Peak Model Variables

The SAE variables for Peak models are modified to account for the coincidence of end uses with the peak hour in each month. For example, in summer months, lighting loads have relatively low coincidence with peak values. In winter, lighting loads have relatively high coincidence with peak values. As a result, lighting efficiency improvements have a bigger impact on winter peaks than on summer peaks. This is mainly an issue for the Other end uses. In the SAE peak models, the XHeat and XCool variables are defined as shown above. These values are interacted with relevant weather variables in the model. The XOther variable is defined to include the peak coincidence factors.

First, for each end use in the XOther category, monthly intensities are converted to an average hourly intensity by dividing by the end-use energy estimate by the number of hours in the month. These values are multiplied by the coincidence factor, which represents the load at the time of the utility system peak relative to the average load for each use. The result for each month is an estimate of the contribution of each end use to the utility system peak in that month. These estimates are summed across the end uses in XOther for each sector, then summed across sectors.

In these equations, CF is the peak coincidence factor for the end use. This is a ratio representing load at time of the utility peak relative to average load for a month.