Type 2 fuzzy adaptive binary particle swarm optimization for optimal placement and sizing of distributed generation

A. Soeprijanto, M. Abdillah
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引用次数: 13

Abstract

This paper proposes a new method for optimizing the placement and size of distributed generation (DG) using type-2 fuzzy adaptive binary particle swarm optimization with single mutation operator, called T2FABPSOM. The objective function of the proposed method to minimize active power losses in transmission line with the bus voltage system constraints is allowed. Type-2 fuzzy logic system (type-2 FLS) is used for tuning the inertia weight w, the learning factors c1 and c2 parameters of particle swarm optimization to control the particle velocity. Single mutation also used in the proposed method as a combination to improve and strengthen the ability of particle to search for candidate solutions globally and avoid convergence to local optima. To evaluate the performance of the proposed method, the method is applied on IEEE 30 bus system. The proposed method compared with the binary PSO (BPSO) and fuzzy adaptive binary PSO (FABPSO). The simulation results indicated that the proposed method can determine the size and location of the optimal DG with a total active power losses are minimum compared to other methods.
2型模糊自适应二元粒子群优化算法用于分布式发电的最优布局和最优规模
本文提出了一种基于单突变算子的2型模糊自适应二元粒子群优化方法,即T2FABPSOM。该方法的目标函数是在母线电压系统约束下使输电线路有功功率损耗最小。采用2型模糊逻辑系统(Type-2 FLS)对粒子群优化的惯性权值w、学习因子c1和c2参数进行调节,控制粒子速度。该方法采用单突变作为组合,提高和增强了粒子全局搜索候选解的能力,避免收敛到局部最优。为了评估该方法的性能,将该方法应用于ieee30总线系统。该方法与二值粒子群算法(BPSO)和模糊自适应二值粒子群算法(FABPSO)进行了比较。仿真结果表明,与其他方法相比,该方法能够以最小的总有功损耗确定最优DG的大小和位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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