This paper presents the results of a survey and analysis ofelectricity tariffs and marginal electricity prices for commercialbuildings. The tariff data come from a survey of 90 utilities and 250tariffs for non-residential customers collected in 2004 as part of theTariff Analysis Project at LBNL. The goals of this analysis are toprovide useful summary data on the marginal electricity prices commercialcustomers actually see, and insight into the factors that are mostimportant in determining prices under different circumstances. We providea new, empirically-based definition of several marginal prices: theeffective marginal price and energy-only anddemand-only prices, andderive a simple formula that expresses the dependence of the effectivemarginal price on the marginal load factor. The latter is a variable thatcan be used to characterize the load impacts of a particular end-use orefficiency measure. We calculate all these prices for eleven regionswithin the continental U.S.

This report documents a project undertaken for theCalifornia Urban Water Conservation Council (the Council) to create a newmethod of accounting for the diverse environmental benefits of raw watersavings. The environmental benefits (EB) model was designed to providewater utilities with a practical tool that they can use to assign amonetary value to the benefits that may accrue from implementing any ofthe Council-recommended Best Management Practices. The model treats onlyenvironmental services associated directly with water, and is intended tocover miscellaneous impacts that are not currently accounted for in anyother cost-benefit analysis.

Much of the work done in energy research involves ananalysis of the costs and benefits of energy-saving technologies andother measures from the perspective of the consumer. The economic valuein particular depends on the price of energy (electricity, gas or otherfuel), which varies significantly both for different types of consumers,and for different regions of the country. Ideally, to provide accurateinformation about the economic value of energy savings, prices should becomputed directly from real tariffs as defined by utility companies. Alarge number of utility tariffs are now available freely over the web,but the complexity and diversity of tariff structures presents aconsiderable barrier to using them in practice. The goal of the TariffAnalysis Project (TAP) is to collect andarchive a statistically completesample of real utility tariffs, and build a set of database and web toolsthat make this information relatively easy to use in cost-benefitanalysis. This report presentsa detailed picture of the current TAPdatabase structure and web interface. While TAP has been designed tohandle tariffs for any kind of utility service, the focus here is onelectric utilities withinthe United States. Electricity tariffs can bevery complicated, so the database structures that have been built toaccommodate them are quite flexible and can be easily generalized toother commodities.

The Home Energy Saver (HES, http://HomeEnergySaver.lbl.gov) is an interactive web site designed to help residential consumers make decisions about energy use in their homes. This report describes the underlying methods and data for estimating energy consumption. Using engineering models, the site estimates energy consumption for six major categories (end uses); heating, cooling, water heating, major appliances, lighting, and miscellaneous equipment. The approach taken by the Home Energy Saver is to provide users with initial results based on a minimum of user input, allowing progressively greater control in specifying the characteristics of the house and energy consuming appliances. Outputs include energy consumption (by fuel and end use), energy-related emissions (carbon dioxide), energy bills (total and by fuel and end use), and energy saving recommendations. Real-world electricity tariffs are used for many locations, making the bill estimates even more accurate. Where information about the house is not available from the user, default values are used based on end-use surveys and engineering studies. An extensive body of qualitative decision-support information augments the analytical results.