Which historical data is best to use for predicting line loading on a hot day?

Utilizing data from a day last year with a similar temperature is the most effective approach for predicting line loading on a hot day, as it directly correlates historical demand with the current weather conditions. Temperature significantly affects electricity usage, and patterns of consumption can vary widely based on seasonal factors.

When you select a day from the previous year that experienced similar temperature conditions, you are essentially comparing apples to apples. This historical data captures the effects of heat on electrical consumption, likely reflecting the same upward trend in demand due to increased use of air conditioning and cooling systems, which are often responsible for the highest loads during hot weather.

In contrast, utilizing yesterday's load might not account for daily fluctuations or weather variations that can influence demand. Similarly, a week's "same day" load may not reflect the current year's specific weather patterns or any changes in overall energy consumption habits. Lastly, looking at the past winter's peak load is typically irrelevant when predicting demand on a hot day, as winter demands are driven by heating rather than cooling.

Thus, the most contextually relevant and predictive measure for line loading during extreme temperatures comes from similar historical conditions, making the choice of a comparable day last year the most logical option.