In this work, a size optimization approach for utility-scale solar photovoltaic (PV) systems is proposed. The purpose of the method is to determine the optimal solar energy generation capacity and optimal location by the minimizing total system cost subject to the constraint that the system reliability requirements. Due to the stochastic characteristic of the solar irradiation, the reliability performance of a power system with PV generation is quite different from the one with only conventional generation. Basically, generation adequacy level of power systems containing solar energy is evaluated by reliability assessment and the most widely used reliability index is the loss of load probability (LOLP). The value of LOLP depends on various factors such as power output of the PV system, outage rate of generating facilities and the system load profile. To obtain the LOLP, the Monte Carlo method is applied to simulate the reliability performance of the solar penetrated power system. The total system cost model consists of the system installation cost, mitigation cost, and saving fuel and operation cost. Mitigation cost is accomplished with N-1 contingency analysis. The cost function minimization process is implemented in Genetic Algorithm toolbox, which has the ability to search the global optimum with relative computational simplicity. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/71815 |
| Date | 19 July 2016 |
| Creators | Chen, Xiao |
| Contributors | Electrical and Computer Engineering, Centeno, Virgilio A., De La Ree, Jaime, Kekatos, Vasileios |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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