Distributionally robust optimal dispatching of integrated energy system considering line pack effect of gas network

被引：0
作者：
Yi W. [1 ]
Bu Q. [1 ]
Lu S. [2 ]
Qin Y. [3 ]
Li P. [3 ]
机构：
[1] Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd., Nanjing
[2] School of Electrical Engineering, Southeast University, Nanjing
[3] School of Automation, Nanjing University of Science and Technology, Nanjing
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2022年 / 42卷 / 06期
关键词：
Column-and-constraint generation algorithm; Distributionally robust optimization; Integrated energy system; Line pack of gas network; Uncertainty;
D O I：
10.16081/j.epae.202203024
中图分类号：
学科分类号：
摘要：
The IES(Integrated Energy System) integrated with renewable energy has the feature of uncertainty, while the solution methods such as stochastic programming and robust optimization suffer from insufficient robustness or high conservation. As the important flexible resources for IES, the line pack of gas network is effective in alleviating the influence of uncertainty. For that, the distributionally robust optimal dispatching method of IES considering the line pack of gas network is proposed. The consumption of renewable energy is promoted and the safe and stable operation of system is realized by making full use of the flexible resour-ces of system. On the basis of analyzing gas flow characteristics in natural gas pipeline and line pack effect, the optimal dispatching model of IES considering the line pack effect of gas network is proposed to minimize the integrated cost. In view of the different characteristics of uncertainty for wind power output and electric load, the probability distribution set and trapezoidal fuzzy function are employed respectively to depict these two kinds of uncertainty factors. On this basis, the distributionally robust optimal dispatching model of IES is established and solved by the column-and-constraint generation algorithm. Finally, the case analysis verifies the accuracy and effectiveness of the proposed method, and the results show that the proposed method has stronger regulation ability and excellent economy under uncertain scenarios. © 2022, Electric Power Automation Equipment Press. All right reserved.
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页码：53 / 60and83
页数：6030
相关论文
共 25 条
  • [21] DING T, YANG Q R, YANG Y H, Et al., A data-driven stoc-hastic reactive power optimization considering uncertainties in active distribution networks and decomposition method, IEEE Transactions on Smart Grid, 9, 5, pp. 4994-5004, (2018)
  • [22] LIU Wenxue, LIANG Jun, YUN Zhihao, Et al., Multi-objective fuzzy chance constrained optimal reactive power flow based on credibility theory, Transactions of China Electrotechnical Society, 30, 21, pp. 82-89, (2015)
  • [23] LI Guoqing, LI Xintong, BIAN Jing, Et al., Two level schedu-ling strategy for inter-provincial DC power grid considering the uncertainty of PV-load prediction, Proceedings of the CSEE, 41, 14, pp. 4763-4776, (2021)
  • [24] DE WOLF D, SMEERS Y., The gas transmission problem solved by an extension of the simplex algorithm, Manage-ment Science, 46, 11, pp. 1454-1465, (2000)
  • [25] DONG Shuai, WANG Chengfu, XU Shijie, Et al., Day-ahead optimal scheduling of electricity-gas-heat integrated energy system considering dynamic characteristics of networks, Automation of Electric Power Systems, 42, 13, pp. 12-19, (2018)
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