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Technology Data Characterizing Lighting In Commercial Buildings: Application To End-Use Forecasting With COMMEND
Energy Analysis Program
End-use forecasting models typically utilize technology tradeoff curves to represent technology options available to consumers. A tradeoff curve, in general terms, is a functional form which relates efficiency to capital cost. Each end-use is modeled by a single tradeoff curve. This type of representation is satisfactory in the analysis of many policy options. On the other hand, for policies addressing individual technology options or groups of technology options, because individual technology options are accessible to the analyst, representation in such reduced form is not satisfactory.
To address this and other analysis needs, the Electric Power Research Institute (EPRI) has enhanced its Commercial End-Use Planning System (COMMEND) to allow modeling of specific lighting and space conditioning (HVAC) technology options. The EPRI contractor for this effort, Regional Economic Research, Inc. (RER), worked with Lawrence Berkeley Laboratory (LBL) in the development and testing of the technology modules contained in COMMEND 4.0. LBL is also providing assistance in the development and refinement of technology data for the model.
This report characterizes the present commercial floorstock in terms of lighting technologies and develops cost-efficiency data for these lighting technologies. The report also characterizes the present lighting utilization patterns and lighting level requirements. Much of the data presented in this report were developed for the Analysis of Federal Policy Options for Improving U.S. Lighting Energy Efficiency, a study performed by LBL for the U.S. Department of Energy. This report organizes the data from the above-mentioned study in a form usable by a forecasting analyst.
This report also characterizes the interactions between the lighting and space conditioning end uses in commercial buildings in the U.S. In general, lighting energy reductions increase the heating and decrease the cooling requirements. The net change in a building's energy requirements, however, depends on the building characteristics, operating conditions, and the climate. Lighting/HVAC interactions data were generated through computer simulations using the DOE-2 building energy analysis program. Ten building types of two vintages and ten climates were used to represent the U.S. commercial building stock for this purpose.
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