Probabilistic multiobjective reconfiguration considering the optimal location of shunt capacitors and distributed generations in distribution network,International Transactions on Electrical Energy Systems

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Probabilistic multiobjective reconfiguration considering the optimal location of shunt capacitors and distributed generations in distribution network
International Transactions on Electrical Energy Systems ( IF 1.9 ) Pub Date : 2021-07-12 , DOI: 10.1002/2050-7038.12979
Meysam Beirami ₁ , Salar Naghdalian ₂ , Mahmood Hosseini Aliabadi ₁

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Reconfiguration is one of the most important functions in the distribution network's automation system. Reconfiguration is formulated as an optimization problem with a large number of scenarios, which demands high central processing unit time to check all of them. Therefore, it is necessary to utilize a high-efficiency optimization method. In this paper, the minimization of active power losses, total voltage deviations of buses, and maximization of system loading margin are integrated as three objective functions of the proposed reconfiguration model. Also, to improve the voltage profile, reduce power losses, and increase system loading margin, shunt capacitors (SCs) and distributed generations (DGs) are located. Seasonal daily load curves are applied to better simulate networks' real conditions. This paper uses the nondominated sorting genetic algorithm II, which generates a set of nondominated solutions. This set includes a wide range of solutions with different weighting coefficients. The multicriteria decision-making (MCDM) algorithm, as a powerful and flexible decision-making tool, is utilized to select the best solution based on tuning parameters. Also, it is assumed that DGs are wind farms, thus the uncertainty of DGs' power output is taken into the account, and the three-point estimate method (3PEM) is utilized to reduce the number of subscenarios generated by 3PEM. Finally, the subscenario aggregation method is utilized to extract the value of objective functions in subscenarios. The developed model determines the optimal location of SCs and DGs in conjunction with the optimal network reconfiguration. The proposed method is implemented on the typical 33 and 69 bus radial distribution systems.

中文翻译：

考虑配电网中并联电容器和分布式电源最优位置的概率多目标重构

重新配置是配电网络自动化系统中最重要的功能之一。重新配置被表述为一个具有大量场景的优化问题，需要很高的中央处理单元时间来检查所有场景。因此，有必要采用一种高效的优化方法。在本文中，有功功率损耗的最小化、母线总电压偏差的最小化和系统负载裕度的最大化被整合为所提出的重构模型的三个目标函数。此外，为了改善电压分布、减少功率损耗和增加系统负载裕度，还安装了并联电容器 (SC) 和分布式发电 (DG)。应用季节性日负荷曲线以更好地模拟网络的真实条件。本文采用非支配排序遗传算法II，生成一组非支配解。该集合包括具有不同加权系数的广泛解决方案。多准则决策（MCDM）算法作为一种强大而灵活的决策工具，用于根据调整参数选择最佳解决方案。同时，假设DGs为风电场，考虑DGs出力的不确定性，利用三点估计法（3PEM）减少3PEM产生的子场景数量。最后，利用子场景聚合方法提取子场景中目标函数的值。开发的模型结合最佳网络重构来确定 SC 和 DG 的最佳位置。

更新日期：2021-09-16

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