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dc.contributor.advisorKarki, Rajeshen_US
dc.contributor.advisorBillinton, Royen_US
dc.creatorThapa, Sumanen_US
dc.date.accessioned2014-02-27T12:00:11Z
dc.date.available2014-02-27T12:00:11Z
dc.date.created2014-01en_US
dc.date.issued2014-02-26en_US
dc.date.submittedJanuary 2014en_US
dc.identifier.urihttp://hdl.handle.net/10388/ETD-2014-01-1408en_US
dc.description.abstractWind power installations are growing rapidly throughout the world due to environmental concerns associated with electric power generation from conventional generating units. Wind power is highly variable and its uncertainty creates considerable difficulties in system operation. Reliable operation of an electric power system with significant wind power requires quantifying the uncertainty associated with wind power and assessing the capacity value of wind power that will be available in the operating lead time. This thesis presents probabilistic techniques that utilize time series models and a conditional probability approach to quantify the uncertainty associated with wind power in a short future time, such as one or two hours. The presented models are applied to evaluate the risk of committing electric power from a wind farm to a power system. The impacts of initial wind conditions, rising and falling wind trends, and different operating lead times are also assessed using the developed methods. An appropriate model for day-ahead wind power commitment is also presented. Wind power commitment for the short future time is commonly made equal to, or a certain percentage, of the wind power available at the present time. The risk in meeting the commitment made in this way is different at various operating conditions, and unknown to the operator. A simplified risk based method has been developed in this thesis to assist the operator in making wind power commitments at a consistent level of risk that is acceptable to the system. This thesis presents a methodology to integrate the developed short-term wind models with the conventional power generation models to evaluate the overall operational reliability of a wind integrated power system. The area risk concept has been extended to incorporate wind power, evaluate the unit commitment risk and the well- being indices of a power system for a specified operating lead time. The method presented in this thesis will assist the operator to determine the generator units and the operating reserve required to integrate wind power and meet the forecast load for a short future time while maintaining an acceptable reliability criterion. System operators also face challenges in load dispatch while integrating wind power since it cannot be dispatched in a conventional sense, and is accepted as and when present in current operational practices. The thesis presents a method to evaluate the response risk and determine the unit schedule while satisfying a specified response risk criterion incorporating wind power. Energy storage is regarded as an effective resource for mitigating the uncertainty of wind power. New methods to incorporate energy storage with wind models, and with wind-integrated power system models to evaluate the wind power commitment risk and unit commitment risk are presented in this thesis. The developed methods and the research findings should prove useful in evaluating the operating risks to wind farm operators and system operators in wind integrated power systems.en_US
dc.language.isoengen_US
dc.subjectPower system, operation, reliability, wind power commitment risk, unit commitment risk, response risk, energy storage systemen_US
dc.titleOperating risk analysis of wind integrated generation systemsen_US
thesis.degree.departmentElectrical and Computer Engineeringen_US
thesis.degree.disciplineElectrical Engineeringen_US
thesis.degree.grantorUniversity of Saskatchewanen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophy (Ph.D.)en_US
dc.type.materialtexten_US
dc.type.genreThesisen_US
dc.contributor.committeeMemberFaried, Sherif O.en_US
dc.contributor.committeeMemberPark, Peteren_US
dc.contributor.committeeMemberChen, Lien_US
dc.contributor.committeeMemberKlymyshyn, David M.en_US


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