Masters Theses

Keywords and Phrases

Monte Carlo; Stochastic Model; TMY3 Data; Vanadium Redox Battery

Abstract

"Photovoltaic (PV) Microgrids have been proven to be a useful technology in providing an environmentally friendly source of energy when compared to the use of fossil fuels. Accurately characterizing the performance of a microgrid system would ensure that the system is appropriately sized to meet electrical loads without a heavy reliance on diesel generators. A microgrid that is sized properly will reduce the cost of diesel fuel, while also reducing the risk of wasting money on an oversized system. A deterministic model which was created to characterize the performance of PV microgrids based on percent of time generator running was modified in order to perform a stochastic Monte Carlo analysis. The analysis used four random variables: global horizontal irradiance (GHI), ambient temperature, vanadium redox battery state of charge (VRB SOC), and energy load. Values for these variables in the model will be generated using PDFs derived from probability plots. Data for GHI and ambient temperature were taken from a TMY3 data set for the microgrid locations. Energy load data was collected over eight months and used to characterize the energy load for one year. The VRB SOC distribution was determined using engineering judgment. Three test methods will be performed on two microgrid systems to predict the performance of each system using stochastic and deterministic methods."--Abstract, page iv.

Advisor(s)

Elmore, A. Curt

Committee Member(s)

Crow, Mariesa
Maerz, Norbert H.

Department(s)

Geosciences and Geological and Petroleum Engineering

Degree Name

M.S. in Geological Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2015

Journal article titles appearing in thesis/dissertation

Using TMY3 data to stochastically predict the performance of a PV/VRB microgrid

Pagination

ix, 63 pages

Note about bibliography

Includes bibliographical references.

Rights

© 2015 Kayla Marie Speidel, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Subject Headings

Photovoltaic power generationSmart power gridsVanadium -- Electric propertiesStochastic analysis

Thesis Number

T 10698

Electronic OCLC #

913516090

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