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Title: Optimum design and reliability studies of stand-alone hybrid renewable energy microgrids
Author: Abdulkarim, Abubakar
ISNI:       0000 0004 6060 9299
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2016
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The research is designed to investigate the potential of renewable energy resources, e.g., wind and solar, and hence develop a suitable probabilistic model for these resources. Different stochastic models have been examined to determine the best one serving the purpose of the study. Methods for the design of hybrid microgrid systems consisting of wind/photovoltaic/diesel generators and energy storage supplying an isolated load will be explored. Finally, a model is developed that will determine the optimal sizes of the system components to minimize installation, operational costs and operation strategies to maximize both the benefits and reliability of the system. The model has been verified through applications to a test microgrid of common size. The results have shown a 70% reduction in gas emissions and an 80% reduction in energy costs. Sensitivity analysis is done to study the effects of various system parameters on the optimum design. The output of the optimal design has been used to model a microgrid using DlgSILENT software. This is to define new indices in order to investigate the reliability of the microgrid at different levels. The levels considered include system, busbar, and load point. The results have shown that diesel generators have the least busbar interruption indices. Load point indices are not sensitive to the component failure rates. In addition, a new approach has been proposed to study the effects that network structure has on the reliability of a microgrid. The line and inverter are the most critical components of the proposed microgrid. A technique has been proposed to study the impacts of site and size factors on the number of times a diesel generator starts. Furthermore, the effects of weather on the availability of the hybrid renewable energy microgrid have also been investigated using the Variable Boolean Logic Driven Markov process.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available