Demand Forecasting Methodologies This appendix outlines the approaches used by the Commission in undertaking the MD and energy projections. System-Wide Energy Projections The approach to modelling system energy demand was equivalent to that used for system MD. Energy demand was modelled on the major potential drivers of usage: population growth; economic activity; and trend growth. With limited data it was difficult to include many more factors. In each system, energy use reflected slightly different drivers. In all three systems, the underlying important measure was the level of energy use which reflects both that met by the system and that by PV. System-wide MD Projections The approach by the Commission had similarities to that used by PWC with rooftop PV and spot load being considered separately (that is, removed from the regression model) and the same data range (starting in 2006-07). The Commission examined the drivers of overall regional MD for the three power systems. Econometric analysis was again undertaken examining a number of functional forms and the appropriate explanatory variables. There was no preferred model as all four functional forms considered (linear, log linear, linear log and double log) provided reasonable explanations of changes in maximum demand. The most appropriate model form was determined to be double-log for Darwin-Katherine and Alice Springs, and a linear-log for Tennant Creek. The best estimate of overall change varied across the systems. Growth for energy use in Tennant reflected broad population growth. This suggests that trend rate of growth slows over time. For Alice Springs the sole explanatory variable was trend. This suggests a constant rate of decline over time. Finally, Darwin-Katherine was best explained by a combination of economic activity and population. The coefficients suggest that growth is fairly constant but that the impact of economic surges can be perverse. Temperature was not a significant explanator in the regression. The P10 MD was developed from the regression estimate using the regression error (1.4 standard deviations). Zone Substation MD Projections
Demand Forecasting Methodologies This appendix outlines the approaches used by the Commission in undertaking the MD and energy projections. System-Wide Energy Projections The approach to modelling system energy demand was equivalent to that used for system MD. Energy demand was modelled on the major potential drivers of usage: population growth; economic activity; and trend growth. With limited data it was difficult to include many more factors. In each system, energy use reflected slightly different drivers. In all three systems, the underlying important measure was the level of energy use which reflects both that met by the system and that by PV. System-wide MD Projections The approach by the Commission had similarities to that used by PWC with rooftop PV and spot load being considered separately (that is, removed from the regression model) and the same data range (starting in 2006-07). The Commission examined the drivers of overall regional MD for the three power systems. Econometric analysis was again undertaken examining a number of functional forms and the appropriate explanatory variables. There was no preferred model as all four functional forms considered (linear, log linear, linear log and double log) provided reasonable explanations of changes in maximum demand. The most appropriate model form was determined to be double-log for Darwin-Katherine and Alice Springs, and a linear-log for Tennant Creek. The best estimate of overall change varied across the systems. Growth for energy use in Tennant reflected broad population growth. This suggests that trend rate of growth slows over time. For Alice Springs the sole explanatory variable was trend. This suggests a constant rate of decline over time. Finally, Darwin-Katherine was best explained by a combination of economic activity and population. The coefficients suggest that growth is fairly constant but that the impact of economic surges can be perverse. Temperature was not a significant explanator in the regression. The P10 MD was developed from the regression estimate using the regression error (1.4 standard deviations). Zone Substation MD Projections