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Reliability Constrained Optimal Investment in a Microgrid with Renewable Energy, Storage, and Smart Resource Management

dc.contributor.advisorKarki, Rajeshen_US
dc.contributor.committeeMemberBillinton, Royen_US
dc.contributor.committeeMemberChen, Lien_US
dc.contributor.committeeMemberMeda, Venkateshen_US
dc.creatorJansen, Ryanen_US
dc.date.accessioned2015-09-12T12:00:18Z
dc.date.available2015-09-12T12:00:18Z
dc.date.created2015-09en_US
dc.date.issued2015-09-11en_US
dc.date.submittedSeptember 2015en_US
dc.description.abstractEnvironmental concerns have led to a rapid increase in renewable energy development and production as the global demand for electricity continues to increase. The intermittent and uncertain nature of electricity generation from renewable sources, such as wind and solar, however, create significant challenges in maintaining power system reliability at reasonable costs. Energy storage and smart-grid technologies are perceived to provide potential solutions to these challenges in modern power systems of different sizes. This work investigates the opportunity to incorporate energy storage in microgrids with renewable energy production, as well as applying smart microgrid management techniques to reduce the lifetime costs while maintaining an acceptable level of reliability. A microgrid consisting of a 5 home community with generation supplied by two propane generators to meet the “N-1” reliability criterion is used as the base case scenario. Actual load data of typical homes is obtained from the industry partner. An equivalent loss of load expectation criterion is used to benchmark the acceptable reliability level. A model is developed to calculate the lifetime operational cost of the base case scenario which is used to assess the benefit of the addition of renewable energy sources, energy storage, and smart microgrid management techniques. A MATLAB program is developed to assess the 20 year operational costs of various combinations of renewable energy sources and battery energy storage, which will be considered the lifetime of the system. The combination of generation and storage which yields the lowest lifetime operational cost is defined as the optimized microgrid, and is used as a basis to determine if additional savings are realized by the implementation of a microgrid operated by a Smart Microgrid Management System (SMMS). The conceptual layout of the proposed SMMS is presented along with identified methods of utilizing in-home thermal storage. The SMMS mechanism is discussed along with proposed functionality, potential methods of employment, and associated development and implementation costs. The microgrid operated by the SMMS is assessed, and its lifetime operational cost is presented and contrasted against the base case microgrid and the optimized microgrid. A power system reliability evaluation of the proposed microgrids are conducted using a probabilistic method to ensure that reliability is not sacrificed by the implementation of a cost-minimized microgrid. A sequential Monte Carlo simulation model is developed to assess the power system reliability of the various microgrid configuration cases. The functionality of this model is verified using an existing reliability assessment program. The results from the presented studies show that the implementation of renewable energy sources, energy storage, and smart microgrid management techniques are an effective way of reducing the operational cost of a remote microgrid while increasing its power system reliability.  en_US
dc.identifier.urihttp://hdl.handle.net/10388/ETD-2015-09-2180en_US
dc.language.isoengen_US
dc.subjectsmart griden_US
dc.subjectload managementen_US
dc.subjectthermal storageen_US
dc.subjectenergy storageen_US
dc.subjectintelligent algorithmen_US
dc.subjectfinancial viabilityen_US
dc.subjectautomated controlen_US
dc.subjectdemand side managementen_US
dc.subjectmicrogriden_US
dc.subjectrenewable energyen_US
dc.titleReliability Constrained Optimal Investment in a Microgrid with Renewable Energy, Storage, and Smart Resource Managementen_US
dc.type.genreThesisen_US
dc.type.materialtexten_US
thesis.degree.departmentElectrical and Computer Engineeringen_US
thesis.degree.disciplineElectrical Engineeringen_US
thesis.degree.grantorUniversity of Saskatchewanen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Science (M.Sc.)en_US

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