Copyright © 2017 International Journal of Development and Sustainability. All Rights Reserved.
International Journal of Development and Sustainability
ISSN: 2186-8662 – www.isdsnet.com/ijds
Volume 6 Number 11 (2017): Pages 1803-1823
ISDS Article ID: IJDS17101001
Abstract
The uncertainty management is a key challenge in grid operations and the probabilistic forecasts will play an important role toward this end as the penetration of photovoltaic solar generation continues to increase. Since so many different aspects can influence in forecasting of photovoltaic solar generation, mainly for this forecasting does an intermediate step of global solar irradiance forecasting, the probabilistic forecasting to predicting ramp events is increasingly used to deal with the factor of global solar irradiance dependence of the dynamics atmospheric and presence and level of clouds, and contribute to higher prediction accuracy through characterization of the ramp events. This paper proposes an algorithm for development of transition probabilities matrices to predicting ramp events, based on Markov model, for application, mainly in the local site where there is the absence of a long amount of solarimetric dates and clouds patterns information to represent the best characteristics of the ramp events. The tests are repeated for solar data set and observations are presented, prediction modeling results with distinct properties in terms of accuracy are achieved. The results show accuracy of 7 to 20% in performance of the prediction method developed, at time intervals presented, and your discussion evidences the importance of global solar irradiance prediction methods.
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