Intelligent machine learning with evolutionary algorithm based short term load forecasting in power systems

• Main Authors: Mehedi, I. M., Bassi, H., Rawa, M. J., Ajour, M., Abusorrah, A., Vellingiri, M. T., Salam, Z., Abdullah, M. P.
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2021
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/94846/1/ZainalSalam2021_IntelligentMachineLearning.pdf; http://eprints.utm.my/id/eprint/94846/; http://dx.doi.org/10.1109/ACCESS.2021.3096918

Electricity demand forecasting remains a challenging issue for power system scheduling at varying stages of energy sectors. Short Term load forecasting (STLF) plays a vital part in regulated power systems and electricity markets, which is commonly employed to predict the outcomes power failures. Thi...