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Photovoltaic Systems: Forecasting for Demand Response Management and Environmental Modelling to Design Accelerated Aging Tests

Abstract Distributed Renewable energy generators are now contributing a significant amount of energy into the energy grid. Consequently, reliability adequacy of such energy generators will depend on making accurate forecasts of energy produced by them. Power outputs of Solar PV systems depend on the stochastic variation of environmental factors (solar irradiance, ambient temperature & wind speed) and random mechanical failures/repairs. Monte Carlo Simulation which is typically used to model such problems becomes too computationally intensive leading to simplifying state-space assumptions. Multi-state models for power system reliability offer a higher flexibility in providing a description of system state evolution and an accurate representation ... (more)
Created Date 2017
Contributor Kadloor, Nikhil (Author) / Kuitche, Joseph (Advisor) / Pan, Rong (Advisor) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Subject Statistics / Energy / Sustainability / Accelerated tests / Distributed energy / Photovoltaics / Reliability / Support Vector Regression / Universal Generating Functions
Type Masters Thesis
Extent 99 pages
Language English
Reuse Permissions All Rights Reserved
Note Masters Thesis Industrial Engineering 2017
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis