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Reactive Power Optimization Algorithm of Active Distribution Network Based on Improved Quantum Particle Swarm Optimization

机译:基于改进量子粒子群算法的有源配电网无功优化算法

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The particle swarm optimization (PSO) algorithm is prone to local optimal position in the late iteration when solving the reactive power optimization problem of active distribution network. Aiming at the above problems, a reactive power optimization algorithm, improved quantum particle swarm optimization (IQPSO), is proposed in this paper. Based on quantum particle swarm optimization (QPSO) algorithm, the inverse point of worst particle position in the iteration process is introduced into the update formula of particle position, which makes the particle jump out of the local optimal position constraint in the iterative process. In this paper, an optimization model is established with the aim of minimum voltage deviation and system loss in a typical 34 node system, and the effectiveness of proposed method is verified by comparing with QPSO.
机译:解决有源配电网无功优化问题时,粒子群优化算法在后期迭代中容易出现局部最优位置。针对上述问题,提出了一种无功优化算法,即改进的量子粒子群算法。基于量子粒子群算法(QPSO),将迭代过程中最差粒子位置的逆点引入粒子位置的更新公式,使粒子在迭代过程中跳出局部最优位置约束。本文针对典型的34节点系统,建立了以最小电压偏差和系统损耗为目标的优化模型,并与QPSO进行了比较,验证了所提方法的有效性。

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