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dc.contributor.authorKosunalp S.
dc.date.accessioned20.04.201910:49:12
dc.date.accessioned2019-04-20T21:43:13Z
dc.date.available20.04.201910:49:12
dc.date.available2019-04-20T21:43:13Z
dc.date.issued2017
dc.identifier.issn0360-5442
dc.identifier.urihttps://dx.doi.org/10.1016/j.energy.2017.05.175
dc.identifier.urihttps://hdl.handle.net/20.500.12403/457
dc.description.abstractEnergy harvesting (EH) from environmental energy sources has the potential to ensure unlimited, uncontrollable and unreliable energy for wireless sensor networks (WSNs), bringing a need to predict future energy availability for the effective utilization of the harvested energy. The majority of previous prediction approaches have exploited the diurnal cycle dividing the whole day into equal-length time slots in which predictions were carried out in each slot independently. This is not, however, efficient for wind energy as it exhibits non-controllable behaviour in that the amount of energy to be harvested varies over time. This paper proposes a novel approach to predict the wind energy for EH-WSNs depending on the energy generation profile of latest condition. The distinctive feature of the proposed approach is to consider the recent conditions in current-day, instead of past-day's energy generation profiles. The performance of the proposed algorithm is evaluated using real measurements in comparison with state-of-art approaches. Results show that the proposed strategy significantly outperforms the two popular energy predictors, EWMA and Pro-Energy. © 2017 Elsevier Ltden_US
dc.language.isoengen_US
dc.publisherElsevier Ltd
dc.relation.isversionof10.1016/j.energy.2017.05.175
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEnergy harvesting
dc.subjectEnergy prediction
dc.subjectWind power
dc.subjectWireless sensor networks
dc.subjectEnergy harvesting
dc.subjectForecasting
dc.subjectWind power
dc.subjectDiurnal cycle
dc.subjectEnergy generations
dc.subjectEnergy prediction
dc.subjectEnvironmental energy
dc.subjectFuture energies
dc.subjectReal measurements
dc.subjectTime slots
dc.subjectWireless sensor network (WSNs)
dc.subjectWireless sensor networks
dc.subjectalgorithm
dc.subjectenergy efficiency
dc.subjectenergy resource
dc.subjectnetwork analysis
dc.subjectpower generation
dc.subjectprediction
dc.subjectsensor
dc.subjectwind power
dc.subjectEnergy harvesting
dc.subjectEnergy prediction
dc.subjectWind power
dc.subjectWireless sensor networks
dc.subjectEnergy harvesting
dc.subjectForecasting
dc.subjectWind power
dc.subjectDiurnal cycle
dc.subjectEnergy generations
dc.subjectEnergy prediction
dc.subjectEnvironmental energy
dc.subjectFuture energies
dc.subjectReal measurements
dc.subjectTime slots
dc.subjectWireless sensor network (WSNs)
dc.subjectWireless sensor networks
dc.subjectalgorithm
dc.subjectenergy efficiency
dc.subjectenergy resource
dc.subjectnetwork analysis
dc.subjectpower generation
dc.subjectprediction
dc.subjectsensor
dc.subjectwind power
dc.titleAn energy prediction algorithm for wind-powered wireless sensor networks with energy harvestingen_US
dc.typearticleen_US
dc.relation.journalEnergyen_US
dc.contributor.departmentBayburt Universityen_US
dc.contributor.authorID36975673200
dc.identifier.volume139
dc.identifier.startpage1275
dc.identifier.endpage1280
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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