Energy Procedia · 2015 · 31 citations · 10 references
EngineeringComputer ScienceElectrical EngineeringArtificial IntelligenceMachine LearningQuality EngineeringElectrical MeasurementElectrical System DiagnosticsElectrical TechnologyNeural NetworksPower QualityPower SystemsElectrical Power QualityNeural Network ModelingNeural Network-based EstimationPower Quality AssessmentPower Quality IndicesPower Quality MeasurementPower Quality ModelingPower Quality Monitoring
The aim of this paper is to present a Total Power Quality Index (TPQI) for estimating Power Quality (PQ) at a specific site of the electric network using Artificial Neural Network (ANN) methodology techniques and a variety of methods from Machine Learning. The main advantage of this methodology is the avoidance of certain arbitrary parameters used in previous research efforts implementing a Fuzzy Index Model. For the purposes of this study and for the training process of the proposed ANN model additional data derived from Power Quality measurements along with an appropriate questionnaire which gathered the opinion of experts was used. The proposed methodology appeared to be flexible, reprogrammable with the capability to assimilate new measurements and estimations in any specific case study. The outcome of the proposed ANN model is compared with the corresponding previously introduced Fuzzy Index model over three different case studies, providing significant results for further improvement.
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Nabeel M. Gazzaz, Mohd Kamil Yusoff, Ahmad Zaharin Aris et al. · Marine Pollution Bulletin · 2012 · 406 citations
Natural Resources, Hydrology, Water Resources Management +10
Math Bollen · Electric Power Systems Research · 2003 · 249 citations