Sundaram B. Pandya, Pradeep Jangir, Indrajit N. Trivedi
{"title":"Multi-objective Moth Flame Optimizer: A Fundamental Visions for Wind Power Integrated Optimal Power Flow with FACTS Devices","authors":"Sundaram B. Pandya, Pradeep Jangir, Indrajit N. Trivedi","doi":"10.1080/23080477.2021.1964693","DOIUrl":null,"url":null,"abstract":"ABSTRACT Optimal power flow (OPF) is one of the complex optimization problems in the power system domain. The OPF problem becomes much more challenging when renewable energy sources are added to the power system grid, which is unpredictable and volatile. Also, FACTS (flexible AC transmission system) devices are becoming more common in modern power systems to help ease network congestion and minimize demand. This paper aims to solve the single and multi-objective OPF by combining stochastic wind power with various types of FACTS devices such as static VAR compensator, thyristor-controlled series compensator, and thyristor-controlled phase shifter. To model stochastic wind energy, Weibull probability density functions have been used. The locations and ratings of the FACTS devices are also designed to reduce the system’s total generation cost. A non-dominated multi-objective moth flame optimization technique is used for the optimization issue. The fuzzy decision-making approach is applied to the best compromise solution. The results are validated through a modified IEEE-30 bus test system and compared with three newly developed algorithms. Graphical abstract","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"10 1","pages":"118 - 141"},"PeriodicalIF":2.4000,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23080477.2021.1964693","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 8
Abstract
ABSTRACT Optimal power flow (OPF) is one of the complex optimization problems in the power system domain. The OPF problem becomes much more challenging when renewable energy sources are added to the power system grid, which is unpredictable and volatile. Also, FACTS (flexible AC transmission system) devices are becoming more common in modern power systems to help ease network congestion and minimize demand. This paper aims to solve the single and multi-objective OPF by combining stochastic wind power with various types of FACTS devices such as static VAR compensator, thyristor-controlled series compensator, and thyristor-controlled phase shifter. To model stochastic wind energy, Weibull probability density functions have been used. The locations and ratings of the FACTS devices are also designed to reduce the system’s total generation cost. A non-dominated multi-objective moth flame optimization technique is used for the optimization issue. The fuzzy decision-making approach is applied to the best compromise solution. The results are validated through a modified IEEE-30 bus test system and compared with three newly developed algorithms. Graphical abstract
期刊介绍:
Smart Science (ISSN 2308-0477) is an international, peer-reviewed journal that publishes significant original scientific researches, and reviews and analyses of current research and science policy. We welcome submissions of high quality papers from all fields of science and from any source. Articles of an interdisciplinary nature are particularly welcomed. Smart Science aims to be among the top multidisciplinary journals covering a broad spectrum of smart topics in the fields of materials science, chemistry, physics, engineering, medicine, and biology. Smart Science is currently focusing on the topics of Smart Manufacturing (CPS, IoT and AI) for Industry 4.0, Smart Energy and Smart Chemistry and Materials. Other specific research areas covered by the journal include, but are not limited to: 1. Smart Science in the Future 2. Smart Manufacturing: -Cyber-Physical System (CPS) -Internet of Things (IoT) and Internet of Brain (IoB) -Artificial Intelligence -Smart Computing -Smart Design/Machine -Smart Sensing -Smart Information and Networks 3. Smart Energy and Thermal/Fluidic Science 4. Smart Chemistry and Materials