Process / pipelinePower system operation and planning
Load Forecasting
Load forecasting predicts future electrical demand on power systems across various time horizons: minutes to hours (short-term), days to weeks (medium-term), and months to years (long-term). Accurate forecasting is essential for economic dispatch, unit commitment, and system reliability. Methods range from classical statistical regression to modern machine learning approaches.
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Sources
- Hippert, H. S., Pedreira, C. E., & Souza, R. C. (2001). Neural networks for short-term load forecasting: A review and evaluation. IEEE Transactions on Power Systems, 16(1), 44-55. DOI: 10.1109/59.910770 ↗
- Charlton, J. D., Kalamara, E., & James, R. D. (2008). Quantifying electricity load profiles and demand patterns. Energy Policy, 36(1), 181-193. link ↗
- Bunn, D. W. (2005). Forecasting with Multiple Models: A Case Study of Electric Load Forecasting. Futures, 37(8), 896-906. DOI: 10.1016/j.futures.2005.01.004 ↗