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An Improved Particle Swarm Optimization Algorithm Applied to Economic Dispatch

机译:改进的粒子群算法在经济调度中的应用

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This paper proposes a new practical optimization method applied to the economic dispatch (ED) in a power system. The proposed method is based on an improved particle swarm optimization algorithm and considers some restrict conditions of ED in a practical power system. By reinitializing them with some currently optimal values during every cycle of iteration, this proposed method can make some inactivity particles to be always within a very small area having an optimal solution. The proposed method can avoid effectively the "premature" of the classic particle swarm optimization (PSO) algorithm due to improve the cognized capacity of the classic PSO, thereby it is beneficial to obtain some optimal global solutions. The simulation results show that proposed method has some excellent characteristics of higher quality calculation precision and better computation efficiency, compared with some other PSO methods.
机译:提出了一种适用于电力系统经济调度的新的实用优化方法。该方法基于改进的粒子群优化算法,并考虑了实际电力系统中ED的一些约束条件。通过在迭代的每个循环期间用一些当前最佳值重新初始化它们,此提出的方法可以使一些不活动粒子始终处于具有最佳解的非常小的区域内。所提出的方法由于提高了经典粒子群优化算法的认知能力,可以有效避免经典粒子群优化算法的“过早”,从而有利于获得一些最优的全局解。仿真结果表明,与其他PSO方法相比,该方法具有较高的计算精度和较高的计算效率。

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