利用二元粒子群优化和概率潮流优化径向配电系统电压分布

F. Ruiz-Rodriguez, M. Gómez-González, F. Jurado
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引用次数: 2

摘要

电压调节是分布式光伏发电系统需要解决的主要问题之一。负荷和分布式发电产量可以假设为随机变量。结果表明,该方法可用于光伏并网系统所有负荷节点的电压维持在既定范围内。为了评估光伏系统的性能,本文提出了一个考虑太阳辐照度和负荷随机性的概率模型。本文提出了一种基于离散粒子群优化和概率径向负荷流的优化方法。与蒙特卡罗模拟相比,计算机仿真简化证明了该方法具有更好的性能。令人满意的解决方案在更少的迭代中得到。因此,收敛速度快,计算成本比蒙特卡罗模拟所需的计算成本低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving voltage profile in radial distribution systems using binary particle swarm optimization and probabilistic load flow
The voltage regulation is one of the main problems to be dealt in distributed generation photovoltaic systems. Loads and distributed generation production can be assumed as random variables. Results demonstrate that the suggested method can be applied for the maintaining of voltages within established limits at all load nodes of a photovoltaic grid-connected system (PVGCS). To assess the performance of photovoltaic system, this work proposes a probabilistic model that takes into account the random nature of solar irradiance and load. In this paper is presented a new method employing discrete particle swarm optimization and probabilistic radial load flow. Computer simulation reduction evidences a better performance of the new probabilistic load flow in comparison to Monte Carlo simulation. Satisfactory solutions are reached in a smaller number of iterations. Hence, convergence is quickly reached and computational cost is low enough than that demanded for Monte Carlo simulation.
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