Efficient day-ahead energy forecasting for microgrids using LSTM optimized by grey wolf algorithm

As distributed energy resources become increasingly integrated into power systems, accurate day-ahead load-forecasting is essential for effective microgrid (MG) management—enabling optimized energy generation, reduced reliance on the main grid. However, forecasting energy demand remains a significan...

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Bibliographic Details

Published in:	e-Prime: Advances in Electrical Engineering, Electronics and Energy
Main Authors:	Ahmed Khayat, Mohammed Kissaoui, Lhoussaine Bahatti, Abdelhadi Raihani, Khalid Errakkas, Youness Atifi
Format:	Article
Language:	English
Published:	Elsevier 2025-09-01
Subjects:	Load forecasting Machine learning Microgrid Energy management Long short-term memory Grey wolf optimizer
Online Access:	http://www.sciencedirect.com/science/article/pii/S2772671125001615