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A linear programming-driven MCDM approach for multi-objective economic dispatch in smart grids

机译:用于智能电网中多目标经济调度的线性规划驱动MCDM方法

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This paper presents a novel approach to deal with the multi-objective economic dispatch problem in smart grids as a multi-criteria decision making (MCDM) problem, whose decision alternatives are dynamically generated. Four objectives are considered: emissions, energy cost, distance of supply, and load balancing. Objectives are preliminarily preference-ranked through a fuzzy version of the analytic hierarchy process (AHP), and then classified into two categories of importance. The more important objectives form the objective function of a linear programming (LP) problem, whose solution (driving solution) drives the generation of Pareto-optimal alternative configurations of power output of the generators. The technique for order of preference by similarity to ideal solution (TOPSIS) is used to automatically select the most suitable power output configuration, according to initial preferences, derived with fuzzy AHP. The effectiveness of our approach is validated by comparing it to the weighted sum (WS) method, by simulating 40 different operating scenarios on a prototype smart microgrid.
机译:本文提出了一种新颖的方法,将智能电网中的多目标经济调度问题作为多准则决策问题(MCDM)来解决,该决策方法是动态生成的。考虑了四个目标:排放,能源成本,供应距离和负载平衡。首先通过模糊层次分析层次(AHP)对目标进行优先排序,然后将其分为两类。更为重要的目标形成了线性规划(LP)问题的目标函数,该线性规划问题的解决方案(驱动解决方案)推动了发电机功率输出的帕累托最优替代配置的产生。通过类似于理想解决方案(TOPSIS)的优先级排序技术,可根据模糊AHP得出的初始优先级,自动选择最合适的功率输出配置。通过将其与加权和(WS)方法进行比较,并通过在原型智能微电网上模拟40种不同的操作方案,验证了我们方法的有效性。

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