T. M. Dao, Truong Hoang Bao Huy, Duy-Phuong N. Do, Dieu Ngoc Vo
{"title":"A chaotic equilibrium optimization for temperature-dependent optimal power flow","authors":"T. M. Dao, Truong Hoang Bao Huy, Duy-Phuong N. Do, Dieu Ngoc Vo","doi":"10.1080/23080477.2023.2171696","DOIUrl":null,"url":null,"abstract":"ABSTRACT Optimal power flow (OPF) is one of the common problems in power systems. In general, the branch resistance of the system is assumed to be constant with respect to temperature variation in conventional optimal power flow. However, the temperature correlation of the branch resistance should be taken into account to enhance the accurate calculation of the power flow and branch losses. This paper suggests a new and efficient method, which is chaotic equilibrium optimization (CEO) to deal with the temperature-dependent optimal power flow (TDOPF) problem. The CEO is validated on IEEE 30-bus and 118-bus networks with different objective functions, including generating fuel cost, total active power losses, voltage profile enhancement, voltage stability improvement, and emission reduction. Furthermore, the temperature effect on the TDOPF problem is also analyzed. In the case of fuel cost optimization in the 30-bus network, fuel cost increases from 799.85 $/h to 802.9474 $/h when the temperature increases from 0°C to 100°C, corresponding to a fuel cost increase of 0.04% for each 10°C. From the obtained outcomes, the efficacy of the CEO has been proven in finding accurate solutions for the TDOPF problem. GRAPHICAL ABSTRACT","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23080477.2023.2171696","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: 4
Abstract
ABSTRACT Optimal power flow (OPF) is one of the common problems in power systems. In general, the branch resistance of the system is assumed to be constant with respect to temperature variation in conventional optimal power flow. However, the temperature correlation of the branch resistance should be taken into account to enhance the accurate calculation of the power flow and branch losses. This paper suggests a new and efficient method, which is chaotic equilibrium optimization (CEO) to deal with the temperature-dependent optimal power flow (TDOPF) problem. The CEO is validated on IEEE 30-bus and 118-bus networks with different objective functions, including generating fuel cost, total active power losses, voltage profile enhancement, voltage stability improvement, and emission reduction. Furthermore, the temperature effect on the TDOPF problem is also analyzed. In the case of fuel cost optimization in the 30-bus network, fuel cost increases from 799.85 $/h to 802.9474 $/h when the temperature increases from 0°C to 100°C, corresponding to a fuel cost increase of 0.04% for each 10°C. From the obtained outcomes, the efficacy of the CEO has been proven in finding accurate solutions for the TDOPF problem. 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
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