Scheduling of domestic shiftable loads via Cuckoo search optimization algorithm
Özet
Electrical power systems have been developed to more advanced structures called as smart grids. Among many other issues, demand side management (DSM) is one of the important instruments of the smart grids. DSM techniques increase the efficiency of the grid, and modify consumer's electrical demand via demand response (DR) programs using financial incentives. In this study, shiftable domestic loads scheduled by Cuckoo search algorithm (CSA) to ensure balanced load curve as much as possible while considering the consumers' preferences. The main motivation of this paper is scheduling the usage hours of the shiftable household appliances in a neighborhood by applying the recently developed metaheuristic CSA. This paper proposes an approach to increase the efficiency and lifetime of utility network by scheduling and operating shiftable domestic loads while considering consumer's demand in terms of financial benefits. Proposed CSA based scheduling mechanism is compared with that of Genetic algorithm (GA). The results reveal positive effects of the scheduling and the performance of the CSA over GA.
Anahtar Kelimeler
Tam Kayıt
| Alan | Değer | Dil |
|---|---|---|
| dc.contributor.author | Cakmak, Recep | |
| dc.contributor.author | Altas, Ismail H. | |
| dc.contributor.editor | Cetin, A. | |
| dc.contributor.editor | Camurcu, A.Y. | |
| dc.contributor.other | IEEE | |
| dc.date.accessioned | 2026-10-22T10:23:25.638533240Z | |
| dc.date.available | 2026-10-22T10:23:25.638533240Z | |
| dc.date.issued | 2016 | |
| dc.description.abstract | Electrical power systems have been developed to more advanced structures called as smart grids. Among many other issues, demand side management (DSM) is one of the important instruments of the smart grids. DSM techniques increase the efficiency of the grid, and modify consumer's electrical demand via demand response (DR) programs using financial incentives. In this study, shiftable domestic loads scheduled by Cuckoo search algorithm (CSA) to ensure balanced load curve as much as possible while considering the consumers' preferences. The main motivation of this paper is scheduling the usage hours of the shiftable household appliances in a neighborhood by applying the recently developed metaheuristic CSA. This paper proposes an approach to increase the efficiency and lifetime of utility network by scheduling and operating shiftable domestic loads while considering consumer's demand in terms of financial benefits. Proposed CSA based scheduling mechanism is compared with that of Genetic algorithm (GA). The results reveal positive effects of the scheduling and the performance of the CSA over GA. | |
| dc.identifier.articlenumber | 7492435 | |
| dc.identifier.doi | 10.1109/sgcf.2016.7492435 | |
| dc.identifier.endpage | 59 | |
| dc.identifier.isbn | 978-150900865-0 | |
| dc.identifier.scopus | 2-s2.0-84978768035 | |
| dc.identifier.startpage | 56 | |
| dc.identifier.uri | https://rdlopen.rawdatalibrary.net/r/gumushane/14991 | |
| dc.identifier.wos | WOS:000389660400010 | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.relation.conference | 4th International Istanbul Smart Grid Congress and Fair, ICSG 2016 | |
| dc.relation.ispartof | 4th International Istanbul Smart Grid Congress and Fair, ICSG 2016 | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | cuckoo search algorithm | |
| dc.subject | demand side management | |
| dc.subject | optimal scheduling | |
| dc.subject | Smart grids | |
| dc.subject.classification | Computer Science, Artificial Intelligence | |
| dc.subject.classification | Engineering, Electrical & Electronic | |
| dc.subject.classification | Computer Science | |
| dc.subject.classification | Engineering | |
| dc.subject.other | Algorithms | |
| dc.subject.other | Demand side management | |
| dc.subject.other | Domestic appliances | |
| dc.subject.other | Efficiency | |
| dc.subject.other | Electric power systems | |
| dc.subject.other | Electric power transmission networks | |
| dc.subject.other | Electric utilities | |
| dc.subject.other | Genetic algorithms | |
| dc.subject.other | Learning algorithms | |
| dc.subject.other | Optimization | |
| dc.subject.other | Scheduling | |
| dc.subject.other | Consumers' preferences | |
| dc.subject.other | Cuckoo search algorithms | |
| dc.subject.other | Demand response programs | |
| dc.subject.other | Electrical power system | |
| dc.subject.other | Financial incentives | |
| dc.subject.other | Optimal scheduling | |
| dc.subject.other | Scheduling mechanism | |
| dc.subject.other | Smart grid | |
| dc.subject.other | Smart power grids | |
| dc.title | Scheduling of domestic shiftable loads via Cuckoo search optimization algorithm | |
| dc.type | Conference Object | |
| dspace.entity.type | Publication | |
| rdl.citation.openalex | 25 | |
| rdl.citation.scopus | 23 | |
| rdl.citation.wos | 9 | |
| rdl.conference.date | 20 April 2016 through 21 April 2016 | |
| rdl.conference.place | Istanbul | |
| rdl.oa.status | closed | |
| rdl.sdg | SDG07 | |
| rdl.sdg | SDG09 | |
| rdl.source.index | SCOPUS | |
| rdl.source.index | WOS | |
| rdl.wos.index | Conference Proceedings Citation Index - Science (CPCI-S) |


