dc.contributor.author | Ahmetovic, Haris | |
dc.contributor.author | Saric, Mirza | |
dc.contributor.author | Hivziefendic, Jasna | |
dc.date.accessioned | 2021-07-16T09:28:33Z | |
dc.date.available | 2021-07-16T09:28:33Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Advances in electrical and electronic engineering. 2021, vol. 19, no. 2, p. 123 - 133 : ill. | cs |
dc.identifier.issn | 1336-1376 | |
dc.identifier.issn | 1804-3119 | |
dc.identifier.uri | http://hdl.handle.net/10084/145065 | |
dc.description.abstract | This paper presents a fuzzy system for reliability-based power distribution network planning. The proposed Mamdani type fuzzy inference system with subsequent application of the Bellman-Zadeh decision-making method is used to evaluate the reliability of the power line feeders as criteria for power system planning. Unplanned outages of system components, the Energy Not Supplied (ENS) and age of the power lines are used as input variables of the system and are fuzzified using triangular fuzzy functions. The proposed model was tested on a model of a realistic distribution network in order to prove its relevance and applicability. Results demonstrated that this model could make a contribution in this field as it can be used in practical planning situations for project priority ranking. | cs |
dc.language.iso | en | cs |
dc.publisher | Vysoká škola báňská - Technická univerzita Ostrava | cs |
dc.relation.ispartofseries | Advances in electrical and electronic engineering | cs |
dc.relation.uri | https://doi.org/10.15598/aeee.v19i2.4011 | cs |
dc.rights | © Vysoká škola báňská - Technická univerzita Ostrava | |
dc.rights | Attribution-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nd/4.0/ | * |
dc.subject | Bellman-Zadeh method | cs |
dc.subject | fuzzy logic | cs |
dc.subject | Mamdani fuzzy inference system | cs |
dc.subject | power distribution system planning | cs |
dc.subject | reliability | cs |
dc.title | Reliability Based Power Distribution Network Planning Using Fuzzy Logic | cs |
dc.type | article | cs |
dc.identifier.doi | 10.15598/aeee.v19i2.4011 | |
dc.rights.access | openAccess | cs |
dc.type.version | publishedVersion | cs |
dc.type.status | Peer-reviewed | cs |