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Research on Microgrid Optimization Based on Simulated Annealing Particle Swarm Optimization

机译:基于模拟退火粒子群优化的微电网优化研究

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摘要

Based on the pursuit of different goals in the operation of the microgrid, it is not possible to meet the lowest cost and the least pollution at the same time. From the perspective of economy and environmental protection, a microgrid model including photovoltaic power generation, wind power generation, micro gas turbine, fuel cell and energy storage device is proposed. This paper establishes a comprehensive benefit objective function that considers both microgrid fuel cost, maintenance management cost, depreciation cost, interaction cost with public grid and pollutant treatment cost. In order to avoid the defect that the traditional particle swarm optimization algorithm is easy to fall into the local optimal solution, this paper uses the combination of simulated annealing algorithm and particle swarm optimization algorithm to compare with the traditional particle swarm optimization algorithm to obtain a more suitable method for microgrid operation. Finally, a typical microgrid in China is taken as an example to verify the feasibility of the algorithm.
机译:基于追求在微电网的操作不同的目标,这是不可能满足的同时以最低的成本和最少的污染。从经济和环保的角度看,包括光伏发电,风力发电,微型燃气轮机,燃料电池和能量存储装置中的微电网模型。本文建立了一个综合效益的目标函数,同时考虑了微电网燃料成本,维护管理费,折旧费,互动成本与公共电网和污染物处理成本。为了避免该缺陷,传统的粒子群优化算法是容易陷入局部最优解,本文采用模拟退火算法和粒子群优化算法的组合与传统的粒子群优化算法来比较,以获得更用于微电网操作合适的方法。最后,在中国一个典型的微电网为例验证算法的可行性。

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