引用本文: | 袁杨,张衡,程浩忠,柳璐,张啸虎,励刚,张建平.发输电系统鲁棒优化规划研究综述与展望[J].电力自动化设备,2022,42(1): |
| YUAN Yang,ZHANG Heng,CHENG Haozhong,LIU Lu,ZHANG Xiaohu,LI Gang,ZHANG Jianping.Review and prospect of robust optimization and planning research on generation and transmission system[J].Electric Power Automation Equipment,2022,42(1): |
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摘要: |
随着电力系统不确定性增加,应用发输电系统鲁棒优化规划研究抵御不确定性极端场景已成为重要研究方法。首先从是否计及不确定因素概率分布特征角度,将鲁棒优化分为经典鲁棒优化和分布鲁棒优化,梳理了这2类鲁棒优化的数学模型和不确定集合特征。然后将现有的发输电系统经典鲁棒优化和分布鲁棒优化研究分为考虑节点注入功率不确定性、电源容量增长及成本不确定性、输电网络状态不确定性3个方面,提炼了发输电系统鲁棒优化规划的研究框架和局限性。最后展望了发输电系统鲁棒优化规划值得深入研究的问题,为发输电系统鲁棒优化规划后续研究提供思路和方向。 |
关键词: 发输电系统 优化规划 不确定性 鲁棒优化 分布鲁棒优化 |
DOI:10.16081/j.epae.202108014 |
分类号:TM715 |
基金项目:国家重点研发计划项目(2016YFB0900100) |
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Review and prospect of robust optimization and planning research on generation and transmission system |
YUAN Yang1, ZHANG Heng1, CHENG Haozhong1, LIU Lu1, ZHANG Xiaohu2, LI Gang2, ZHANG Jianping2
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1.Key Laboratory Control of Power Transmission and Conversion, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China;2.East China Branch of State Grid Corporation of China, Shanghai 200120, China
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Abstract: |
With the uncertainty of power system increasing gradually, the application of robust optimization and planning research on generation and transmission system to resist the uncertainty of extremely scenes has become a significant research method. Firstly, the robust optimization is divided into classical robust optimization and distributionally robust optimization from the perspective of whether the probability distribution characteristics of uncertain factors are considered, the mathematical models and uncertain set characteristics of these two kinds of robust optimization are sorted out. Secondly, the existing classical robust optimization and distributionally robust optimization research on generation and transmission system are divided into three aspects: considering the uncertainty of node injection power, considering the uncertainty of power capacity growth and cost, and considering the uncertainty of transmission network state, and the research framework and limitations of robust optimization planning research on generation and transmission system are refined. Finally, the problems worthy of further study in robust optimization planning on power generation and transmission system are prospected, which provides ideas and directions for the robust optimization planning follow-up research on power generation and transmission system. |
Key words: generation and transmission system optimization and planning uncertainty robust optimization distributionally robust optimization |