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Multi-Objective Reactive Power Optimization Based On The Fuzzy Adaptive Particle Swarm Algorithm

机译:基于模糊自适应粒子群算法的多目标无功功率优化

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To research the problem on the multi-objective reactive power optimization, to utilize the theory of multi-objective fuzzy optimization to change the multi-objective optimization into the single-objective optimization, and to adopt the fuzzy adaptive particle swarm algorithm to carry out solutions. Comprehensively considering the security and economical efficiency of the system, as well as the condition of the operation constraints, to propose a comprehensive and practical multi-objective reactive power optimization model. To consider the multi-objective reactive power optimization model of the voltage stability index can optimize the economic benefit and safety benefit of the system. Applying the theory of multi-objective fuzzy optimization combined with the adaptive particle swarm optimization algorithm to the problem of the multi-objective reactive power optimization could solve the problem of the different dimensional multi-objective optimization in a better way. After adopting the fuzzy adaptive particle swarm algorithm, the superiorities, such as achieving the global optimal solution, reducing the computational complexity, and improving the computational efficiency,are displayed.
机译:为了研究关于多目标无功优化的问题,利用多目标模糊优化理论将多目标优化改变为单目标优化,采用模糊自适应粒子群进行解决方案。全面考虑系统的安全性和经济效率,以及运作限制的条件,提出了一种全面实用的多目标无功功率优化模型。要考虑电压稳定性指数的多目标无功功率优化模型,可以优化系统的经济效益和安全益处。应用多目标模糊优化理论与自适应粒子群优化算法结合到多目标无功功率优化的问题,以更好的方式解决了不同维度多目标优化的问题。在采用模糊自适应粒子群算法之后,显示优越性,例如实现全局最优解,降低计算复杂性,提高计算效率。

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