Control Method for PEMFC Using Improved Deep Deterministic Policy Gradient Algorithm

被引：0
|
作者：
Li, Jiawen [1 ]
Li, Yaping [2 ]
Yu, Tao [1 ]
机构：
[1] South China Univ Technol, Coll Elect Power, Guangzhou, Peoples R China
[2] China Elect Power Res Inst, Nanjing, Peoples R China
来源：
FRONTIERS IN ENERGY RESEARCH | 2021年 / 9卷
基金：
中国国家自然科学基金;
关键词：
output voltage; proton exchange membrane fuel cell; deep deterministic policy gradient algorithm; robustness; PEMFC; OXYGEN EXCESS RATIO; POWER POINT TRACKING; FUEL-CELL; PV SYSTEMS; PID CONTROL; AIR-FLOW; EXTRACTION;
D O I：
10.3389/fenrg.2021.753064
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
A data-driven PEMFC output voltage control method is proposed. Moreover, an Improved deep deterministic policy gradient algorithm is proposed for this method. The algorithm introduces three techniques: Clipped multiple Q-learning, policy delay update, and policy smoothing to improve the robustness of the control policy. In this algorithm, the hydrogen controller is treated as an agent, which is pre-trained to fully interact with the environment and obtain the optimal control policy. The effectiveness of the proposed algorithm is demonstrated experimentally.</p>
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页数：5
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