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 methodology to retail energy forecasting in order to feed the forecasts to a conservative trading strategy. The problem is dissected into two sub-problems: load per customer forecasting and 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 (MAPE) of both daily and monthly energy, over a commonly used method that assumes constant customer attrition rate.
