An environmental‐friendly green energy system with a real wind speed prediction based on innovative hierarchical forecast error correction model. Issue 6 (15th February 2022)

• Record Type: Journal Article
• Authors: Akhtar, Iram; Altamimi, Abdullah; Khan, Zafar Ali; Kirmani, Sheeraz
• Is Part Of: IET renewable power generation. Volume 16:Issue 6(2022)
• Page Start: 1180
• Page End: 1193
• Publication Date: 2022-02-15
• Subjects: Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/rpg2.12425
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract: 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 wind speed 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 average 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% and 2.298%, compared with simple BP method. The study displays that 1, 485, 550 kg CO2 emission is decreased from the ENNORE thermal power plant.