Predictions of End-Use Electric Demand and Energy Use of Rural Residential Consumers
ABSTRACT RURAL electric power suppliers need methods and data from which to predict electric demand and energy use of rural customers. Electric demand and energy use data from 55 rural residential customers in Nebraska were gathered from May 1983 to September 1985. The customers were randomly selected from customer lists after stratification into three energy usage categories based on previous customer history. Regression analyses were used on subcategories within each major category to provide demand predictions based on subcategories of heating and cooling equipment. High correlations were found between heating and cooling degree-days and energy use. Linear regression of demand versus energy gave higher correlations than curvilinear regressions. Prediction equations of demand based on energy use are provided for six subcategories with different combinations of heating and cooling appliances.