Robust multi-objective optimization for energy production scheduling in microgrids

作     者：Wang, Luhao Li, Qiqiang Zhang, Bingying Ding, Ran Sun, Mingshun 

作者机构：Univ Jinan Sch Elect Engn Jinan Shandong Peoples R China Shandong Univ Sch Control Sci & Engn Jinan Shandong Peoples R China Arizona State Univ Elect & Comp Engn Tucson AZ USA 

出 版 物：《ENGINEERING OPTIMIZATION》 (工程优选)

年 卷 期：2019年第51卷第2期

页      面：332-351页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 

基　　金：Shandong Provincial Natural Science Foundation [ZR2014FM036] 

主　　题：Microgrid robust multi-objective optimization scheduling uncertainty 

摘      要：In order to achieve better economic and environmental benefits of microgrids (MGs) under multiple uncertainties in renewable energy resources and loads, a novel energy production scheduling method is proposed based on robust multi-objective optimization with minimax criterion. Firstly, a mixed integer minimax multi-objective formulation is developed to capture uncertainties as well as minimize economic and environmental objectives. Secondly, the primal problem is decomposed into a bi-level optimization problem, which attempts to seek robust scheduling scheme set under the worst-case realization of uncertainties in a multi-objective framework. Finally, a hierarchical meta-heuristic solution strategy, including multi-objective cross entropy algorithm and delta+ indicator, is designed to solve the reconstructed problem. Numerical results demonstrate that the proposed scheduling method can effectively attenuate the disturbance of uncertainties as well as reduce energy costs and emissions, as compared with single-objective robust optimization and multi-objective optimization scheduling approaches. This study could offer useful insights which help decision-makers balance robustness and comprehensive benefits in the operation of MGs.