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South Dakota State University

Spatially Diverse Photovoltaic Power Plants for Reduced Power and Voltage Fluctuation Using Weather Forecast

Abstract

dc:description.abstract

<p>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).</p>

Degree

thesis:*
Name thesis:degree_name
Master of Science (MS)
Level thesis:degree_level
Thesis - University Access Only
Discipline thesis:degree_discipline
Electrical Engineering and Computer Science
Year dc:date.available
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Dhakal, Sunil
Contributors dc:contributor
  • Mahdi Farrokh Baroughi

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • <p>In Copyright - Educational Use Permitted<br /><a href="http://rightsstatements.org/vocab/InC-EDU/1.0/">http://rightsstatements.org/vocab/InC-EDU/1.0/</a></p>
Language dc:language
en

Identifiers

dc:identifier.*
Repository record dc:identifier
https://openprairie.sdstate.edu/etd/1399
OAI identifier oai:identifier
oai:openprairie.sdstate.edu:etd-2402

Chain of custody

source
Harvested from
South Dakota State University
Base URL
openprairie.sdstate.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Dhakal, Sunil. Spatially Diverse Photovoltaic Power Plants for Reduced Power and Voltage Fluctuation Using Weather Forecast. Thesis - University Access Only thesis, 2013. https://openprairie.sdstate.edu/etd/1399