Electrical load and solar power forecasting using machine learning techniques

Abstract In contemporary power networks, short-term load forecasting (STLF) is essential for efficiently managing reserve requirements. During the power-balancing operation, it then helps the grid operator make wise and cost-effective decisions. This paper thoroughly examines STLF techniques includi...

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Auteur principal:	Saroj Kumar Panda
Format:	Artigo
Langue:	Inglês
Publié:	Springer 2025-07-01
Collection:	Journal of King Saud University: Engineering Sciences
Sujets:	Renewable energy Artificial neural network Particle swarm optimization Short-term load forecasting Enhanced particle swarm optimization Machine learning techniques (MLT)
Accès en ligne:	https://doi.org/10.1007/s44444-025-00012-y
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