标题:Robust multi-objective optimization for energy production scheduling in microgrids
作者:Wang L.; Li Q.; Zhang B.; Ding R.; Sun M.
作者机构:[Wang, L] School of Electrical Engineering, University of Jinan, Jinan, People’s Republic of China;[ Li, Q] School of Control Science and Engineering 更多
通讯作者:Wang, L(wlhbeyond@gmail.com)
来源:Engineering Optimization
出版年:2018
页码:1-20
DOI:10.1080/0305215X.2018.1457655
关键词: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 δ+ 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. © 2018 Informa UK Limited, trading as Taylor & Francis Group
收录类别:SCOPUS
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045673157&doi=10.1080%2f0305215X.2018.1457655&partnerID=40&md5=b04d045a2e1ad4ff6837db5d7f461f50
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