Optimal energy flow method of integrated energy system based on Sinkhorn distribution robust optimization

被引：0
|
作者：
Wei C. [1 ]
Jiang F. [1 ]
Wang Y. [1 ]
Bai X. [2 ]
机构：
[1] Department of Information Engineering, Zhejiang University of Technology, Hangzhou
[2] Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2024年 / 44卷 / 05期
基金：
中国国家自然科学基金;
关键词：
fuzzy uncertainty set; integrated energy system; optimal energy flow; robust optimization; uncertainty of wind power;
D O I：
10.16081/j.epae.202312009
中图分类号：
学科分类号：
摘要：
Aiming at the uncertainty problem brought by wind power access to the integrated energy system, a dynamic optimal energy flow model and solution method based on Sinkhorn distribution robust optimization are proposed. The uncertainty of wind power is described as a fuzzy uncertainty set containing probability distribution information,and it is constructed as a Sinkhorn sphere with the empirical distribution of wind power output as the center and the Sinkhorn distance as the radius. Then,a batch gradient descent method of binary search is used to solve the problem in order to reduce the impact of wind power uncertainty and the computational complexity. The results of case study show that the proposed method can effectively balance the robustness and economy of system compared with the stochastic optimization and traditional robust optimization. Moreover,the computational time and objective function of the proposed method are better than those of the Wasserstein method under different sample scales. © 2024 Electric Power Automation Equipment Press. All rights reserved.
引用
收藏
页码：28 / 35
页数：7
相关论文
共 21 条
  • [1] WANG C S, LV C X, LI P, Et al., Modeling and optimal operation of community integrated energy systems:a case study from China[J], Applied Energy, 230, pp. 1242-1254, (2018)
  • [2] YUAN Xiaohui, YUAN Yanbin, ZHANG Yongchuan, A survey of modern intelligence optimization methods for unit commitment in electric power systems, Electric Power Automation Equipment, 23, 2, pp. 73-78, (2003)
  • [3] WANG Bao, XU Jian, SUN Yuanzhang, Et al., Stochastic dynamic economic dispatch of power systems considering wind power based on versatile probability distribution, Automation of Electric Power Systems, 40, 6, pp. 17-24, (2016)
  • [4] AHMADI-KHATIR A, CONEJO A J, CHERKAOUI R., Multi-area energy and reserve dispatch under wind uncertainty and equipment failures, IEEE Transactions on Power Systems, 28, 4, pp. 4373-4383, (2013)
  • [5] JABR R A., Adjustable robust OPF with renewable energy sources, IEEE Transactions on Power Systems, 28, 4, pp. 4742-4751, (2013)
  • [6] WANG Chaoqun, WEI Hua, WU Siyuan, Stochastic-security-constrained unit commitment considering uncertainty of wind power [J], Power System Technology, 41, 5, pp. 1419-1427, (2017)
  • [7] ZHANG Qianwen, WANG Xiuli, YANG Tingtian, Et al., A robust dispatch method for power grid with wind farms, Power System Technology, 41, 5, pp. 1451-1463, (2017)
  • [8] PENG Chunhua, CHEN Jing, ZHENG Cong, Robust economic dispatch of CSP-CHPMG based on chance constrained Gaussian mixture model [J], Electric Power Automation Equipment, 41, 4, pp. 77-84, (2021)
  • [9] GAO Xiaosong, LI Gengfeng, XIAO Yao, Et al., Day-ahead economical dispatch of electricity-gas-heat integrated energy system based on distributionally robust optimization, Power System Technology, 44, 6, pp. 2245-2254, (2020)
  • [10] ZHANG Shang, GU Xueping, WANG Tao, Static security corrective control method of wind power-integrated system based on distributional robust optimization, Electric Power Automation Equipment, 39, 2, pp. 58-64, (2019)
123