付文龙, 卓庆澳, 吴月超, 方念, 张海荣, 陈曦. 多能互补提供频率支撑的储能容量分布鲁棒规划方法[J]. 电网技术, 2024, 48(1): 282-290. DOI: 10.13335/j.1000-3673.pst.2023.0804
引用本文: 付文龙, 卓庆澳, 吴月超, 方念, 张海荣, 陈曦. 多能互补提供频率支撑的储能容量分布鲁棒规划方法[J]. 电网技术, 2024, 48(1): 282-290. DOI: 10.13335/j.1000-3673.pst.2023.0804
FU Wenlong, ZHUO Qingao, WU Yuechao, FANG Nian, ZHANG Hairong, CHEN Xi. Distributed Robust Planning for Energy Storage Capacity With Multi-energy Complementarity Providing Frequency Support[J]. Power System Technology, 2024, 48(1): 282-290. DOI: 10.13335/j.1000-3673.pst.2023.0804
Citation: FU Wenlong, ZHUO Qingao, WU Yuechao, FANG Nian, ZHANG Hairong, CHEN Xi. Distributed Robust Planning for Energy Storage Capacity With Multi-energy Complementarity Providing Frequency Support[J]. Power System Technology, 2024, 48(1): 282-290. DOI: 10.13335/j.1000-3673.pst.2023.0804

多能互补提供频率支撑的储能容量分布鲁棒规划方法

Distributed Robust Planning for Energy Storage Capacity With Multi-energy Complementarity Providing Frequency Support

  • 摘要: 随着具有不确定性的新能源大规模并网,电力系统的频率安全面临严峻挑战,而合理规划储能是维持电力系统稳定运行和应对可再生能源不确定性的重要手段。为此,针对高可再生能源渗透率系统的储能容量规划问题,提出了一种考虑多能互补提供频率支撑的储能容量分布鲁棒规划方法。首先,建立了多能互补提供频率支撑的频率安全模型,并将其线性化后嵌入到典型日运行中,以维护电力系统频率的稳定性。其次,采用基于生成对抗网络的分布鲁棒优化,实现在新能源出力最劣概率分布下的储能容量规划,以应对新能源出力的不确定性。最后,基于IEEE39节点系统进行算例分析,验证了所提方法可在保证电力系统频率安全的同时,具有较好的经济性和鲁棒性。

     

    Abstract: With the large-scale integration of uncertain renewable energy sources into power systems, the frequency stability of the power system is facing severe challenges. Reasonable planning of the energy storage is an important means for maintaining the stable operation of the power system and coping with the uncertainty of renewable energy sources. Therefore, focusing on the planning problem of the energy storage capacity for the power system with high renewable energy penetration, a distributed robust planning for the energy storage capacity is proposed while providing frequency support by the multi-energy complementarity. Firstly, a frequency safety model with frequency support provided by the multi-energy complementarity is established, which is then linearized and embedded into the typical daily operation to maintain the frequency stability of the power system. Secondly, the distributed robust optimization based on the generative adversarial network is adopted to achieve the energy storage capacity planning under the worst probability distribution of the new energy output and to deal with the uncertainty of the new energy output. Finally, simulation with the IEEE39 node system verifies that the proposed method is able to ensure the frequency security of the power system and possess a good economy and robustness.

     

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