Long-Term Retail Energy Forecasting With Consideration of Residential Customer Attrition

Deregulation of the electric power industry has created both wholesale markets and retail markets. Most load forecasting studies in the literature are on the wholesale side. Minimal research efforts have been devoted to tackling the challenges on the retail side, such as limited data history and high customer attrition rate. This paper proposes a comprehensive solution to long-term retail energy forecasting in order to feed the forecasts to a conservative trading strategy. We dissect the problem into two sub-problems: 1) load per customer forecasting; and 2) tenured customer forecasting. Regression analysis and survival analysis are applied to each sub-problem respectively. The proposed methodology has been implemented at a fast growing retailer in the U.S., showing superior performance in terms of mean absolute percentage error of hourly demand and daily and monthly energy over a common industry practice that assumes constant customer attrition rate.