Electrical & Computer Engineering, Department of

 

First Advisor

Fred Choobineh

Date of this Version

Fall 12-5-2019

Citation

Carlos Mendoza,"Optimal Allocation of Energy Storage and Wind Generation in Power Distribution Systems", Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, 2019

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Electrical Engineering, Under the Supervision of Fred Choobineh. Lincoln, Nebraska: December, 2019

Copyright 2019 Carlos Alberto Mendoza Santos

Abstract

The advent of energy storage technologies applications for the electric power system gives new tools for planners to cope with the operation challenges that come from the integration of renewable generation in medium voltage networks. This work proposes and implements an optimization model for Battery Energy Storage System (BESS) and distributed generation allocation in radial distribution networks. The formulation aims to assist distribution system operators in the task of making decisions on energy storage investment, BESSs' operation, and distributed generation penetration's level to minimize electricity costs. The BESSs are required to participate in energy arbitrage and voltage control. In addition, due to the complexity of the model formulated, a genetic algorithm combined with an AC multi-period optimal power flow implementation is used to solve the problem. The methodology provides the optimal connection points and size of a predetermined number of BESSs and wind generators, and the BESS's operation. The model considers the BESSs' charging/discharging efficiency, depth of discharge level, and the network's operation constraints on the nodal voltage and branches power flow limits. The proposed methodology was evaluated in the IEEE 33-bus system. The results show that BESSs investment in radial distribution systems facilitates the deployment of distributed generation and favors the reduction of generation costs despite its still high capital cost.

Adviser: Fred Choobineh

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