Stochastic Model for Generation of High-Resolution Irradiance Data and Estimation of Power Output of Photovoltaic Plants
| Autor: | Carmen L. T. Borges, Cleber Onofre Inacio |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Series (mathematics)
Markov chain Renewable Energy Sustainability and the Environment Stochastic modelling 020209 energy Photovoltaic system Irradiance 02 engineering and technology Solar Resource Stochastic simulation 0202 electrical engineering electronic engineering information engineering Environmental science Time series Remote sensing |
| Zdroj: | IEEE Transactions on Sustainable Energy. 9:952-960 |
| ISSN: | 1949-3037 1949-3029 |
| DOI: | 10.1109/tste.2017.2767780 |
| Popis: | This paper presents a method for the generation of synthetic time series of solar radiation with a one-minute time resolution using an automatic cloud classification procedure. Solar radiation data from ground-based measurements are used to determine the correlation between the irradiance and the prevailing cloud classes extracted from satellite images. A specific set of Markov chains for each cloud class is adjusted empirically and used for a stochastic simulation of clear sky index time series. The different models are then combined to convert the irradiance into power output time series of photovoltaic power plants of different sizes. Tests to determine the methodology's performance showed positive results in reproducing the statistical characteristics of observed time series data. Estimates of a selected set of metrics were obtained for several sites in Brazil and allowed the characterization of the solar resource for photovoltaic plants of various sizes and mounting methods considering the generation potential and short-term variability. |
| Databáze: | OpenAIRE |
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