A Naïve multiple linear regression benchmark for short term load forecasting

Benchmarking issue in short term load forecasting has not received as much attention as it deserves. Although dozens of techniques have been reported to be applied to short term load forecasting, most of them are still on the theoretical level with insignificant practical value. None of them has been established to produce benchmarking models for comparative assessment. This paper proposes a naïve multiple linear regression benchmark for short term load forecasting, which is from the experience of helping a US utility develop the first in-house short term load forecasts. The proposed model has been served as a benchmark for this utility since 2009, and was in production use for a year with satisfying performance before a major upgrade. It has also been used for a Canadian utility for load forecasting purposes. In addition, it was reproduced by a group of graduate students from a creditable US university following the documented procedure.