Wednesday, 26 January 2011: 10:30 AM
4C-2 (Washington State Convention Center)
Debra Lew, National Renewable Energy Laboratory, Golden, CO; and M. Milligan and G. Jordan
Manuscript
(310.0 kB)
In 2009, wind matched natural gas as the leading source of new electricity generation in the US. While wind only meets a small portion of the nationwide electricity demand, in specific utilities such as Xcel Energy, wind meets up to 8% of the local load. Wind power is variable (output fluctuates over time) and uncertain (output cannot be perfectly forecast) and these characteristics can make it difficult for utilities to integrate wind (or solar) into their power system. Utilities can compensate for the uncertainty by increasing back-up reserves or adding storage, but these options can be expensive. Another option is to reduce the uncertainty by forecasting the wind power production and utilizing this forecast in the utility unit commitment and dispatch process. This can yield significant savings: utilities and regional transmission organizations that have significant experience with wind power now use wind forecasts and are increasing the sophistication of their forecasts. While existing techniques, observational data, and weather models produce reasonably good wind forecasts especially for energy production, they still have ample room for improvement, especially in increased better modeling of the planetary boundary layer and in more accurate forecasting of wind ramps. This paper evaluates the value of wind forecasting improvements in the western U.S.
Many utilities have undertaken wind integration studies that examine the operating impact of increased penetrations of wind power on their grids. Additionally, two large regional studies were completed in 2010 that investigate up to 30% wind penetration in the eastern and western US. In many of these studies the uncertainty in the wind power has had a larger impact on operating impacts and costs than the variability of the wind. The annual value of using existing wind forecasting technology versus a perfect forecast in utility operations has been estimated to be $10-60M in New York, California and Texas, and up to $500M across the western US, depending on wind penetration. This paper will expand upon those existing studies, building upon the Western Wind and Solar Integration Study in particular, and examine the impact of improvements in wind power forecasting in greater detail. For example, this paper will investigate the impacts of incremental improvements in forecasting, which are more realistic than perfect forecasts. This paper will also examine the impact of forecasting improvements within the existing utility industry structure in the western U.S., in which many utilities are responsible for balancing their own generation and demand, as opposed to the consolidated balancing area structure that has been assumed in previous studies.
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