Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking
Access Status
Open access
Authors
Barbieri, Florian Benjamin Eric
Date
2019Supervisor
Arindam Ghosh
Type
Thesis
Award
PhD
Metadata
Show full item recordFaculty
Science and Engineering
School
School of Electrical Engineering, Computing, and Mathematical Sciences
Collection
Abstract
Tracking clouds with a sky camera within a very short horizon below thirty seconds can be a solution to mitigate the effects of sunlight disruptions. A Probability Hypothesis Density (PHD) filter and a Cardinalised Probability Hypothesis Density (CPHD) filter were used on a set of pre-processed sky images. Both filters have been compared with the state-of-the-art methods for performance. It was found that both filters are suitable to perform very-short term irradiance forecasting.
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