Propane demand modeling for residential sectors- A regression analysis
Shenoy, Nitin K.
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This thesis presents a forecasting model for the propane consumption within the residential sector. In this research we explore the dynamic behavior of different variables that affect the propane consumption and develop a forecasting model. The significant factors that had an impact on the propane consumption in houses were heating degree days of that area, wind speed, precipitation and the size of the houses. However in case of mobile homes only the heating degree days had significance. The behavior of the customers was assumed to be static. This model is based on multiple regression methods. The data was collected from a local propane company in West Texas. Different combinations of months were used in this model to study the propane consumption behavior for each month. These different studies were used to generate the final forecasting model. As propane consumption was low for the months from June to September, the best results were obtained when the data for the months from October through May was used for analysis. The results indicate that the forecasting model provides a potentially useful forecast.