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Optimal operation of microgrid based on improved binary particle swarm optimization algorithm with double-structure coding

机译:基于双结构编码的改进二进制粒子群算法的微电网优化运行

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Due to energy crisis and environmental concern, distributed generations including renewable energy sources have become popular in the electric energy industry. Microgrid is an effective technical means of the integration and access of distributed generations. On the basic of the generating characteristics of various microsources, this paper establishes a multi-objective optimal operation model with multiple constraints, aiming at minimizing the generation cost, pollutant emission cost, compensation cost of load shedding and network loss of microgrid. Different weights are assigned to the four sub-objective functions to transform the multi-objective optimization problem into a single objective optimization problem. Binary particle swarm optimization (BPSO) algorithm is improved with double-structure coding. Its performance is tested by two test functions and comparison with the traditional BPSO algorithm is made. The improved algorithm is applied to a microgrid simulation example which is in the island mode. Simulation results demonstrate the correctness of the proposed optimization model and the effectiveness of the improved algorithm.
机译:由于能源危机和环境问题,包括可再生能源在内的分布式发电已在电能工业中流行。微电网是集成和访问分布式世代的有效技术手段。基于各种微源的发电特性,建立了具有多个约束条件的多目标最优运行模型,旨在使发电成本,污染物排放成本,减荷补偿成本和微电网的网络损失最小。将不同的权重分配给四个子目标函数,以将多目标优化问题转换为单个目标优化问题。二进制粒子群优化(BPSO)算法通过双重结构编码得到了改进。通过两个测试功能测试其性能,并与传统的BPSO算法进行比较。该改进算法应用于孤岛模式的微电网仿真实例。仿真结果证明了所提优化模型的正确性和改进算法的有效性。

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