The Locating and Sizing of Distribution Generation Based on the Distribution Network

Abstract:

According to the national policy of energy conservation and emissions reduction, using renewable resources and new energy to reduce environmental pollution. Reforming power distribution network system for housing estate in taiyuan. Access to distributed power supply, researching the exact location and capacity. By analyzing the distributed generation of the impact of distribution network,the objective function including investment and operating maintenance cost, environmental factors, network loss costs; putting power flow , current, voltage, system capacity constraints as constraint conditions, Using particle swarm optimization (PSO) algorithm with inertia weight, determine the location and capacity of distributed power supply. The proposed method is testified on the IEEE-33 bus system,and get the reasonable installation position and capacity, the simulation results will be used in transformation housing estate in taiyuan.

• Periodical: Applied Mechanics and Materials (Volume 590)
• Pages: 521-525
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.590.521
• Online since: June 2014
• Authors: Xiao Qian Lu*, Ying Nan Xue, Xiao Dong Mi, Xin Hui Du
• Keywords: Distribution Generation (DG), Distribution Network Planning, Multi-Objective Optimization (MOP), Particle Swarm Optimization (PSO)

References

[1] ZHOU Qiao-qiao, TANG Yun-yan, HAI Xiao- tao, etal. Location and Sizing of Distribute Generation Based on Improved Self-adaptive Genetic Algorithm[J]. Shaanxi Electric Power, 2010, 38(6): 40-44.

[2] ZHANG Ting-ting. The distributed power supply's location in distribution network planning and the capacity of research [D]. Southwest jiaotong university, (2010).

[3] CHEN Hao. Research on the effects of distributed power supply for power distribution network loss[J]. Science&Tech- nology Information, 2011, (1): 371-372, 363.

[4] JING Jiang-ping, WEN Jie. Research on Siting and Sizing Grid-connected Distributed Generation Based on Power Circle [J]. Water Resources and Power, 2012, 30(3): 180-183, 80.

[5] XU Lei. Transmission Network Expansion Planning Based on Quantum-behaved Particle Swarm Optimization Algorithm [J]. Science Technology and Engineering, 2012, 12(2): 322- 324.

[6] ZHAO Xingyong, KANG Kai, ZHAO Yan-qiu etal. Optimal Algorithm for Selected Location and Selected Capacity of the Distributed Generation[J]. Electric Power Science And Engineering, 2011, 27(3): 51-54.

[7] LIU Xing. The Multi-objective Optimization of Distribution Generation Based on Quantum Particle Swarms Optimization[D]. North China electric power university, (2012).

[8] QIAN Ke-jun, YUAN Yue, SHI Xiao-dan, etal. Environmental Benefits Analysis of Distributed Generation [J]. Proceedings Of The Chinese Society For Electrical Engineering, 2008, 28(29): 11-15.

[9] LIU Lei, JING Hui, PENG Jian-chun, etal. Impact of Distributed Generation on Distribution System Power Loss and Voltage Profile[J]. Computer Simulation, 2010, 27(4)279 -283.

[10] YANG Mei, DU Xin-hui. Power flow of micro-grid based on back-forward substitution method[J]. ournal of Liaoning Technical University(Natural Science Edition , 2013, (2): 38-41.