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考虑节能效益的企业分布式电源优化配置
引用本文:田贺平,孙舟,王伟贤,李香龙. 考虑节能效益的企业分布式电源优化配置[J]. 电力系统保护与控制, 2017, 45(10): 38-47
作者姓名:田贺平  孙舟  王伟贤  李香龙
作者单位:国网北京市电力公司电力科学研究院,北京 100075,国网北京市电力公司电力科学研究院,北京 100075,国网北京市电力公司电力科学研究院,北京 100075,国网北京市电力公司电力科学研究院,北京 100075
摘    要:针对企业供配电系统分布式电源规划问题,以企业节能效益最大化为目标,建立企业分布式电源优化配置模型。采用改进粒子群算法进行求解,将参数自适应调节、粒子交叉、模拟退火算法融入粒子群算法,有效提高了粒子群算法的寻优效率。采用IEEE33节点配电系统进行了算例仿真分析,仿真结果表明,利用此模型对分布式电源进行优化配置后,配电网损耗降低、电压质量显著提高、企业节能经济效益得到最大化提升。算例有效验证了优化配置模型与改进粒子群算法的可行性。

关 键 词:企业节能;分布式电源优化配置;改进粒子群算法
收稿时间:2016-03-31
修稿时间:2016-08-25

Enterprises distributed power optimization allocation considering energy-saving benefit
TIAN Heping,SUN Zhou,WANG Weixian and LI Xianglong. Enterprises distributed power optimization allocation considering energy-saving benefit[J]. Power System Protection and Control, 2017, 45(10): 38-47
Authors:TIAN Heping  SUN Zhou  WANG Weixian  LI Xianglong
Affiliation:State Grid Beijing Electric Power Research Institute, Beijing 100075, China,State Grid Beijing Electric Power Research Institute, Beijing 100075, China,State Grid Beijing Electric Power Research Institute, Beijing 100075, China and State Grid Beijing Electric Power Research Institute, Beijing 100075, China
Abstract:In allusion to the distributed power planning of enterprises power supply and distribution system, this paper establishes distributed power optimal allocation model which maximizes energy saving benefits. Improved particle swarm optimization algorithm is used to solve the problem, in which integrates parameter adaptive adjustment, particle cross, simulated annealing algorithm into particle swarm algorithm to improve its optimization efficiency. The IEEE33 node distribution system is simulated and analyzed. Simulation results show that using the proposed model to optimize configuration of distributed power supply, distribution network loss is reduced, voltage quality is significantly improved, and energy-saving economic benefits of the enterprises are maximized. Case analysis effectively verifies the feasibility of optimal allocation model and improved particle swarm optimization algorithm.
Keywords:enterprises energy saving   distributed power optimization allocation   improved particle swarm optimization algorithm
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