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Improving Solar PV Scheduling using Statistical Techniques

Abstract The inherent intermittency in solar energy resources poses challenges to scheduling generation, transmission, and distribution systems. Energy storage devices are often used to mitigate variability in renewable asset generation and provide a mechanism to shift renewable power between periods of the day. In the absence of storage, however, time series forecasting techniques can be used to estimate future solar resource availability to improve the accuracy of solar generator scheduling. The knowledge of future solar availability helps scheduling solar generation at high-penetration levels, and assists with the selection and scheduling of spinning reserves. This study employs statistical techniques to improve the accuracy of solar resource for... (more)
Created Date 2016
Contributor Soundiah Regunathan Rajasekaran, Dhiwaakar Purusothaman (Author) / Johnson, Nathan G (Advisor) / Karady, George G (Advisor) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Statistics
Type Masters Thesis
Extent 63 pages
Language English
Reuse Permissions All Rights Reserved
Note Masters Thesis Electrical Engineering 2016
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis