Optimal power flow calculation including power flow router in distribution network

被引：0
|
作者：
Li C. [1 ]
Wang C. [1 ]
Yin F. [1 ,2 ]
Wang T. [1 ]
机构：
[1] Department of Electrical and Automatic Engineering, Nanchang University, Nanchang
[2] College of Physical Science and Technology Engineering, Yichun University, Yichun
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2019年 / 47卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Distribution network; Latin hypercube sampling; Optimal power flow; Power flow router; Second-order cone relaxation;
D O I：
10.7667/PSPC180348
中图分类号：
学科分类号：
摘要：
In order to solve the problem of limited control range of control elements and scattered control pattern of distribution networks, Power Flow Router (PFR) is applied in distribution networks. An improved branch flow model with power flow routers in distribution networks is proposed and an optimal power flow model including PFR is constructed. Second-order cone relaxation is used to relax the model and the relaxed model is solved by using the commercial algorithm package such as Gurobi. Furthermore, a method, which considers the uncertainty of load and distributed generation's output, is presented based on the combination of Latin hypercube sampling and second-order cone programming. The revised IEEE 33-bus system verifies the effectiveness of the proposed method. © 2019, Power System Protection and Control Press. All right reserved.
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页码：1 / 8
页数：7
相关论文
共 24 条
  • [1] Dommel H.W., Tinney W.F., Optimal power flow solution, IEEE Transactions on Power Apparatus and Systems, 87, pp. 1866-1876, (1968)
  • [2] Zhang X., Zhang Y., Qian W., Et al., Research on the optimal power flow of VSC-HVDC based on the simplified null space interior point method, Power System Protection and Control, 45, 18, pp. 15-23, (2017)
  • [3] Ma L., Yu Q., Liu G., Et al., Power system reactive power optimization based on quantum DE algorithm, Power System Protection and Control, 41, 17, pp. 39-43, (2013)
  • [4] Cai B., Huang S., Multi-objective reactive power optimization based on the multi-objective partial swarm optimization algorithm, Power System Protection and Control, 45, 15, pp. 77-84, (2017)
  • [5] Tang X., Liu H., Fan Y., Et al., Analysis of the optimal dispatch in real-time generation market using an improved multi-objective genetic algorithm, Power System Protection and Control, 45, 17, pp. 65-71, (2017)
  • [6] He T., Wei Z., Sun G., Et al., Modified direct current optimal power flow algorithm based on net loss equivalent load model, Automation of Electric Power Systems, 40, 6, pp. 58-64, (2016)
  • [7] Farivar M., Low S.H., Branch flow model: relaxations and convexification-part I, IEEE Transactions on Power Systems, 28, 3, pp. 2554-2564, (2013)
  • [8] Low S.H., Convex relaxation of optimal power flow-part I: formulations and equivalence, IEEE Transactions on Control of Network Systems, 1, 1, pp. 15-27, (2014)
  • [9] Liu B., Liu F., Mei S., Et al., Optimal power flow in active distribution networks with on-load tap changer based on second-order cone programming, Automation of Electric Power Systems, 39, 19, pp. 40-47, (2015)
  • [10] Gao H., Liu J., Shen X., Et al., Optimal power flow research in active distribution network and its application examples, Proceedings of the CSEE, 37, 6, pp. 1634-1644, (2017)
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