{"title":"考虑性能参数和渗透的混合可再生能源多目标最优潮流的不同感知","authors":"Sundaram B. Pandya, H. Jariwala","doi":"10.1080/23080477.2021.1916853","DOIUrl":null,"url":null,"abstract":"ABSTRACT Traditional generating units, as well as renewable energy resources, make up the electrical grid. The proposed article proposes performance indices for optimal power flow, which combine wind turbines, solar photovoltaic systems, and hybrid solar with small hydropower sources. The irregularity of renewable energy sources’ performance adds to the complexity of the optimal power flow (OPF) problem. The analytical strategies also use lognormal, Weibull, and Gumbel probability density functions to approximate the energy yield of those renewables. Also explored is the effect of changing distribution parameters and the penetration of renewable energy resources as a function of optimal power flow. Penalty charges for underestimation and standby charges for overestimation of unusual non-conventional generating units are included in the objective feature. The optimization problem is solved using a non-dominated multi-objective moth flame optimization technique. In terms of achieving diverse and convergent Pareto optimal solutions, the MOMFO optimizer is more efficient and robust than the SMODE/SF and MOEA/D-SF optimizers, according to the simulation outcomes. As a result IEEE-30 bus system, the MOMFO optimizer can be used to tackle the MO-SCOPF issue with the incorporation of wind, solar, hydro, and thermal generators in an integrated multiple-power system. GRAPHICAL ABSTRACT","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"9 1","pages":"186 - 215"},"PeriodicalIF":2.4000,"publicationDate":"2021-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23080477.2021.1916853","citationCount":"9","resultStr":"{\"title\":\"A Different Perception of Hybrid Renewable Energy Sources Integrated Multi-objective Optimal Power Flow considering Performance Parameters and Penetration\",\"authors\":\"Sundaram B. Pandya, H. Jariwala\",\"doi\":\"10.1080/23080477.2021.1916853\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Traditional generating units, as well as renewable energy resources, make up the electrical grid. The proposed article proposes performance indices for optimal power flow, which combine wind turbines, solar photovoltaic systems, and hybrid solar with small hydropower sources. The irregularity of renewable energy sources’ performance adds to the complexity of the optimal power flow (OPF) problem. The analytical strategies also use lognormal, Weibull, and Gumbel probability density functions to approximate the energy yield of those renewables. Also explored is the effect of changing distribution parameters and the penetration of renewable energy resources as a function of optimal power flow. Penalty charges for underestimation and standby charges for overestimation of unusual non-conventional generating units are included in the objective feature. The optimization problem is solved using a non-dominated multi-objective moth flame optimization technique. In terms of achieving diverse and convergent Pareto optimal solutions, the MOMFO optimizer is more efficient and robust than the SMODE/SF and MOEA/D-SF optimizers, according to the simulation outcomes. As a result IEEE-30 bus system, the MOMFO optimizer can be used to tackle the MO-SCOPF issue with the incorporation of wind, solar, hydro, and thermal generators in an integrated multiple-power system. GRAPHICAL ABSTRACT\",\"PeriodicalId\":53436,\"journal\":{\"name\":\"Smart Science\",\"volume\":\"9 1\",\"pages\":\"186 - 215\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2021-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/23080477.2021.1916853\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Smart Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/23080477.2021.1916853\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23080477.2021.1916853","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
A Different Perception of Hybrid Renewable Energy Sources Integrated Multi-objective Optimal Power Flow considering Performance Parameters and Penetration
ABSTRACT Traditional generating units, as well as renewable energy resources, make up the electrical grid. The proposed article proposes performance indices for optimal power flow, which combine wind turbines, solar photovoltaic systems, and hybrid solar with small hydropower sources. The irregularity of renewable energy sources’ performance adds to the complexity of the optimal power flow (OPF) problem. The analytical strategies also use lognormal, Weibull, and Gumbel probability density functions to approximate the energy yield of those renewables. Also explored is the effect of changing distribution parameters and the penetration of renewable energy resources as a function of optimal power flow. Penalty charges for underestimation and standby charges for overestimation of unusual non-conventional generating units are included in the objective feature. The optimization problem is solved using a non-dominated multi-objective moth flame optimization technique. In terms of achieving diverse and convergent Pareto optimal solutions, the MOMFO optimizer is more efficient and robust than the SMODE/SF and MOEA/D-SF optimizers, according to the simulation outcomes. As a result IEEE-30 bus system, the MOMFO optimizer can be used to tackle the MO-SCOPF issue with the incorporation of wind, solar, hydro, and thermal generators in an integrated multiple-power system. 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