Optimization model of selecting power supply reliability reconstruction measures in large-scale MV distribution network and its solution method

被引：0
|
作者：
Su Y. [1 ]
Liu J. [1 ]
Liu Y. [1 ]
Cheng S. [2 ]
Gao H. [1 ]
Ding L. [1 ]
机构：
[1] Department of Electrical Information, Sichuan University, Chengdu, 610065, Sichuan Province
[2] State Grid Chengdu Power Supply Company, Chengdu, 610041, Sichuan Province
来源：
| 2017年 / Power System Technology Press卷 / 41期
关键词：
Large-scale distribution network; Reconstruction; Reliability;
D O I：
10.13335/j.1000-3673.pst.2016.0276
中图分类号：
学科分类号：
摘要：
Distribution network reconstruction is in vigorous progress in China with reliability enhancement as one of its core targets. In order to deal with large amount of candidate measures, an optimal selection model used for large-scale distribution network is established and its solving method is designed in this paper. Firstly, an improved approximate evaluation algorithm for reliability indices is proposed so that system reliability enhancement from various reconstruction measures can be calculated with continuous derivable functions. Then, on this basis, optimization model is established, taking investment cost and power outage cost as objectives and meeting reliability requirements in each area as constraints. The model is solved with a combinatorial optimization algorithm based on genetic algorithm and branch and bound method after classifying variables. Finally, solution quality and stability is verified with a city distribution network case study. Because correlations between multiple areas and multiple reconstruction measures are considered in the proposed model, it can maximize fund savings and bring social economic benefits in distribution network. © 2017, Power System Technology Press. All right reserved.
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页码：201 / 209
页数：8
相关论文
共 20 条
  • [1] Feng M., Xie N., Wang C., Et al., Reliability planning of distribution power network considering the characteristics of short-term peak load, Power System Technology, 39, 3, pp. 757-762, (2014)
  • [2] Samper M.E., Vargas A., Investment decisions in distribution networks under uncertainty with distributed generation, part I: model formulation, IEEE Transactions on Power Systems, 28, 3, pp. 2331-2340, (2013)
  • [3] Martins V.F., Borges C.L.T., Active distribution network integrated planning incorporating distributed generation and load response uncertainties, IEEE Transactions on Power Systems, 26, 4, pp. 2164-2172, (2011)
  • [4] Bagheri A., Monsef H., Lesani H., Integrated distribution network expansion planning incorporating distributed generation considering uncertainties, reliability, and operational conditions, International Journal of Electrical Power & Energy Systems, 73, pp. 56-70, (2015)
  • [5] Ziari I., Ledwich G., Ghosh A., Et al., Integrated distribution systems planning to improve reliability under load growth, IEEE Transactions on Power Delivery, 27, 2, pp. 757-765, (2012)
  • [6] Ziari I., Ledwich G., Ghosh A., Optimal distribution network reinforcement considering load growth, line loss, and reliability, IEEE Transactions on Power Systems, 28, 2, pp. 587-597, (2013)
  • [7] Wang G., Xie K., Hu B., Et al., A reliability level tree algorithm for reliability evaluation of medium voltage distribution networks, Power System Technology, 35, 12, pp. 77-82, (2011)
  • [8] Chen C., Wu W., Zhang B., Et al., Reliability evaluation for large-scale distribution network based on component groups, Power System Technology, 36, 8, pp. 81-86, (2012)
  • [9] Liang H., Cheng L., Liu S., Monte Carlo simulation based reliability evaluation of distribution system containing microgrids, Power System Technology, 35, 10, pp. 76-81, (2011)
  • [10] Wang Y., Chen G., Zhang J., Et al., Optimal switching device placement based on niche genetic algorithm in distribution network, Transactions of China Electrotechnical Society, 21, 5, pp. 82-86, (2006)
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