| 杨家令,陈 涛,高赐威.基于双延迟深度确定性策略梯度算法的微电网能源优化分配策略研究[J].电力需求侧管理,2024,26(4):01-08 |
| 基于双延迟深度确定性策略梯度算法的微电网能源优化分配策略研究 |
| Research on energy optimization allocation strategy for microgrids based on double delay deep deterministic strategy gradient algorithm |
| 投稿时间：2024-04-21 修订日期：2024-06-05 |
| DOI：10. 3969 / j. issn. 1009-1831. 2024. 04. 001 |
| 中文关键词: 微电网 燃料电池 能源优化分配 TD3算法 深度强化学习 |
| 英文关键词: microgrids fuel cells optimal energy allocation TD3 algorithm deep reinforcement learning |
| 基金项目:国家自然科学基金《基于深度强化学习技术的可交易能源系统智能决策问题研究》（52107079） |
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| 中文摘要: |
| 在孤岛模式下,微电网需独立于传统电力系统运作,高效协调内部能源以保障能源供应的连续性与高效性。通过策略延迟更新与双Q网络的引入,双延迟深度确定性策略梯度算法（twin delayed deep deterministic policy gradient,TD3）显著提升了复杂连续控制任务的处理效率和精度。基于此方法,设计了基于TD3算法的嵌有燃料电池的微电网能源优化分配策略,以提升微电网系统的稳定供电能力和质量,降低能耗与运维成本,增强系统的经济性与可靠性。通过综合分析,全面评估了所设计能源优化分配策略在不同场景下的综合性能。结果表明,通过对燃料电池系统充放电模式及比例的优化调度,所设计基于TD3算法的能源优化分配策略在提升能源分配效率、缩短响应时间及降低运营成本方面的性能优于传统算法。研究结果验证了TD3算法在应对可再生能源发电功率输出波动和负载需求变化时的高效适应能力,在实际能源管理场景中具有广泛适用性。 |
| 英文摘要: |
| In island mode, microgrids need to operate independently from traditional power systems, efficiently coordinating internal ener?gy to ensure the continuity and efficiency of energy supply. The twin delayed deep deterministic policy gradient algorithm significantly im?proves the processing efficiency and accuracy of complex continuous control tasks through policy delay updates and the introduction of du?al Q networks. Based on this way, an energy optimization allocation strategy is designed for microgrids embedded with fuel cells based onthe TD3 algorithm, to improve the stable power supply capacity and quality of the microgrid system, reduce energy consumption and opera?tion costs, and enhance the system’s economy and reliability. Through comprehensive analysis, the comprehensive performance of the de?signed energy optimization allocation strategy in different scenarios is comprehensively evaluated. The results show that by optimizing thecharging and discharging modes and ratios of fuel cell systems, the energy optimization allocation strategy designed based on TD3 algo?rithm performs better than traditional algorithms in improving energy allocation efficiency, shortening response time, and reducing operat?ing costs. The research results have verified the efficient adaptability of TD3 algorithm in dealing with fluctuations in renewable energygeneration power output and changes in load demand, and it has wide applicability in practical energy management scenarios. |
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