Spatio-Temporal Modelling of Wind Power Ramps in Alberta

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dc.contributor.advisorSezer, Deniz
dc.contributor.advisorZareipour, Hamidreza
dc.contributor.authorMahmoudi Gharaie, Maryam
dc.contributor.committeememberWood, David
dc.contributor.committeememberAminghafari, Mina
dc.date2024-11
dc.date.accessioned2024-09-27T21:52:45Z
dc.date.available2024-09-27T21:52:45Z
dc.date.issued2024-09-27
dc.description.abstractThe goal of this thesis is to model wind power ramps using a three-state Markov chain. The ramp detection technique employed is known as L1-SW in the literature. Within the Markov chain, the states’ transition probabilities are governed by a Gaussian process with a separable spatiotemporal covariance function, designed to capture the space-time dependencies across wind farms. The three states of the Markov chain are ramp up (+1), ramp down (-1), and non-ramp interval (0). The parameters of this model are estimated using a Bayesian inference framework, specifically employing no U-Turn Sampler (NUTS), which is a Hamiltonian Monte Carlo (HMC) Method. The inference procedure is implemented using RStan, an interface for working with Stan in R. The results demonstrate that our model effectively captures the properties of wind power ramps. This model is then extended to predict the ramping behavior of future, not-yet-established wind farms.
dc.identifier.citationMahmoudi Gharaie, M. (2024). Spatio-temporal modelling of wind power ramps in Alberta (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.
dc.identifier.urihttps://hdl.handle.net/1880/119925
dc.language.isoen
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgary
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectWind power
dc.subjectWind power ramps
dc.subjectMarkov chain
dc.subjectGaussian process
dc.subjectSpatio-temporal Process
dc.subjectCovariance function
dc.subjectHamiltonian Monte Carlo
dc.subjectNo U-Turn Sampler
dc.subjectRStan
dc.subjectBayesian inference
dc.subjectWind farm
dc.subjectHMC
dc.subject.classificationEngineering--Electronics and Electrical
dc.subject.classificationMathematics
dc.subject.classificationStatistics
dc.titleSpatio-Temporal Modelling of Wind Power Ramps in Alberta
dc.typemaster thesis
thesis.degree.disciplineMathematics & Statistics
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.thesis.accesssetbystudentI do not require a thesis withhold – my thesis will have open access and can be viewed and downloaded publicly as soon as possible.
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