Optimized energy management for photovoltaic/wind hybrid micro-grid using energy storage solution

IF 3.1 Q1 ENGINEERING, MULTIDISCIPLINARY
Neethu Elizabeth Michael, Ramesh C. Bansal, Ali A.A. Ismail, A. Elnady, Shazia Hasan
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A sensitivity assessment is also performed to evaluate the influence of different input constraints on the model. The output results demonstrated that the EMS could schedule power effectively while considering electricity pricing. By up to 1636.96 $/hr. in day-ahead revenue with the degradation effect and 1811.96 $/hr. without the degradation effect, the analysis confirmed the usefulness of the proposed framework. Through the case studies explained, the new objective function observed minimum power costs with battery degradation by up to 1.10% less as compared to without battery degradation effect. 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引用次数: 0

Abstract

ABSTRACTOne of the key strategies for reducing the rate of environmental pollution is decarbonizing the power industry. In this work, we investigate the effects of energy storage systems (ESS) and fluctuations in renewable energy on climate change mitigation in a grid-connected microgrid. This analysis has been carried out by utilizing an improved energy management system (EMS) and optimal economic dispatch using computational models of mixed-integer linear programming (MILP). In addition to battery deterioration analysis, long short-term memory (LSTM) is developed to estimate photovoltaic and wind power renewable production, energy price, and load requirement. A sensitivity assessment is also performed to evaluate the influence of different input constraints on the model. The output results demonstrated that the EMS could schedule power effectively while considering electricity pricing. By up to 1636.96 $/hr. in day-ahead revenue with the degradation effect and 1811.96 $/hr. without the degradation effect, the analysis confirmed the usefulness of the proposed framework. Through the case studies explained, the new objective function observed minimum power costs with battery degradation by up to 1.10% less as compared to without battery degradation effect. Furthermore, the second case analysis indicates the significance of considering forecasted electrical parameters for realistic microgrid power dispatch.KEYWORDS: Economic dispatchenergy storage systemenergy management systemrenewable poweruncertaintymicrogrid Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationNotes on contributorsNeethu Elizabeth MichaelNeethu Elizabeth Michael received her Ph.D. in Electrical Engineering from BITS Pilani, India in 2022, her MTech degree in Power Systems from the University of Calicut, Kerala, India in 2011, and her BTech degree in Electrical and Electronics Engineering from Mahatma Gandhi University, Kerala, India in 2009. Her work demonstrates quantitative scientific methodologies expertise, collaboration with societal research partners, and a track record of Q1 research publications. Her research interest includes microgrid power quality issues, renewable energy resources integration problems, virtual inertia applications in power systems, and participation and optimization of electric vehicles in the power market.Ramesh C. BansalRamesh C. Bansal has over 25 years of teaching, research, academic leadership, and industrial experience. Currently, he is a Professor in the EE Dept. at the University of Sharjah, UAE, and an Extraordinary Professor at the University of Pretoria, South Africa. In previous postings, he was a Professor and Group head (Power) at the University of Pretoria and worked with the University of Queensland, Australia; USP, Fiji; and BITS Pilani, India. Prof. Bansal has published over 400 journal articles, conf. papers, books/book chapters. He has Google citations of over 18000 and an h-index of 65. He has supervised 25 PhD and 5 Post Docs. Prof. Bansal has significantly attracted significant funding from Industry and Government Organizations. He is an Editor of reputed journals including IEEE Systems Journal, IET-RPG, and SGSE. He is a Fellow, and CP Engg IET-UK, Fellow IE (India), and a Senior Member IEEE. He has diversified research interests in the areas of Renewable Energy, Power Systems, and Smart Grid.Ali A.A. IsmailAli A.A. Ismail (Member, IEEE) received a B.Sc. degree from the University of Khartoum, Sudan, in 1991, a M.Sc. degree from the University of Baghdad, Iraq, in 1997, and a Ph.D. degree in electrical engineering from Yildiz Technical University, Istanbul, Turkey, in 2007. His research interests include the control of electrical machines, power electronics applications, low-frequency electromagnetic waves, filters, and smart grids.A. ElnadyA. Elnady (Senior Member, IEEE) received bachelor’s and master’s degrees from Cairo University, Cairo, Egypt, in 1990 and 1998, respectively, and the Ph.D. degree from the University of Waterloo, Waterloo, ON, Canada, in 2004. His research interests include power-electronics applications in power systems, power quality in distribution systems, smart grids, and the integration of renewable sources within power grids.Shazia HasanShazia Hasan has more than 15 years of teaching and research experience in reputed institutes of India and currently working as an Associate Professor at BITS Pilani Dubai Campus. She received her bachelor’s degree in 2002 and her Ph.D. in the year 2012. She won the ‘Young Scientist Award’ from VIFRA in 2015. She has published more than 40 research papers in peer-reviewed international journals/conferences like IEEE, IET, Elsevier, Measurement, etc. She has served as convenor/co-convenor for several international conferences. Recently she received the “Academic Achievement for university professor award” LEWAS 2020. Her research interest includes signal processing application for Power systems, renewable energy integration, and filter design.
利用储能解决方案优化光伏/风能混合微电网的能源管理
摘要降低环境污染率的关键策略之一是使电力工业脱碳。在这项工作中,我们研究了储能系统(ESS)和可再生能源的波动对并网微电网中气候变化缓解的影响。本文采用混合整数线性规划(MILP)计算模型,利用改进的能源管理系统(EMS)和最优经济调度进行了分析。除了电池劣化分析之外,还开发了长短期记忆(LSTM)来估计光伏和风能的可再生能源产量、能源价格和负荷需求。还进行了敏感性评估,以评估不同输入约束对模型的影响。输出结果表明,在考虑电价的情况下,EMS可以有效地进行电力调度。高达1636.96美元/小时。在前一天的收入与退化效应和1811.96美元/小时。在没有退化效应的情况下,分析证实了所提议框架的有效性。通过案例研究解释,新的目标函数观察到,与没有电池退化影响相比,电池退化影响下的最低电力成本减少了1.10%。第二例分析表明,考虑电参数预测对现实微网电力调度的重要意义。关键词:经济调度储能系统能源管理系统可再生能源不确定性微电网披露声明作者未报告潜在利益冲突。neethu Elizabeth Michael于2022年在印度理工学院皮拉尼分校获得电气工程博士学位,2011年在印度喀拉拉邦卡利卡特大学获得电力系统硕士学位,2009年在印度喀拉拉邦圣雄甘地大学获得电气和电子工程学士学位。她的工作展示了定量科学方法的专业知识,与社会研究伙伴的合作,以及Q1研究出版物的记录。主要研究方向为微电网电能质量问题、可再生能源资源整合问题、虚拟惯性在电力系统中的应用、电动汽车在电力市场中的参与与优化。Ramesh C. Bansal拥有超过25年的教学、研究、学术领导和行业经验。目前,他是阿联酋沙迦大学电子工程系的教授,以及南非比勒陀利亚大学的特聘教授。在之前的职位中,他是比勒陀利亚大学的教授和小组负责人(电力),并与澳大利亚昆士兰大学合作;USP,斐济;以及印度的BITS Pilani。班萨尔教授发表了400多篇期刊文章、论文、书籍/书籍章节。他被引用次数超过18000次,h指数为65。培养博士25人,博士后5人。班萨尔教授吸引了来自工业界和政府组织的大量资金。他是知名期刊的编辑,包括IEEE Systems Journal, IET-RPG和SGSE。他是IEEE资深会员,英国工程师,印度工程师,IEEE资深会员。他在可再生能源、电力系统和智能电网等领域有广泛的研究兴趣。Ali A.A. Ismail (IEEE成员),1991年获得苏丹喀土穆大学的学士学位,1997年获得伊拉克巴格达大学的硕士学位,2007年获得土耳其伊斯坦布尔Yildiz Technical University的电气工程博士学位。他的研究兴趣包括电机控制、电力电子应用、低频电磁波、滤波器和智能电网。ElnadyA。Elnady (IEEE高级会员)分别于1990年和1998年在埃及开罗大学获得学士和硕士学位,并于2004年在加拿大滑铁卢大学获得博士学位。他的研究兴趣包括电力系统中的电力电子应用、配电系统中的电能质量、智能电网以及可再生能源在电网中的整合。Shazia Hasan在印度知名机构拥有超过15年的教学和研究经验,目前在BITS Pilani迪拜校区担任副教授。2002年获学士学位,2012年获博士学位。2015年,她获得了VIFRA颁发的“青年科学家奖”。在IEEE、IET、Elsevier、Measurement等国际期刊/会议上发表研究论文40余篇。她曾担任若干国际会议的召集人/共同召集人。最近,她获得了LEWAS 2020“大学教授学术成就奖”。 主要研究方向为电力系统信号处理应用、可再生能源集成、滤波器设计等。
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来源期刊
INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION
INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION Engineering-Industrial and Manufacturing Engineering
CiteScore
6.10
自引率
32.30%
发文量
66
期刊介绍: This journal was first published in 1981 and covers languages, hardware, software, methodology, identification, numerical methods, graphical methods, VLSI, microcomputers in simulation, and applications in all fields. It appears quarterly.
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