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  • Author or Editor: Rodney F. Weiher x
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Thomas J. Teisberg
,
Rodney F. Weiher
, and
Alireza Khotanzad

Every day, the U.S. electricity-generating industry decides how to meet the electricity demand anticipated over the next 24 h. Various generating units are available to meet the demand, and each unit may have its own production lead time, start-up cost, and production cost. Total costs can be minimized if electricity demand is accurately forecast. Accurate demand forecasts, in turn, depend on accurate temperature forecasts.

This paper estimates the cost savings (i.e., benefits) attributable to temperature forecasts used by the U.S. electricity-generation industry. It does this by establishing the relationship between the quality of temperature forecasts and the quality of electricity demand forecasts at six sites around the United States. It then draws on earlier work by Hobbs et al. on the relationship between the quality of demand forecasts and production costs to estimate the percentage of cost savings from different temperature forecasts. Finally, these cost savings are extrapolated to estimate the total benefits, and incremental benefits, for the United States as a whole.

The total benefits of U.S. National Weather Service (NWS) forecasts are estimated to be $166 million. The additional benefits potentially obtainable from a perfect temperature forecast are $75 million per year. It is estimated that an incremental 1% improvement in the forecast quality (from the current NWS forecast) would be worth an additional $1.4 million per year. These numbers do not include other possible benefits of forecasts to the electricity industry, such as those from the improved scheduling of plant maintenance.

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Kristie L. Ebi
,
Thomas J. Teisberg
,
Laurence S. Kalkstein
,
Lawrence Robinson
, and
Rodney F. Weiher

The Philadelphia, Pennsylvania, Hot Weather-Health Watch/Warning System was initiated in 1995 to alert the city's population to take precautionary actions when hot weather posed risks to health. The number of lives saved and the economic benefit of this system were estimated using data from 1995 to 1998. Excess mortality in people 65 yr of age and older was defined as reported mortality minus mortality predicted by a historical trend line developed over the period of 1964–88. Excess mortality during heat waves was explained using multiple linear regression. Two variables were convincingly associated with mortality: the time of season when a particular heat wave started, and a warning variable indicating whether or not a heat wave warning had been issued. The estimated coefficient of the warning variable was about −2.6, suggesting that when a warning was issued, 2.6 lives were saved, on average, for each warning day and for 3 days after the warning ended. Given the number of warnings issued over the 3-yr period, the system saved an estimated 117 lives. Estimated dollar costs for running the system were small compared with estimates of the value of a life.

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