Zobrazit minimální záznam

dc.contributor.authorDashtdar, Masoud
dc.contributor.authorFlah, Aymen
dc.contributor.authorHosseinimoghadam, Seyed Mohammad Sadegh
dc.contributor.authorKotb, Hossam
dc.contributor.authorJasińska, Elżbieta
dc.contributor.authorGoňo, Radomír
dc.contributor.authorLeonowicz, Zbigniew
dc.contributor.authorJasiński, Michał
dc.date.accessioned2022-09-08T11:57:23Z
dc.date.available2022-09-08T11:57:23Z
dc.date.issued2022
dc.identifier.citationSustainability. 2022, vol. 14, issue 11, art. no. 6759.cs
dc.identifier.issn2071-1050
dc.identifier.urihttp://hdl.handle.net/10084/148596
dc.description.abstractAn important issue in power systems is the optimal operation of microgrids with demand-side management. The implementation of demand-side management programs, on the one hand, reduces the cost of operating the power system, and on the other hand, the implementation of such programs requires financial incentive policies. In this paper, the problem of the optimal operation of microgrids along with demand-side management (DSM) is formulated as an optimization problem. Load shifting is considered an effective solution in demand-side management. The objective function of this problem is to minimize the total operating costs of the power system and the cost of load shifting, and the constraints of the problem include operating constraints and executive restrictions for load shifting. Due to the dimensions of the problem, the simultaneous combination of a genetic algorithm and an ABC is used in such a way that by solving the OPF problem with an ABC algorithm and applying it to the structure of the genetic algorithm, the main problem will be solved. Finally, the proposed method is evaluated under the influence of various factors, including the types of production units, the types of loads, the unit uncertainty, sharing with the grid, and electricity prices all based on different scenarios. To confirm the proposed method, the results were compared with different algorithms on the IEEE 33-bus network, which was able to reduce costs by 57.01%.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesSustainabilitycs
dc.relation.urihttps://doi.org/10.3390/su14116759cs
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectmicrogridcs
dc.subjectoptimal operationcs
dc.subjectdemand-side managementcs
dc.subjectload shiftingcs
dc.subjectgenetic algorithmcs
dc.subjectABCcs
dc.titleOptimal operation of microgrids with demand-side management based on a combination of genetic algorithm and artificial bee colonycs
dc.typearticlecs
dc.identifier.doi10.3390/su14116759
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume14cs
dc.description.issue11cs
dc.description.firstpageart. no. 6759cs
dc.identifier.wos000808841500001


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Zobrazit minimální záznam

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.