Date of Award
Master of Science
Electrical and Computer Engineering
As utilities become more interested in using renewable energy to power the grid, the problem becomes how to size and locate the generation facilities. This thesis approaches the idea of using distributed medium scale generation facilities at the distribution feeder level. We propose an algorithm to determine the optimum size of a photovoltaic(PV) array and an energy storage system for a distribution feeder. The cost of operating a feeder is quantified by considering the net load at the substation, voltage changes, load following, and the initial cost of implementing a photovoltaic system and a battery energy storage system. The PV inverter is utilized in order to improve the voltage on the circuit and is sized proportionally to the array size. The energy storage system operates in peak shaving and load following capacities in order to reduce stress on current generation facilities. The algorithm then operates to minimize the total cost of the feeder operation for a year by sizing these distributed generation resources utilizing particle swarm optimization. Optimization of a real-world system yielding results where the power at the substation (including all losses) is reduced by 5.39% over the course of a year and the average voltage drop on the circuit is improved by 50.17% using the proposed photovoltaic inverter control scheme.
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