复杂有源配电网供电路径快速优化

doi:10.19595/j.cnki.1000-6753.tces.151769

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (19177 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract The increasing complexity of network structure and the uncertainty of distributed generation wide access bring out the power supply route optimization issue in active distribution network. Traditional distribution network reconfiguration methods are hard to meet the rapidity requirements. For the output volatility of wind turbine and photovoltaic power, based on the construction of the probability model of the scene, outputting segmentation is carried out on time scale, and the complex search space is simplified by the trees generation method without duplications. It can avoid repetitive radiation calibration, and reduce the redundancy of the solution space. The model is solved by the improved encoding method and the modified teaching learning based optimization algorithm. The search speed and global optimization ability are improved. Examples demonstrate that the proposed method is fast and effective.

Key words： Distributed generation complexity network reconfiguration the generation of trees without duplication the modified teaching learning based optimization algorithm fast

Received: 18 October 2015 Published: 19 July 2017

PACS:

TM764

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Chi Jiyun
	Wei Gang
	Li Gongxin
	Li Qinyu
	Zhang Jiakun

Cite this article:

Chi Jiyun,Wei Gang,Li Gongxin等. Fast Optimization of Power Supply Route for the Complex Active Distribution Network[J]. Transactions of China Electrotechnical Society, 2017, 32(13): 219-228.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.151769 OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I13/219

[1] 靳小龙, 穆云飞, 贾宏杰, 等. 面向最大供电能力提升的配电网主动重构策略[J]. 电工技术学报, 2014, 29(12): 137-147.
Jin Xiaolong, Mu Yunfei, Jia Hongjie, et al. An active reconfiguration strategy for distribution network based on maximum power supply capabi- lity[J]. Transactions of China Electrotechnical Society, 2014, 29(12): 137-147.
[2] Rao R S, Ravindra K, Satish K, et al. Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation[J]. IEEE Transactions on Power Systems, 2013, 28(1): 317-325.
[3] 李奔, 刘会家, 李珺. 考虑网络结构优化的含风电配电网多目标重构[J]. 电力系统保护与控制, 2015, 43(17): 57-62.
Li Ben, Liu Huijia, Li Jun. Multi-objective reconfiguration of distribution network with wind power generators considering network survivabi- lity[J]. Power System Protection and Control, 2015, 43(17): 57-62.
[4] 蒲天骄, 刘克文, 陈乃仕, 等. 基于主动配电网的城市能源互联网体系架构及其关键技术[J]. 中国电机工程学报, 2015, 35(14): 3511-3521.
Pu Tianjiao, Liu Kewen, Chen Naishi, et al. Design of ADN based urban energy internet architecture and its technological issues[J]. Proceedings of the CSEE, 2015, 35(14): 3511-3521.
[5] 张建华, 曾博, 张玉莹, 等. 主动配电网规划关键问题与研究展望[J]. 电工技术学报, 2014, 29(2): 13-23.
Zhang Jianhua, Zeng Bo, Zhang Yuying, et al. Key issues and research prospects of active distribution network planning[J]. Transactions of China Electro- technical Society, 2014, 29(2): 13-23.
[6] 王佳佳, 吕林, 刘俊勇, 等. 基于改进分层前推回代法的含分布发电单元的配电网重构[J]. 电网技术, 2010, 34(9): 60-64.
Wang Jiajia, Lü Lin, Liu Junyong, et al. Reconfiguration of distribution network containing distribution generation units based on improved layered forward-backward sweep method[J]. Power System Technology, 2010, 34(9): 60-64.
[7] 赵晶晶, 李新, 彭怡, 等. 基于粒子群优化算法的配电网重构和分布式电源注入功率综合优化算法[J]. 电网技术, 2009, 33(17): 162-166.
Zhao Jingjing, Li Xin, Peng Yi, et al. A com- prehensive optimization algorithm for injection power of distributed generation and distribution network reconfiguration based on particle swarm optimization[J]. Power System Technology, 2009, 33(17): 162-166.
[8] Wu Y K, Lee C Y, Liu L C, et al. Study of reconfiguration for the distribution system with distributed generators[J]. IEEE Transactions on Power Delivery, 2010, 25(3): 1678-1685.
[9] De M B H D, De Souza B A. Distribution network reconfiguration using genetic algorithms with sequ- ential encoding: subtractive and additive approaches[J]. IEEE Transactions on Power Systems, 2011, 26(2): 582-593.
[10] 李锰, 黄泽华, 曾业运, 等. 基于信息集成的配电网关键负荷保障[J]. 电工技术学报, 2014, 29(增刊1): 481-485.
Li Meng, Huang Zehua, Zeng Yeyun, et al. The security of the critical load in the distribution network based on information integration[J]. Transactions of China Electrotechnical Society, 2014, 29(S1): 481-485.
[11] 张涛, 史苏怡, 徐雪琴. 基于二进制量子粒子群算法的含分布式电源配电网重构[J]. 电力系统保护与控制, 2016, 44(4): 22-28.
Zhang Tao, Shi Suyi, Xu Xueqin. Distribution network reconfiguration with distributed generation based on improved quantum binary particle swarm optimization[J]. Power System Protection and Control, 2016, 44(4): 22-28.
[12] 卢扬, 吴俊勇, 郝亮亮. 基于改进MOBPSO算法的含分布式电源的多目标配电网重构[J]. 电力系统保护与控制, 2016, 44(7): 62-68.
Lu Yang, Wu Junyong, Hao Liangliang. Multi- objective distribution network reconfiguration with distributed generations based on improved MOBPSO algorithm[J]. Power System Protection and Control, 2016, 44(7): 62-68.
[13] 李振坤, 周伟杰, 钱啸, 等. 有源配电网孤岛恢复供电及黑启动策略研究[J]. 电工技术学报, 2015, 30(21): 67-75.
Li Zhenkun, Zhou Weijie, Qian Xiao, et al. Distribution network restoration and black start based on distributed generators[J]. Transactions of China Electrotechnical Society, 2015, 30(21): 67-75.
[14] Kavousi-Fard A, Niknam T, Fotuhi-Firuzabad M. Stochastic reconfiguration and optimal coordination of V2G plug-in electric vehicles considering correlated wind power generation[J]. IEEE Transa- ctions on Sustainable Energy, 2015, 6: 1-9.
[15] 曾博, 刘念, 张玉莹, 等. 促进间歇性分布式电源高效利用的主动配电网双层场景规划方法[J]. 电工技术学报, 2013, 28(9): 155-163.
Zeng Bo, Liu Nian, Zhang Yuying, et al. Bi-levelscenario programming of active distribution network for promoting intermittent distributed gener- ationutilization[J]. Transactions of China Electro- technical Society, 2013, 28(9): 155-163.
[16] Bernardon D P, Mello A P C, Pfitscher L L, et al. Real-time reconfiguration of distribution network with distributed generation[J]. Electric Power Systems Research, 2014, 107(2): 59-67.
[17] Mayeda W, Seshu S. Generation of trees without duplications[J]. IEEE Transactions on Circuit Theory, 1965, 12(2): 181-185.
[18] Xing H, Cheng H, Zhang Y. Optimal coordination of intermittent distributed generation with probabilistic power flow[J]. Journal of Electrical Engineering & Technology, 2015, 10(6): 2211-2220.
[19] 王晓龙. 基于两点估计法的电力系统概率潮流计算[D]. 太原: 太原理工大学, 2013.
[20] Rao R V, Savsani V J, Vakharia D P. Teaching- learning-based optimization: an optimization method for continuous non-linear large scale problems[J]. Information Sciences, 2012, 183(1): 1-15.
[21] Sultana S, Roy P K. Optimal capacitor placement in radial distribution systems using teaching learning based optimization[J]. International Journal of Electrical Power & Energy Systems, 2014, 54(1): 387-398.
[22] Meneses d Q P, Contreras J, Rider M J, et al. Contingency assessment and network reconfiguration in distribution grids including wind power and energy storage[J]. IEEE Transactions on Sustainable Energy, 2015, 6(4): 1524-1533.
[23] 黄红程, 顾洁, 方陈. 基于无向生成树的并行遗传算法在配电网重构中的应用[J]. 电力系统自动化, 2015, 39(14): 89-96.
Huang Hongcheng, Gu Jie, Fang Chen. Application of undirected spanning tree-based parallel genetic algorithm in distributed network reconfiguration[J]. Automation of Electric Power Systems, 2015, 39(14): 89-96.
[24] Cebrian J C, Kagan N. Reconfiguration of distri- bution networks to minimize loss and disruption costs using genetic algorithms[J]. Electric Power Systems Research, 2010, 80(1): 53-62.
[25] Yin S A, Lu C N. Distribution feeder scheduling considering variable load profile and outage costs[J]. IEEE Transactions on Power Systems, 2009, 24(2): 652-660.