A model for the effect of aggregation on short term load forecasting

In this work, we propose a simple empirical scaling law that describes load forecasting accuracy at different levels of aggregation. We show that for the short term forecasting problem, aggregating more users will improve the relative forecasting performance up to a point. Beyond this point, no more improvement in relative performance can be obtained.