Forecasting Power Output of Photovoltaic Systems Based on Weather Classification and Support Vector Machines

@article{Shi2011ForecastingPO,
  title={Forecasting Power Output of Photovoltaic Systems Based on Weather Classification and Support Vector Machines},
  author={Jie Shi and Wei-Jen Lee and Yongqian Liu and Yongping Yang and Peng Wang},
  journal={2011 IEEE Industry Applications Society Annual Meeting},
  year={2011},
  pages={1-6}
}
Due to the growing demand on renewable energy, photovoltaic (PV) generation systems have increased considerably in recent years. However, the power output of PV systems is affected by different weather conditions. Accurate forecasting of PV power output is important for system reliability and promoting large-scale PV deployment. This paper proposes algorithms to forecast power output of PV systems based upon weather classification and support vector machines (SVM). In the process, the weather… CONTINUE READING

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  • However, in the morning, evening, or under rainy weather conditions, the forecasting precision is lower, and sometimes the relative mean square error (RMSE) can be higher than 50%.

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