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基于复合粒子群算法的微电网能量管理策略
引用本文:徐科,吴鸣,霍现旭,李国栋,项添春,孙丽敬. 基于复合粒子群算法的微电网能量管理策略[J]. 电测与仪表, 2018, 55(10): 57-61
作者姓名:徐科  吴鸣  霍现旭  李国栋  项添春  孙丽敬
作者单位:国网天津市电力公司,中国电力科学研究院,国网天津市电力公司电力科学研究院,国网天津市电力公司电力科学研究院,国网天津市电力公司电力科学研究院,中国电力科学研究院
摘    要:微网中的部分分布式能源的功率输出具备一定的随机和性间歇性,很大程度上影响了系统的供电稳定性和可靠性,因此,有效的对微网系统进行能量管理显得至关重要。以往的研究中,多采用优化算法在解决能量管理等问题,但其存在着陷入局部最优解等问题,为有效的解决上述问题,本文引入一种复合粒子群优化算法,综合考虑了微网运行过程的经济性、环保特性以及运行可靠性等要求,建立了微电网能量管理多目标优化数学模型,优化目标是运行成本及环境治理的费用最小。在满足功率平衡、分布式电源输出功率等约束条件下,对模型进行了求解,同时,预测系统内负荷需求的变化情况来确定微网的能量管理策略。通过仿真算例的分析验证改进算法的有效性。

关 键 词:微电网  能量管理  复合粒子群算法  多目标优化
收稿时间:2017-06-10
修稿时间:2017-06-10

Energy management strategy of microgrid based on composite particle swarm optimization
Xu Ke,Wu Ming,Hou Xianxu,Li Guodong,Xiang Tianchun and Su Limin. Energy management strategy of microgrid based on composite particle swarm optimization[J]. Electrical Measurement & Instrumentation, 2018, 55(10): 57-61
Authors:Xu Ke  Wu Ming  Hou Xianxu  Li Guodong  Xiang Tianchun  Su Limin
Affiliation:State Grid Tianjin Electric Power Corporation,China Electric Power Research Institute,Electric Power Research Institute of State Grid Tianjin Electric Power Corporation,Electric Power Research Institute of State Grid Tianjin Electric Power Corporation,Electric Power Research Institute of State Grid Tianjin Electric Power Corporation,China Electric Power Research Institute
Abstract:Some distributed power generation in microgrid has intermittent and random characteristics, which has a negative impact on the power supply stability and reliability of the system. Therefore, it is necessary to carry out the energy management of microgrid system. The traditional particle swarm optimization algorithm is easy to fall into local optimum in solving the energy problem of management, in order to solve this problem, this paper introduces a hybrid particle swarm optimization algorithm, considering the micro grid economy, environmental protection and reliability requirements, established the minimum cost of the micro grid energy management optimization model to run the lowest cost, pollutant treatment. When the power balance and the output power of the distributed power supply are satisfied, the model is solved. At the same time, the change of the load demand in the system is predicted to determine the energy management strategy of microgrid. Simulation results show the effectiveness of the proposed algorithm and its strategy.
Keywords:Microgrid, energy  management, composite  particle swarm  optimization, multi-objective  optimization
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