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at: weather forecasting

Forecasting fails and the effort costs money

Lesser, 12 - President of Continental Economics, Inc., an economic and litigation consulting firm. Dr. Lesser has almost 30 years of experience in the energy industry working for electric utilities, state government agencies, and as an independent economic consultant. He testified before utility commissions in many U.S. states, before the Federal Energy Regulatory Commission (FERC), before international regulators in Latin America and the Caribbean; in commercial litigation cases; and before state legislative committees on regulatory and policy matters affecting the electric and natural gas industries (Jonathan, “WIND INTERMITTENCY AND THE PRODUCTION TAX CREDIT: A HIGH COST SUBSIDY FOR LOW VALUE POWER” October, http://www.continentalecon.com/publications/cebp/Lesser_PTC_Report_Final_October-2012.pdf)

To ensure the lights stay on, power system planners’ ability to predict the amount of wind generation that will be available several days in advance is critical as the amount of wind generation determines how much fossil-fuel back-up generation must be available. Although even wind advocates acknowledge wind’s inherent intermittency they claim wind generation can be predicted accurately several days in advance, allowing system operators to reduce, if not eliminate, the impacts of wind’s volatility. 32 In other words, proponents argue that, because wind generation can be predicted accurately, wind does not impose higher reliability costs than conventional generating resources.

Notably, however, forecast and operational data in areas including ERCOT, as well as in European countries, 33 do not support such forecast accuracy claims. In addition, wind’s volatility can be significant. For example, on October 28, 2011, wind generation decreased in MISO by 2,700 MW in just two hours. In ERCOT, on December 30, 2011, wind generation decreased 2,079 MW in one hour and over 6,100 MW between 6AM and 4PM that day. 34

Moreover, even substantially reducing the capacity factor for wind generation, as done in ERCOT, MISO, and PJM, does not compensate for the significant forecast accuracy problem. Capacity de-rating addresses long-term planning issues: how much installed capacity must an electric system have one year from now to ensure there are sufficient reserves to meet future peak demand. In contrast, short-term planning issues are focused on the availability of generating resources over the next several days, specifically how much electricity these resources will provide to the power grid. Determinations that wind availability averages about 30% each year are meaningless in this context. As Forbes, et al. stated in their April 2012 study, “Capacity weighting is a distortion because the reported error understates the magnitude of the forecasting challenge.” 35

In ERCOT, for example, the Texas Reliability Entity measures the difference between the actual and scheduled levels of generation. This measure, called “Schedule Control Performance Standard 2” (SCPS2), measures how closely a generator that is scheduling power keeps to its predicted schedule. 36 To meet this standard, the SCPS2 score must be 90% or higher. In their 2012 study, however, Forbes, et al. determined, “During the month of March 2009, 35 out of 36 Non-Wind Only Qualified Scheduling Entities (QSEs) satisfied the reliability standard. None of the 30 Wind Only QSEs met the standard. This is not an isolated case.” 37

Furthermore, the demonstrated inaccuracy of short-term forecasts of wind generation increases the overall cost of meeting electric demand as system planners must reimburse other generators who had been scheduled to operate,

but were not needed because actual wind generation was greater than forecast, or had not been scheduled, but were required to operate because actual wind generation was less than forecast. Although generators can be penalized for erroneous forecasts, most of the resulting system costs are socialized across all users.

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