Unified multi‐objective optimization for regional power systems with unequal distribution of renewable energy generation and load

Author:

Zhao Long1,Meng Xiangfei1ORCID,Yang Lichao1,Wei Jia1

Affiliation:

1. Economic & Technology Research, Institute of State Grid Shandong Electric Power Company Jinan China

Abstract

AbstractThe optimization for large‐scale power systems with unequal renewable energy distribution is an important and urgent task to collaborate operations of the participated sub‐grids. This article proposes a novel method by utilizing the unified multi‐objective optimization (MOO) to integrate diverse strategies to a comprehensive problem. For this aim, individual optimal model is first established to describe the demands of each sub‐grid. The overall objectives are unified in terms of economy costs. This unification integrates evaluate different optimized results without loss of generality. The global objective is the weighted sum of the individual objectives with empirical coefficient. Thus, the internal coupled restrictions and influences among sub‐grids can be solved simultaneously. Finally, by adjusting the corresponding weights according to the preferred requirement, the optimized solution can effectively allocate renewable energy throughout all sub‐grids. Consequently, both individual and global requirements can be met at utmost. The proposed unified MOO is tested on the configured systems based on multiple modified PJM 9‐bus grids. Satisfying the global optimum of the multi‐region joint system, the total system cost increases by 15.1%, the industrial zone cost increases by 21.4%, and the residential load shedding loss cost increases by 27.3%. Although each region has to sacrifice some of its benefits, the compromise operational behavior ensures that the total cost is optimal. Numerical results verify the effectiveness in achieving the promising global optimal solution, and the flexibility in meeting the requirements of different sub‐grids.

Publisher

Wiley

Subject

General Engineering,General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3