USING ARTIFICIAL NEURAL NETWORKS FOR ELECTRIC LOAD FORECASTING
In today’s evolving energy landscape, accurate electric load forecasting has become critical for ensuring the stability and efficiency of power systems. Traditional methods often fall short due to increasing system complexity and variability. Therefore, this article explores the use of Artificial Neural Networks (ANNs) as a modern, adaptive solution. It highlights the strengths of ANNs in handling nonlinear data, integrating multiple input variables, and learning from past patterns. Moreover, it discusses challenges such as data requirements and interpretability. Ultimately, the article concludes that ANNs offer substantial benefits and will play a key role in the future of sustainable energy management.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-04-22
- DOI
- https://doi.org/10.5281/zenodo.15258976
- Primary Topic
- Prenatal Screening and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00