2.7 Combination of ANN with fuzzy logic pre-processing

Sivaneasan [14] develops an improved solar forecasting algorithm by combining fuzzy logic pre-processing and artificial neural network (ANN) model. The fuzzy pre-processing is used to calculate the correlation between temperature, cloud cover, wind speed, and direction with irradiance values. In this method, a threelayer feed forward with back-propagation model is applied as the neural network training algorithm. An error correction factor is proposed to reduce forecast errors by combining the error from the previous 5-min estimated output in the input layer. The evaluation results demonstrate that the error correction factor combined with the ANN approach improves solar irradiance forecasting accuracy due to its adaptive error correction capability. The forecasting accuracy of the proposed method is compared with other ANN forecasting algorithms. The results show that the proposed method has a better performance.
