基于改进粒子群算法的配电网检修计划优化方法
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李亚国(1977-),男,硕士,高级工程师,主要从事配电网大数据运维解析应用研究;E-mail:lyt95588@126.com

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TM732

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国网山西省电力公司科技项目(52053018000M)


Maintenance scheduling optimization method of distribution network based on the improved particle swarm optimization
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    摘要:

    为提高配电网检修计划的合理性与经济性,提出一种基于改进粒子群算法配电网检修计划优化方法。首先,以检修成本、供电损失和故障损失最小为目标,以实际检修过程中存在的检修资源限制、检修先后顺序、安全稳定运行等问题为约束条件,建立符合实际配网检修过程的检修计划优化模型;其次,为减小求解问题的复杂度,提出对不同类型的约束采取相应的预处理方法;最后,通过将自然选择思想融入到种群粒子的迭代更新中,提高种群粒子的整体质量,克服标准粒子群算法存在的早熟收敛、易于陷入局部最优解的问题。将改进的粒子群算法应用于具体算例的求解,结果表明提出的模型和算法具有很好的可行性与合理性。

    Abstract:

    In order to improve the rationality and economy of distribution network maintenance plan, an optimization method of distribution network maintenance plan based on improved particle swarm optimization is proposed. Firstly, with the goal of minimizing maintenance cost, power supply loss, and failure loss, and the constraints of maintenance resource limitations, maintenance sequence, and safe and stable operation in the actual maintenance process, a maintenance plan optimization model that conforms to the actual distribution network maintenance process is established. Secondly, corresponding preprocessing methods are proposed for different types of constraintsto reduce the complexity of solving the problem. Finally, by incorporating the idea of natural selection into the iterative updating of population particles, the overall quality of population particles is improved to overcome the problems of premature convergence and easy to fall into local optimal solution of standard particle swarm optimization algorithm. The improved particle swarm optimization (PSO) algorithm is applied to solve a specific example. Results show that the proposed model and algorithm have good feasibility and rationality.

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李亚国,白鹭,李冠良,等.基于改进粒子群算法的配电网检修计划优化方法[J].电力科学与技术学报,2021,36(5):97-103.
Li Yaguo, Bai Lu, Li Guanliang, et al. Maintenance scheduling optimization method of distribution network based on the improved particle swarm optimization[J]. Journal of Electric Power Science and Technology,2021,36(5):97-103.

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  • 在线发布日期: 2021-11-16
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