Flexible Interconnection Planning of Low-voltage Station Area Distribution Network Consid-ering Power Supply Capacity Improvement
朱建昆 1高红均 1贺帅佳 1李海波 2刘俊勇1
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作者信息
1. 四川大学电气工程学院,成都 610065
2. 清华四川能源互联网研究院,成都 610042
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摘要
构建具有可靠供电能力的低压配电网具有重要意义,然而低压配电网供电能力受到低压配电变压器负载、低压配电网新能源消纳能力以及低压配电网供电电压 3大要素影响.因此,该文基于低压配电网柔性互联技术提出考虑供电能力提升的低压配电网柔性互联规划方法,通过抽取影响低压配电网供电能力的主要场景建立低压配电网柔性互联规划框架.另外,针对该文多主体规划运行模型的不确定性,采用信息间隙决策理论(information gap decision theory,IGDT)与基于Wasserstein距离的分布鲁棒方法进行精细化建模.最后,采用MATLAB和CPLEX求解器在IEEE 38节点配电网上进行算例分析.仿真结果表明,该规划方法在有效提升低压配电网供电能力的同时具有更好的经济性.
Abstract
It is important to build a low-voltage distribution network with reliable power supply capacity,however,the power supply capacity of low-voltage distribution network is affected by three major factors,namely,the load of distribu-tion transformers in the station area,the capacity of new energy consumption in the station area,and the voltage supply in the station area distribution network.Therefore,this paper proposes a flexible interconnection planning method for low-voltage distribution networks based on the flexible interconnection technology of station area distribution networks,and establishes a flexible interconnection planning framework for low-voltage distribution networks by extracting the main scenarios affecting the power supply capacity of low-voltage distribution networks.In addition,for the uncertainty of the multi-subject planning operation model in this paper,the information gap decision theory(IGDT)and the Wasser-stein distance-based distribution robustness method are used for refinement modeling.Finally,the MATLAB and the CPLEX solver are used to analyze the arithmetic cases on the IEEE 38-node distribution network.The simulation results show that the planning method has better economy while effectively improving the power supply capacity of the distribu-tion network in the low-voltage station area.
关键词
低压配电网/供电能力/柔性互联/多主体不确定性/信息间隙决策理论/分布鲁棒
Key words
low-voltage distribution network/power supply capacity/flexible interconnection/multi-subject uncertainty/information gap decision theory/distribution robustness
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