M. Vijayaragavan, V. Krishnakumar, V. Vasan Prabhu
{"title":"基于混合动力方法优化电力消耗成本的电动汽车能量管理方法","authors":"M. Vijayaragavan, V. Krishnakumar, V. Vasan Prabhu","doi":"10.1177/0958305X221135020","DOIUrl":null,"url":null,"abstract":"This paper proposes a hybrid approach for the optimal design of electric vehicle (EV) home energy management. The proposed hybrid system combines the execution of the Lichtenberg optimization algorithm and the heap-based optimizer; hence, it is named as LAHBO method. The main purpose of the proposed system is the reduction of costs and improvement of the power factor. Thus, two phases of optimization, such as Lichtenberg optimization algorithm–based cost minimization and heap-based optimizer–based power factor improvement. At initial phase, power conversation, and operating time of the smart home components are decided using the Lichtenberg optimization algorithm method. It is categorized into four groups, such as interruptible, uninterruptible, thermostatically controlled, and non-programmable loads. In second phase, the residential power factor at grid connection point is improved using the heap-based optimizer approach. Finally, the proposed system is carried out on MATLAB platform related to several existing approaches. The proposed method enhances the power factor and diminishes the cost than the existing method. The cost of proposed method is 0.16$ and existing approaches such as CGO, SMO, and SOA cost become 0.2, 0.3, and 0.35$, respectively.","PeriodicalId":11652,"journal":{"name":"Energy & Environment","volume":"18 1","pages":"663 - 689"},"PeriodicalIF":4.0000,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Energy management approach in electric vehicle with optimizing electricity consumption cost using hybrid method\",\"authors\":\"M. Vijayaragavan, V. Krishnakumar, V. Vasan Prabhu\",\"doi\":\"10.1177/0958305X221135020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a hybrid approach for the optimal design of electric vehicle (EV) home energy management. The proposed hybrid system combines the execution of the Lichtenberg optimization algorithm and the heap-based optimizer; hence, it is named as LAHBO method. The main purpose of the proposed system is the reduction of costs and improvement of the power factor. Thus, two phases of optimization, such as Lichtenberg optimization algorithm–based cost minimization and heap-based optimizer–based power factor improvement. At initial phase, power conversation, and operating time of the smart home components are decided using the Lichtenberg optimization algorithm method. It is categorized into four groups, such as interruptible, uninterruptible, thermostatically controlled, and non-programmable loads. In second phase, the residential power factor at grid connection point is improved using the heap-based optimizer approach. Finally, the proposed system is carried out on MATLAB platform related to several existing approaches. The proposed method enhances the power factor and diminishes the cost than the existing method. The cost of proposed method is 0.16$ and existing approaches such as CGO, SMO, and SOA cost become 0.2, 0.3, and 0.35$, respectively.\",\"PeriodicalId\":11652,\"journal\":{\"name\":\"Energy & Environment\",\"volume\":\"18 1\",\"pages\":\"663 - 689\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2022-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy & Environment\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1177/0958305X221135020\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy & Environment","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1177/0958305X221135020","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
Energy management approach in electric vehicle with optimizing electricity consumption cost using hybrid method
This paper proposes a hybrid approach for the optimal design of electric vehicle (EV) home energy management. The proposed hybrid system combines the execution of the Lichtenberg optimization algorithm and the heap-based optimizer; hence, it is named as LAHBO method. The main purpose of the proposed system is the reduction of costs and improvement of the power factor. Thus, two phases of optimization, such as Lichtenberg optimization algorithm–based cost minimization and heap-based optimizer–based power factor improvement. At initial phase, power conversation, and operating time of the smart home components are decided using the Lichtenberg optimization algorithm method. It is categorized into four groups, such as interruptible, uninterruptible, thermostatically controlled, and non-programmable loads. In second phase, the residential power factor at grid connection point is improved using the heap-based optimizer approach. Finally, the proposed system is carried out on MATLAB platform related to several existing approaches. The proposed method enhances the power factor and diminishes the cost than the existing method. The cost of proposed method is 0.16$ and existing approaches such as CGO, SMO, and SOA cost become 0.2, 0.3, and 0.35$, respectively.
期刊介绍:
Energy & Environment is an interdisciplinary journal inviting energy policy analysts, natural scientists and engineers, as well as lawyers and economists to contribute to mutual understanding and learning, believing that better communication between experts will enhance the quality of policy, advance social well-being and help to reduce conflict. The journal encourages dialogue between the social sciences as energy demand and supply are observed and analysed with reference to politics of policy-making and implementation. The rapidly evolving social and environmental impacts of energy supply, transport, production and use at all levels require contribution from many disciplines if policy is to be effective. In particular E & E invite contributions from the study of policy delivery, ultimately more important than policy formation. The geopolitics of energy are also important, as are the impacts of environmental regulations and advancing technologies on national and local politics, and even global energy politics. Energy & Environment is a forum for constructive, professional information sharing, as well as debate across disciplines and professions, including the financial sector. Mathematical articles are outside the scope of Energy & Environment. The broader policy implications of submitted research should be addressed and environmental implications, not just emission quantities, be discussed with reference to scientific assumptions. This applies especially to technical papers based on arguments suggested by other disciplines, funding bodies or directly by policy-makers.