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A regression-based approach to short-term system load forecasting
Abstract
A linear regression-based model for the calculation of short-term system load forecasts is described. The model's most significant aspects fall into the following areas: innovative model building, including accurate holiday modeling by using binary variables and temperature modeling by using heating and cooling degree functions; robust parameter estimation and parameter estimation under heteroskedasticity by using weighted least-squares linear regression techniques; use of 'reverse errors-in-variables' techniques to mitigate the effects on load forecasts of potential errors in the explanatory variables; and distinction between time-independent daily peak load forecasts and the maximum of the hourly load forecasts in order to prevent peak forecasts from being negatively biased. The model was tested under a wide variety of conditioning and is shown to produce excellent results.>
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Cites
Huber, P. J. (1981) · Wiley Series in Probability and Statistics · doi:10.1002/0471725250 · Cited by 7,066
Cited by
Yildiz, B., Bilbao, J. I., & Sproul, A. B. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.02.023 · Cited by 560
Short-term load forecasting using lifting scheme and ARIMA models
Lee, C.-M., & Ko, C.-N. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.11.033 · Cited by 438
Chen, J.-F., Wang, W.-M., & Huang, C.-M. (1995) · Electric Power Systems Research · doi:10.1016/0378-7796(95)00977-1 · Cited by 253
A hybrid method based on wavelet, ANN and ARIMA model for short-term load forecasting
Fard, A. K., & Akbari-Zadeh, M.-R. (2014) · Journal of Experimental & Theoretical Artificial Intelligence · doi:10.1080/0952813x.2013.813976 · Cited by 134
Qiu, X., Zhu, H., Suganthan, P. N., & Amaratunga, G. A. J. (2017) · Communications in Computer and Information Science · doi:10.1007/978-981-10-6427-2_2 · Cited by 7
Metadata
- Authors
- Papalexopoulos, A. D., & Hesterberg, T. C.
- Venue
- IEEE Transactions on Power Systems
- Published
- 1990
- Volume
- 5
- Issue
- 4
- Pages
- 1535-1547
- ISSN
- 0885-8950 (ISSN-L)
- OpenAlex
- W2105916576
- Cited by
- 823
- References
- 1
- FWCI
- 2.86
- Type
- journal article
- Language
- en
- Open access
- closed
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- Papalexopoulos, A. D., & Hesterberg, T. C. (1990). A regression-based approach to short-term system load forecasting. IEEE Transactions on Power Systems. https://doi.org/10.1109/59.99410
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
