现代电力2026，Vol.43Issue(3)：455-463,9.DOI:10.19725/j.cnki.1007-2322.2024.0063
基于改进双延迟深度确定性策略梯度算法的微电网低碳经济优化调度策略
A Low-carbon Economic Optimization Dispatching Strategy for Microgrids Based on Improved Twin Delayed Deep Deterministic Policy Gradient Algorithm
宋金威 1何悠悠 1孙大帅 1董臣臣 1王景龙1
作者信息
- 1. 上海采日能源科技有限公司,上海市 嘉定区 201800
- 折叠
摘要
Abstract
With the vigorous implementation of China's carbon peaking and carbon neutrality goals,renewable energy has gradually come into the public spotlight.The emergence of microgrids is conducive to the rapid absorption of renewable energy,making microgrid dispatching and optimization a research focal point.Traditional methods for low-carbon economic dispatching of microgrids encounter various challenges such as high data dimensionality,complex modeling,limited flexibility,and extended operation times.To address these challenges,a low-carbon economic optimization dispatching strategy for microgrids is proposed based on an improved twin delayed deep deterministic(TD3)policy gradient algorithm.Firstly,a statistical analysis on the strategy results of model predictive control(MPC)is conducted.The obtained operation rules of energy storage batteries are utilized to refine the self-learning rules of the TD3 algorithm,thereby effectively reducing the model's exploration area.Secondly,the dual buffer technique is introduced to address the issue of sample imbalance,achieving a dual enhancement in efficiency and robustness.Finally,the effectiveness of the proposed algorithm model is verified through the analysis of a case study of a demonstration microgrid.关键词
微电网/深度强化学习/双延迟深度确定性策略梯度算法/低碳经济调度/新能源消纳Key words
microgrid/deep reinforcement learning/twin delayed deep deterministic policy gradient algorithm/low-carbon economic dispatching/renewable energy consumption分类
信息技术与安全科学引用本文复制引用
宋金威,何悠悠,孙大帅,董臣臣,王景龙..基于改进双延迟深度确定性策略梯度算法的微电网低碳经济优化调度策略[J].现代电力,2026,43(3):455-463,9.
