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Estimating the Benefits of the GridWise Initiative
註釋GridWiseTM is a vision, a concept, and a national initiative developed by the U.S. Department of Energy, the Pacific Northwest National Laboratory, and participants from the electricity industry, which seeks to link electricity suppliers and end-users via high-speed networks that provide real-time information about system capacities, demand, prices, and status. This report presents the initial results of a two-phase project designed to characterize and estimate the benefits of applying such advanced communications and information technologies to bring the aging U.S. electricity grid into the information age. The project is intended to provide a better understanding of those benefits-for electricity suppliers, end-users, and society at large-that will inform both public and private sector decisions about GridWise-related research and development (R & D) and implementation strategies. In the first phase of the study, reported here, an analytic framework is developed for characterizing and estimating benefits, and preliminary quantitative estimates are made of gross benefits for the most important benefit categories. The estimates do not include R & D and implementation costs, which will be estimated in the second phase of the study. Assumptions and other input variables for the benefit calculations are clearly delineated, both to indicate the sensitivity of the estimates to such inputs and to provide a basis for improving them. A comparison of estimates for five scenarios indicates that the present value of gross benefits from GridWise can be quite large, exceeding $100 billion in some scenarios. However, the variance among estimates is also very large, depending, of course, on the input data and assumptions. At this early stage of GridWise development, many of the input variables and projections are highly uncertain. Consequently, the report concludes that delineating a range of benefits based on plausible input variables is more useful at this time than trying to converge on a single "best estimate."