On Net Load and Invisible Solar Power Generation Estimation In Modern Power Systems

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atmire.migration.oldid4010
dc.contributor.advisorZareipour, Hamidreza
dc.contributor.advisorWood, David Howe
dc.contributor.authorShakerardakani, Hamid
dc.contributor.committeememberMessier, Geoffrey
dc.contributor.committeememberNowicki, Edwin Peter
dc.contributor.committeememberBergerson, Joule A
dc.contributor.committeememberLi, Yunwei
dc.date.accessioned2016-01-18T21:28:32Z
dc.date.available2016-01-18T21:28:32Z
dc.date.issued2016-01-18
dc.date.submitted2016en
dc.description.abstractIntegration of wind and solar power generation into power systems has grown significantly over the past decade. While system operators have managed the variable and non-dispatchable nature of these resources at current levels, their large-scale integration would pose new challenges in power systems operation procedures. In particular, net load, which is the conventional load minus the non-dispatchable generation, would significantly deviate from load as the penetration level increases. The main non-dispatchable sources of electricity generation are utility-scale and small- scale behind-the-meter wind and solar power. This thesis focuses on characteristics of the net load in power systems when a large amount of wind and solar power generation is integrated into the grid. Historical and simulated net load scenarios are analyzed from a variety of perspectives. It also evaluates the effect of wind integration level on the net load forecasting accuracy. Additionally, the thesis proposes two methodologies to estimate invisible solar power generation using the data from a limited number of sites. The first approach uses data mining tools to identify the critical sites for continuous monitoring. The second approach models the uncertainties of the invisible solar power production using fuzzy arithmetic applied to publicly available production data. This is the first study using public data in the field. Numerical simulations are provided based on California, Alberta, and Ireland power systems. The results show the importance of understanding the changes related to significant wind and solar power generation. New morning downward and an increased level of afternoon upward net load ramps were found compared to the conventional load. The net load was also found to be more volatile compared to the load. In addition, numerical results prove the efficiency and accuracy of the proposed methodologies for the invisible solar power generation estimation. The results showed that continuous monitoring of a small number of sites is enough for accurate estimations. Moreover, the fuzzy model is capable of producing accurate estimations by using public data of only 20 sites per subregion.en_US
dc.identifier.citationShakerardakani, H. (2016). On Net Load and Invisible Solar Power Generation Estimation In Modern Power Systems (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/27182en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/27182
dc.identifier.urihttp://hdl.handle.net/11023/2762
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
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.subjectEngineering--Electronics and Electrical
dc.subjectEngineering--Environmental
dc.subject.classificationRenewable Energyen_US
dc.subject.classificationbehind-the-meter solaren_US
dc.subject.classificationinvisible solar power generationen_US
dc.subject.classificationWind energyen_US
dc.subject.classificationsolar energyen_US
dc.subject.classificationnet loaden_US
dc.subject.classificationdata dimension reductionen_US
dc.subject.classificationCalifornia Renewable Portfolio Standarden_US
dc.subject.classificationforecastingen_US
dc.subject.classificationfuzzy systemsen_US
dc.titleOn Net Load and Invisible Solar Power Generation Estimation In Modern Power Systems
dc.typedoctoral thesis
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameDoctor of Philosophy (PhD)
ucalgary.item.requestcopytrue
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