Optimization and Control of Voltage Security in Active Distribution Network Considering Global Correlation

被引:0
|
作者
Chen Z. [1 ]
Gu D. [1 ]
Guo Q. [1 ]
机构
[1] School of Electrical Engineering, Southeast University, Nanjing
基金
中国国家自然科学基金;
关键词
active distribution network (ADN); optimal control; Sobol’method; uncertainty; voltage stability;
D O I
10.7500/AEPS20230324009
中图分类号
学科分类号
摘要
In the new power system, the uncertainty of large-scale distributed renewable energy on the distribution network side makes the security problems of voltage increasingly prominent. The existing methods mainly assume that the random variables follow independent distribution, and seldom consider the correlation between random distributions. However, the correlation of random variables on the distribution network side is strong, which reduces the voltage control effect. An optimization and control strategy of voltage stability in active distribution network considering global sensitivity is proposed. Firstly, L index is used to measure the voltage stability of the system, and a probabilistic power flow model considering the stability of power systems in multi-scenarios is constructed. Secondly, based on the global sensitivity of Sobol’method, the influence of uncertainty of input variables and correlation between variables on voltage stability is quantitatively analyzed. Then, based on the results of sensitivity analysis, the control equipment in the solution system is optimized. Finally, the simulation is carried out in the modified IEEE 33-bus system, IEEE 118-bus system and actual system. The results show that the optimization and control strategy in multi-stochastic scenarios based on global sensitivity can realize the efficient utilization of the control equipment in different operation scenarios and support the safe operation of the active distribution network while considering the multi-variable correlation. © 2023 Automation of Electric Power Systems Press. All rights reserved.
引用
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页码:99 / 107
页数:8
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共 28 条
  • [1] CHEN Guangyu, WU Wenlong, DAI Zemei, Et al., Multi-objective optimization of regional reactive power reserve in hybrid wind-solar storage system considering fault scenario set[J], Automation of Electric Power Systems, 46, 17, pp. 194-204, (2022)
  • [2] YANG Bo, CHEN Yijun, YAO Wei, Et al., Review on stability assessment and decision for power systems based on new-generation artificial intelligence technology[J], Automation of Electric Power Systems, 46, 22, pp. 200-223, (2022)
  • [3] VOURNAS C., An optimization framework for voltage stability support from active distribution networks[J], Electric Power Systems Research, 211, (2022)
  • [4] ZHANG Zhe, QIN Boyu, GAO Xin, Et al., Emergency control strategy of power grid voltage stability based on convolutional neural network and long short-term memory network [J], Automation of Electric Power Systems, 47, 11, pp. 60-68, (2023)
  • [5] Coordinated active and reactive power control for distribution networks with high penetrations of photovoltaic systems[J], Solar Energy, 231, pp. 809-827, (2022)
  • [6] SOUZA L J., Voltage stability and thermal limit:constraints on the maximum loading of electrical energy distribution feeders [J], IEE Proceedings-Generation,Transmission and Distribution, 145, 5, pp. 573-577, (1998)
  • [7] Energy storage facilities impact on flexibility of active distribution networks:stochastic approach [J], Electric Power Systems Research, 213, (2022)
  • [8] Expansion planning of active distribution networks achieving their dispatchability via energy storage systems[J], Applied Energy, 326, (2022)
  • [9] WANG Shouxiang, LI Qi, ZHAO Qianyu, Et al., Improved particle swarm optimization algorithm for multi-objective voltage optimization of AC/DC distribution network considering the randomness of source and loads[J], Proceedings of the CSUEPSA, 33, 12, pp. 10-17, (2021)
  • [10] MA Zhigang, WEI Zhinong, CHEN Sheng, Et al., Active-reactive power optimal dispatch of AC/DC distribution network based on soft open point[J], Automation of Electric Power Systems, 47, 6, pp. 48-58, (2023)