Optimal photovoltaic size estimation for a campus area considering uncertainties in load, power generation and electricity rates

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2015-6

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Ali, Syed Muhammad Hassan

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The objective of this thesis is to develop simulation based optimization tools to determine the best strategy for photovoltaic (PV) installations at a campus environment (Middle East Technical University, Northern Cyprus Campus) with consideration of available risks and uncertainties in load, power generation and electricity rates. The first step is to accurately characterize the electricity consumption (load) pattern of the campus. Electricity demand is modeled using different forecasting models based on hourly, daily, monthly and yearly time scales. To minimize supply-demand mismatches, the second step of this study is to characterize the amount of solar power generation of a simple PV system. Probabilistic characterization is used for predicting electricity consumption and solar resources. Based on the forecasted values of electricity consumption and solar PV output for 20 years, economic feasibility analysis is performed using Monte Carlo simulation. For the entire lifetime (20 years) of PV system, two different options are analyzed economically; one time installation of 1 MW solar PV power plant, and stepwise installation of solar PV power plant (installing 1 MW after every 7 years). Both cases are analyzed for four different scenarios; constant electricity prices and increasing demand, increasing electricity prices and demand, constant prices and constant demand, and last increasing prices and constant demand. According to our results, although both the cases are feasible under all scenarios, the most feasible size for solar PV installation at METU NCC is between 2 MW – 3 MW.

Subject Keywords

Solar PV, Sizing, University, Stochastic, Optimization, Monte Carlo

URI

https://hdl.handle.net/11511/69833

Collections

Northern Cyprus Campus, Thesis

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Citation Formats

S. M. H. Ali, “Optimal photovoltaic size estimation for a campus area considering uncertainties in load, power generation and electricity rates,” M.S. - Master of Science, Middle East Technical University, 2015.