Dr. Sayed Reza with Dr. Habib Ullah and other collaborators has published a new paper in IEEE, titled “Descriptor: Global Electricity Markets Load Forecasting and Planning Dataset (GloElecLoad)”.
Read the paper: https://ieeexplore.ieee.org/document/11489469
This work introduces GloElecLoad, a comprehensive dataset designed to support research in electricity load forecasting, energy planning, and data‑driven decision making in global energy markets. The dataset provides structured and standardized data resources to enable researchers to develop and evaluate advanced machine learning and forecasting models across diverse electricity markets.
The publication contributes to the growing need for high-quality, accessible datasets in energy analytics, particularly as power systems become increasingly complex and data‑driven. By providing a global perspective, this work facilitates research on renewable integration, demand prediction, and intelligent energy systems, supporting both academic research and real-world applications.
This publication reflects the D3M Lab’s continued focus on data-centric research, open data resources, and interdisciplinary applications of machine learning in critical domains such as energy, infrastructure, and societal systems.