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Document Type

Thesis - University Access Only

Award Date

2013

Degree Name

Master of Science (MS)

Department / School

Electrical Engineering and Computer Science

First Advisor

Mahdi Farrokh Baroughi

Abstract

Environmental benefits, abundance and omnipresence of sunlight, easy installation and developments in the smart grid concept are the key features encouraging installation of photovoltaic power plants. However, the output power from a photovoltaic power plant is highly variable in nature. Several studies have shown that combining spatially diverse PV power plants can smooth out the total PV power output and reduce variability caused by intermittent clouds. But there are no reports of investigating the effect of spatially diverse photovoltaic power plants with different weather conditions in a power system with high-resolution irradiance data. The objective of this research was to develop a quantitative understanding of the impact of irradiance fluctuations on the output power of a single and multiple grid connected PV power plants. The voltage at the point of common coupling fluctuates as power fluctuates which becomes worse on days with popcorn clouds, and is proportional to the PV power penetration. A novel method utilizing an array of four sensors capable of sampling at high rate was developed to measure cloud shadow speed and direction to predict irradiation and PV power. A IEEE-34 node test feeder was used to simulate a power grid with PV power plants. The results indicated that power and irradiance could be predicted for the short-term (2-3 min) using high-resolution cloud information measured by ground based irradiance sensors. The irradiation forecasting method developed using distributed sensing can be used to forecast power output of a PV plant. The forecast information can be used to decide when to curtail PV power to decrease ramp rate. This is the first report of implementing spatially diverse PV power plants in a power feeder with high-resolution irradiance data measured by ground based sensors. Future work can include implementing short term irradiance forecasting for spatially diverse PV plants modeled in IEEE-34 node test feeder to reduce ramp rate by curtailing PV power. This work could be used as a test bed for operation of PV fleet as a schedulable and dispatchable power plant unit which would be controlled by dedicated communication link to a central control unit where each PV power plant would be capable of predicting its own power output in different range (short-, medium- and long-term).

Library of Congress Subject Headings

Photovoltaic power systems
Weather forecasting
Renewable energy sources

Description

Includes bibliographical references (pages 99-107)

Format

application/pdf

Number of Pages

126

Publisher

South Dakota State University

Rights

In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/

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