Forecasts of electricity consumption and peak demand over time horizons of one or two decades are a key element in electric utilities' meeting their core objective and obligation to ensure reliable and affordable electricity supplies for their customers while complying with a range of energy and environmental regulations and policies. These forecasts are an important input to integrated resource planning (IRP) processes involving utilities, regulators, and other stake-holders. Despite their importance, however, there has been little analysis of long term utility load forecasting accuracy. We conduct a retrospective analysis of long term load forecasts on twelve Western U. S. electric utilities in the mid-2000s to find that most overestimated both energy consumption and peak demand growth. A key reason for this was the use of assumptions that led to an overestimation of economic growth. We find that the complexity of forecast methods and the accuracy of these forecasts are mildly correlated. In addition, sensitivity and risk analysis of load growth and its implications for capacity expansion were not well integrated with subsequent implementation. We review changes in the utilities load forecasting methods over the subsequent decade, and discuss the policy implications of long term load forecast inaccuracy and its underlying causes.
In this paper we propose a taxonomy for classifying COTS business applications, i.e. products that are used in the daily functioning of all types of organizations worldwide, such as ERP systems and document management tools. We propose the identification of characterization attributes to arrange the domains which these products belong to, and also we group these domains into categories. We define questions and answers as a means for browsing the taxonomy during COTS selection. We show the need of identifying and recording the relationships among the domains and propose the use of actor-oriented models for expressing these relationships as dependencies. Last, we explore the definition of quality models for the domains, to be used in COTS selection, focusing on their reusability and stepwise definition downwards the hierarchy. Category C1
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