Day-ahead Optimal Scheduling and Operating of Active Distribution Network Considering Violation Risk

被引：0
|
作者：
Fu Y. [1 ]
Liao J. [1 ]
Li Z. [1 ]
Qian X. [2 ]
Tang X. [2 ]
机构：
[1] School of Electric Power Engineering, Shanghai University of Electric Power, Yangpu District, Shanghai
[2] Jiaxing Power Supply Company of State Grid Zhejiang Electric Power Company, Jiaxing, 314000, Zhejiang Province
来源：
| 1600年 / Chinese Society for Electrical Engineering卷 / 37期
基金：
中国国家自然科学基金;
关键词：
Active distribution network; Active management; Day-ahead scheduling; Violation risk;
D O I：
10.13334/j.0258-8013.pcsee.162014
中图分类号：
学科分类号：
摘要：
The efficient utilization of renewable energy generation and optimal operation of network are the core values of active distribution network (ADN). However, the multiple timing fluctuation and uncertainty of load, wind and solar resources bring challenges to the optimal scheduling. In this paper, a new day-ahead optimal scheduling and operating method for ADN considering violation risk was proposed. In day-ahead stage, operation violation risk resulted from uncertainty of load, wind and solar resources was considered. Scheduling scheme's economy and security were both taken into account, and a multi-objective day-ahead optimal scheduling model aiming at the minimum of operation cost and violation risk was established. The scheduling means of ADN include energy storage system, distributed generation, reactive power and voltage equipment, flexible network topology. Ideal point method was used to deal with the multi-objective model. The optimization problem was solved by harmony search algorithm, and the violation risk index was calculated based on probabilistic power flow method of cumulant. Finally, a case study was provided to verify the correctness and superiority of the proposed scheduling method. © 2017 Chin. Soc. for Elec. Eng.
引用
收藏
页码：6328 / 6338
页数：10
相关论文
共 22 条
  • [1] You Y., Liu D., Yu W., Et al., Technology and its trends of active distribution network, Automation of Electric Power Systems, 36, 18, pp. 10-16, (2012)
  • [2] Liu D., Chen Y., Huang Y., Et al., Hierarchical energy management and coordination control of active distribution network, Proceedings of the CSEE, 34, 31, pp. 5500-5506, (2014)
  • [3] Dong L., Chen H., Pu T., Et al., Multi-time scale dynamic optimal dispatch in active distribution network based on model predictive control, Proceedings of the CSEE, 36, 17, pp. 4609-4616, (2016)
  • [4] Zhang J., Yang X., Wang D., Et al., Short-term scheduling of active distribution network integrated with electric vehicle battery swap stations, Proceedings of 2014 IEEE Conference and Expo Transportation Electrification Asia-Pacific(ITEC Asia-Pacific), pp. 1-6, (2014)
  • [5] You Y., Liu D., Zhang Q., Et al., Research on optimal schedule strategy for active distribution network, Automation of Electric Power Systems, 38, 9, pp. 177-183, (2014)
  • [6] Gao Y., Research on intentional islangding and day ahead schedule optimal dispach of active distribution network, (2013)
  • [7] Soroudi A., Siano P., Keane A., Optimal DR and ESS scheduling for distribution losses payments minimization under electricity price uncertainty, IEEE Transactions on Smart Grid, 7, 1, pp. 261-272, (2016)
  • [8] Borghetti A., Bosetti M., Grillo S., Et al., Short-term scheduling of active distribution systems, Proceedings of 2009 IEEE Bucharest PowerTech, pp. 1-7, (2009)
  • [9] Nick M., Cherkaoui R., Paolone M., Stochastic day-ahead optimal scheduling of active distribution networks with dispersed energy storage and renewable resources, Proceedings of 2014 IEEE Conference on Technologies for Sustainability(SusTech), pp. 91-96, (2014)
  • [10] Meng X., Zhang L., Cong P., Et al., Dynamic reconfiguration of distribution network considering scheduling of DG active power outputs, Proceedings of 2014 International Conference on Power System Technology, pp. 1433-1439, (2014)
123