Masters Theses

Yang Liu

Abstract

"The work shown in this thesis is to develop an intelligent energy management and demand-response controller (IEMDC) for a photovoltaic-battery (PVB) system with a programmable load. Specifically, the research work related to this issue focuses on the modeling and real-time simulation of a microgrid with an emphasis on photovoltaic, battery and programmable load and the development of an energy management controller for optimally dispatching the power from the PVB system to the loads. The IEMDC is used for daytime grid-independent operation. The energy management controller is based on fuzzy logic controller (FLC) whose membership functions are optimized using mean-variance optimization (MVO). The controller is implemented in real-time on a digital signal processor (DSP) interfaced to a real-time digital simulator (RTDS).

The objective of the intelligent energy management and demand-response controller is threefold- first, to supply energy to meet the needs of the priority loads; secondly, to maintain a sufficient battery state of charge to meet the priority load demand in hours of short or no PV outputs; and thirdly, with the first and second objectives met, maximize supply to demand-responsive loads.

Results are presented for different types of days (sunny day, moderate day and rainy day) during daytime. The perfom1ance of the IEMDC is compared against traditional PV-priority controller and shown to deliver better performance. More priority load is satisfied even in worse weather condition: a higher state of charge of battery is maintained and the duty cycle for charge and discharge is reduced; controllable load participated in demand-response can be maximally satisfied"--Abstract, page iii.

Advisor(s)

Venayagamoorthy, Ganesh K.

Committee Member(s)

Corzine, Keith, 1968-
Kimball, Jonathan W.

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Sponsor(s)

National Science Foundation (U.S.)
United States. Office of Naval Research

Comments

Support from the National Science Foundation and Office of Naval Research under Grants: EFRI #0836017, ECCS #0348221 and N00014-07-1-0806

Publisher

Missouri University of Science and Technology

Publication Date

2012

Pagination

xi, 75 pages

Note about bibliography

Includes bibliographical references (pages 72-74).

Rights

© 2012 Yang Liu, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Subject Headings

Energy storage -- PlanningPhotovoltaic power generationFuzzy logicRobust optimizationReal-time control

Thesis Number

T 10258

Print OCLC #

863162589

Electronic OCLC #

908850122

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