Energy End-Use Forecasting
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Technology Data Characterizing Refrigeration in Commercial Buildings: Application to End-Use Forecasting with COMMEND 4.0

Osman Sezgen and Jonathan G. Koomey

Energy Analysis Program
Lawrence Berkeley Laboratory
Berkeley, CA 94720
December 1995


In the United States, energy consumption is increasing most rapidly in the commercial sector. Consequently, the commercial sector is becoming an increasingly important target for state and federal energy policies and also for utility-sponsored demand side management (DSM) programs. The rapid growth in commercial-sector energy consumption also makes it important for analysts working on energy policy and DSM issues to have access to energy end-use forecasting models that include more detailed representations of energy-using technologies in the commercial sector. These new forecasting models disaggregate energy consumption not only by fuel type, end use, and building type, but also by specific technology.

Refrigeration's share of U.S. commercial-sector electricity consumption is 8%, which corresponds to 0.7 quads of primary energy consumption annually. Electricity consumption for refrigeration, however, is much more significant in particular building types than in the commercial sector as a whole. For example, refrigeration's share of electricity consumption for groceries, restaurants, and warehouses is 49%, 20% and 35%, respectively. Although smaller in absolute size than the savings associated with other energy end uses such as lighting and space conditioning, the potential cost-effective energy savings from refrigeration for some building types are large enough in percentage terms to warrant closer attention.

The disaggregation of the refrigeration end use in terms of specific technologies, however, is complicated by several factors. First, the number of configurations of refrigeration cases and systems is quite large. Also, energy use is a complex function of the refrigeration-case properties and the refrigeration-system properties. The Electric Power Research Institute's (EPRI's) Commercial End-Use Planning System (COMMEND 4.0) and the associated data development presented in this report attempt to address the above complications and create a consistent forecasting framework.

Expanding end-use forecasting models so that they address individual technology options requires characterization of the present floorstock in terms of service requirements, energy technologies used, and cost-efficiency attributes of the energy technologies that consumers may choose for new buildings and retrofits. This report describes the process by which we collected refrigeration technology data. The data were generated for COMMEND 4.0 but are also generally applicable to other end-use forecasting frameworks for the commercial sector.

Data were obtained from various sources including the U.S. Department of Energy and publications of the Lawrence Berkeley National Laboratory, EPRI, ASHRAE, and Competitek. Several utility studies were also used.

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