An environmental‐friendly green energy system with a real wind speed prediction based on innovative hierarchical forecast error correction model

Precise forecasting of wind speed is an important technology to permit the reliable and efficient operation of sustainable energy system. Here, the authors offer an effective windspeed prediction (EWSP) technique based on advanced forecast error correction model(AFECM). Ramapuram, Chennai is selected to fit the wind-energy-based systems and ENNORE thermal power station, Chennai is selected to decrease the carbon footprints. In the proposed technique, the error correction model is made to produce the final forecast. The proposed wind speed prediction based on innovative hierarchical forecast error correction model reveals that with the proposed AFEC+MSVM technique, the hourly aver-age RMSEs, MADs, MSEs and MAPEs in Delivery 24 are decreased by 2.277%, 1.012%,0.234%, and 1.245 % as compared to the normal SVM technique, while with AFEC+SVM method, average errors in RMSEs, MADs, MSEs and MAPEs in Delivery-24 are reduced by 3.385%, 2.056%, 1.956% and 2.546% as compared with the normal SVM technique, whereas the forecasting errors with AFEC+BP method, the middling errors in RMSEs, MADs, MSEs and MAPEs in Delivery-24 are decreased by 2.867%, 1.654%, 1.834% and2.298%, compared with simple BP method. The study displays that 1,485,550 kg CO2emission is decreased from the ENNORE thermal power plant.

Attribution 4.0 International