樊安洁,高正平,张文嘉,黄河,高松
FAN Anjie,GAO Zhengping,ZHANG Wenjia,HUANG he,GAO Song

• 1:国网江苏省电力有限公司经济技术研究院
• 2:国网江苏省电力有限公司

摘要(Abstract)：

在构建新型电力系统背景下，配电网在规划期内面临多时间尺度不确定性因素的影响，将对最终规划方案的可行性和经济性产生巨大影响。因此将多元不确定性因素建模为多阶段混合场景树，并在此基础上，考虑大规模新能源消纳与系统可靠性需求，构建高压交直流混合配电网的多阶段概率随机规划模型。针对大规模混合整数规划模型中海量场景导致的求解维数灾问题，提出一种改进Benders分解算法，对原始模型进行解耦与高效求解。最后，通过实际高压配电系统的算例分析，验证了所建立规划模型的有效性和优越性。与现有规划方法相比，所建立方法可以提升系统对多维不确定性因素的适应性，提升新能源消纳水平，并降低规划总成本。
In the context of constructing a new-type power system, distribution networks face the impact of multitimescale uncertainties during the planning period, which significantly affects the feasibility and economic efficiency of the final planning scheme. To address this, multi-dimensional uncertainties are modeled as a multi-stage hybrid scenario tree. Based on this model, a multi-stage probabilistic-stochastic planning model is proposed for hybrid high-voltage AC/DC distribution networks, taking into account large-scale new energy consumption and system reliability requirements. To resolve curse of dimensionality caused by the massive number of scenarios in the largescale mixed integer programming model, an improved Benders decomposition algorithm is proposed to decouple and efficiently solve the original model. Finally, the effectiveness and advantages of the proposed planning model are validated through case studies of a high-voltage distribution system. Compared to existing planning methods, the proposed method enhances the system′s adaptability to multi-dimensional uncertainties, improves new energy consumption levels, and reduces total planning costs.

关键词(KeyWords)： 高压交直流混合配电网;长短期不确定性;概率规划;混合整数线性模型
hybrid high-voltage AC/DC distribution networks;long-and short-term uncertainty;probabilistic planning;mixed integer linear model

Abstract:

Keywords:

基金项目(Foundation): 国网江苏省电力有限公司科技项目（J2023165）

作者(Author): 樊安洁,高正平,张文嘉,黄河,高松
FAN Anjie,GAO Zhengping,ZHANG Wenjia,HUANG he,GAO Song

DOI: 10.19585/j.zjdl.202505002

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