Date of Award

2013

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Electrical Engineering

First Advisor

Lebby, Gary L.

Abstract

A biologically inspired method, involving the design of an energy manager, for coordinating the operation of a hybrid renewable residential micro-grid is presented. Flexible optimization procedures that minimize the cost of renewable distribution generators based upon the climate and location of the load profile have been developed and modeled in simulation. A novel design of a dual channel converter system and its control system forms the distributed energy storage (DES) system that features the capability of balancing the power flow in the micro-grid (even in the grid-off mode). The proposed energy management system utilizes a back propagation neural network in order to predict the state of charge (SOC) of the DES, yielding the reference value of control variables, which allows the micro-grid to respond to the desired operation conditions rapidly fast with acceptable controller error. Preliminary results indicate that the DES system allows for the implementation of energy management strategies in a technically viable manner.

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