Improving the Battery Energy Storage System Performance in Peak Load Shaving Applications

Author:

Rocha Anderson V.ORCID,Maia Thales A. C.ORCID,Filho Braz J. C.ORCID

Abstract

Peak load shaving using energy storage systems has been the preferred approach to smooth the electricity load curve of consumers from different sectors around the world. These systems store energy during off-peak hours, releasing it for usage during high consumption periods. Most of the current solutions use solar energy as a power source and chemical batteries as energy storage elements. Despite the clear benefits of this strategy, the service life of the battery energy storage system (BESS) is a driving factor for economic feasibility. The present research work proposes the use of storage systems based on actively connected batteries with power electronics support. The proposed scheme allows the individualized control of the power flow, enabling the use of batteries with different ages, technologies or degradation states in a same BESS. The presented results show that overcoming inherent limitations found in passively connected battery banks makes it possible to extend the system’s useful life and the total amount of dispatched energy by more than 50%. Experimental tests on a bench prototype with electronified batteries are carried out to proof the central concept of the proposed solution. Computational simulations using collected data from a photovoltaic plant support the conclusions and discussions on the achieved benefits.

Funder

CEFET-MG

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Cited by 5 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