4528.pgt.23029
基于深度强化学习的有源配电网电压分层控制策略
Voltage Hierarchical Control Strategy of Active Distribution Network Based on Deep Reinforcement Learning
摘要
Abstract
[Objectives]The randomness and volatility of distributed power generation poses significant challenges for the voltage control in active distribution network(AND).In this context,there is an urgent need for an efficient voltage control strategy to ensure the safe operation of ADN.[Methods]Based on the deep reinforcement learning method,a voltage control strategy for double-layer regional distribution networks was proposed.First,based on the adjustment characteristics of voltage regulating equipment and the complexity of controllable elements,a regional coordinated control area and a local autonomous control area were designed for the radiating grid structure of the ADN,and the voltage control model of each area was constructed.Then,the model was solved by deep Q-Network(DQN)algorithm and deep deterministic policy gradient(DDPG)algorithm to achieve the purpose of tracking voltage changes in real time,and effectively solve the voltage control problem during the operation of the ADN.Finally,the method was verified by IEEE 33-bus simulation examples.[Results]The DQN algorithm and the DDPG algorithm were used to solve the control variables in the coordinated control region and the local autonomous region respectively,realizing real-time decision-making of voltage regulation in the ADN system,and solving the problems of bidirectional flow of ADN power flow and complex and changeable voltage.[Conclusions]The proposed control strategy has obvious effect on controlling voltage deviation,and has strong accuracy and practicality.关键词
有源配电网(ADN)/区域协调控制/本地自治控制/深度强化学习/电压控制策略Key words
active distribution network(ADN)/regional coordination control/local autonomous control/deep reinforcement learning/voltage control strategy分类
能源科技引用本文复制引用
杜婉琳,王玲,罗威,朱远哲,吕鸿,马潇男,周霞..基于深度强化学习的有源配电网电压分层控制策略[J].发电技术,2024,45(4):734-743,10.基金项目
国家自然科学基金项目(52207009) （52207009）
南方电网公司科技项目(GDKJXM20200331). Project Supported by National Natural Science Foundation of China(52207009) （GDKJXM20200331）
Science and Technology Projects of China Southern Power Grid Corporation(GDKJXM20200331). （GDKJXM20200331）
