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针对高比例分布式新能源接入配电网后，常规的解耦电压控制、最大化消纳控制等方式已不能满足高比例新能源并网条件下配电网控制需求的问题，综合考虑配电网运行的经济性、新能源消纳和电压合格率，将分时电价、系统损耗和相关经济损失相结合，提出一种新型评估主动配电网智能体整体经济效益的奖励函数，构建了含高渗透率分布式光伏的配电网控制数学模型，在基于深度强化学习的源荷储协同控制技术下提升主动配电网智能体的动作效果。通过对IEEE 33节点模型进行仿真分析，验证了基于深度强化学习的配电网源荷储协同优化控制技术的有效性，最大电压波动的标幺值降低了0.029 7，最大线损降低了26.09%，光伏消纳率提高了4.73%。
Abstract：With the high proportion of distributed new energy aceess to the distribution network, the conventional decoupling voltage control, maximum consumption control and other methods can not meet the distribution network control needs under the condition of high proportion of new energy integration. Considering the operational economy, new energy consumption and voltage qualification rate of the distribution network, a new reward function for evaluating the overall economic benefits of active distribution network intelligent agents is proposed by combining time-of-use electricity prices, system losses and related economic losses. A distribution network control mathematical model containing high penetration distributed photovoltaics is constructed to improve the action effect of active distribution network agents under the source-load-storage collaborative control technology based on deep reinforcement learning. Through case analysis of the IEEE 33-node model, the universal applicability of distribution network source-load-storage collaborative optimization control technology based on deep reinforcement learning is verified in improving photovoltaic consumption rate, reducing line loss and suppressing voltage fluctuations. The per unit value of maximum voltage fluctuation decreases by 0.029 7. The maximum line loss decreases by 26.09%, and the photovoltaic consumption rate increases by 4.73%.
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基本信息:
DOI：10.19929/j.cnki.nmgdljs.2025.0049
中图分类号:
引用信息:
[1]齐军1,马鹏1,周生存2,等.基于深度强化学习的新型终端配电网源荷储协同控制[J],2025,43(4):56-67.DOI:10.19929/j.cnki.nmgdljs.2025.0049.
基金信息:
内蒙古电力（集团）有限责任公司阿拉善供电分公司科技项目“园区级配电网源网荷储协同控制技术与示范应用项目（二次） ”（ALSYS-2023-5-016）