Voltage and Frequency Recovery in Power System and MicroGrids Using Artificial Intelligent Algorithms

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dc.contributor.advisorRezaei Zare, Afshin
dc.contributor.authorRahmani, Soleiman
dc.date.accessioned2019-11-22T18:33:41Z
dc.date.available2019-11-22T18:33:41Z
dc.date.copyright2019-04
dc.date.issued2019-11-22
dc.date.updated2019-11-22T18:33:41Z
dc.degree.disciplineElectrical and Computer Engineering
dc.degree.levelMaster's
dc.degree.nameMASc - Master of Applied Science
dc.description.abstractThis thesis developed an advanced assessment tools to recover the power system voltage margin to the acceptable values during the disturbance. First, the effect of disturbance in islanded microgrids are analyzed using power factor-based power-voltage curves and a comprehensive under voltage-frequency load shedding(UVFLS) method is proposed as a last resort in order to restore the system voltage and frequency. The effect of disturbance in conventional power system is investigated by introducing a phenomenon called fault induced delayed voltage recovery(FIDVR) and comprehensive real-time FIDVR assessments are proposed to employ appropriate emergency control approaches as fast as possible to maintain the system voltage margins within the desired range. Then, polynomial regression techniques have been used for predicting the FIDVR duration. Next, advanced FIDVR assessment is implemented which simultaneously predicts whether the event can be classified as FIDVR or not and also predicts the duration of FIDVR with high accuracy.
dc.identifier.urihttp://hdl.handle.net/10315/36644
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectEngineering
dc.subject.keywordsElectrical engineering
dc.subject.keywordsComputer science
dc.subject.keywordsPower system
dc.subject.keywordsMicrogrid
dc.subject.keywordsDistributed generation
dc.subject.keywordsInverter-based microgrids
dc.subject.keywordsLoad shedding
dc.subject.keywordsVoltage recovery
dc.subject.keywordsFrequency recovery
dc.subject.keywordsUnder frequency load shedding
dc.subject.keywordsUnder voltage load shedding
dc.subject.keywordsUnder voltage frequency load shedding
dc.subject.keywordsPower system stability
dc.subject.keywordsPower-voltage curve
dc.subject.keywordsPower factor-based power-voltage curve
dc.subject.keywordsFault induced delayed voltage recovery
dc.subject.keywordsSingle-phase induction motor
dc.subject.keywordsAir conditioner
dc.subject.keywordsMachine learning
dc.subject.keywordsSupervised learning
dc.subject.keywordsRegression
dc.subject.keywordsClassification
dc.subject.keywordsTime-series decision making
dc.subject.keywordsLinear regression
dc.subject.keywordsPolynomial regression
dc.subject.keywordsDecision tree
dc.subject.keywordsRandom forest
dc.subject.keywordsPrediction
dc.titleVoltage and Frequency Recovery in Power System and MicroGrids Using Artificial Intelligent Algorithms
dc.typeElectronic Thesis or Dissertation

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