Energy End-Use Forecasting
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Technology Data Characterizing Water Heating In Commercial Buildings: Application To End-Use Forecasting

Osman Sezgen and Jonathan G. Koomey

Lawrence Berkeley Laboratory
Berkeley, CA 94720
December 1995

Abstract

Commercial-sector conservation analyses have traditionally focused on lighting and space conditioning because of their relatively large shares of electricity and fuel consumption in commercial buildings. In this report we focus on water heating, which is one of the neglected end uses in the commercial sector. The share of the water-heating end use in commercial-sector electricity consumption is 3%, which corresponds to 0.3 quadrillion Btu (quads) of primary energy consumption. Water heating accounts for 15% of commercial-sector fuel use, which corresponds to 1.6 quads of primary energy consumption.

Although smaller in absolute size than the savings associated with lighting and space conditioning, the potential cost-effective energy savings from water heaters are large enough in percentage terms to warrant closer attention. In addition, water heating is much more important in particular building types than in the commercial sector as a whole. Fuel consumption for water heating is highest in lodging establishments, hospitals, and restaurants (0.27, 0.22, and 0.19 quads, respectively); water heating's share of fuel consumption for these building types is 35%, 18% and 32%, respectively.

At the Lawrence Berkeley National Laboratory, we have developed and refined a base-year data set characterizing water heating technologies in commercial buildings as well as a modeling framework. We present the data and modeling framework in this report. The present commercial floorstock is characterized in terms of water heating requirements and technology saturations. Cost-efficiency data for water heating technologies are also developed. These data are intended to support models used for forecasting energy use of water heating in the commercial sector.

The representation of the water-heating end use is complicated because the number of configurations of plant types and systems is quite large. Also, energy use is a complex function of the plant and the system properties. In this report, we present a method for segmenting the water heating equipment market. We then develop relevant data in terms of this segmentation to create a consistent forecasting framework.

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