Optimal location and size of distributed energy resources using sensitivity analysis-based approaches

M. Benidris, Yuting Tian, Samer Sulaeman, J. Mitra
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引用次数: 7

Abstract

This paper introduces an analytical approach based on sensitivity analyses of various objective functions with respect to load constraints to determine optimum locations and sizes of distributed energy resources (DERs). This method is based on sequentially calculating Lagrange multipliers of the dual solution of an optimization problem for various load buses. Determining the best candidate locations based on the sensitivity analyses with the assumption that an active constraint would remain active for all source sizes could produce inaccurate results. The reason is that buses that are ranked as the best candidates based on Lagrange multipliers may not be valid for large DERs since Lagrange multipliers change with the change in the system loading. In this work, locations and sizes are jointly determined in a sequential manner based on the validity of the active constraints. The proposed method can be applied with any objective function; however, in this paper, minimum generation cost is used as an objective function in the optimization problem. The method is demonstrated on several test systems including the IEEE RTS, IEEE 14, 30, 57, 118 and 300 bus test systems and the results showed the effectiveness of the proposed method against the traditional sensitivity analysis methods. Also, the results of the proposed method are validated using genetic algorithm.
基于灵敏度分析方法的分布式能源的最优位置和规模
本文介绍了一种基于负荷约束下各种目标函数敏感性分析的分布式能源优化配置方法。该方法基于对各种负载总线的优化问题的对偶解的拉格朗日乘子的顺序计算。根据敏感性分析确定最佳候选位置,并假设对所有源大小都有活动约束,可能会产生不准确的结果。原因是基于拉格朗日乘数被列为最佳候选的总线可能对大型der无效,因为拉格朗日乘数随着系统负载的变化而变化。在这项工作中,位置和大小是根据活动约束的有效性以顺序的方式共同确定的。该方法适用于任意目标函数;而本文以发电成本最小作为优化问题的目标函数。在ieeerts、ieee14、ieee30、ieee57、ieee118和ieee300总线测试系统上进行了验证,结果表明该方法与传统的灵敏度分析方法相比是有效的。最后,利用遗传算法对所提方法的结果进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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