NDLI: A Wind Power Forecasting System to Optimize Power Integration

Content Provider	The American Society of Mechanical Engineers (ASME) Digital Collection
Author	Haupt, Sue Ellen Wiener, Gerry Liu, Yubao Myers, Bill Sun, Juanzhen Johnson, David Mahoney, William
Copyright Year	2011
Abstract	The National Center for Atmospheric Research (NCAR) has developed a wind prediction system for Xcel Energy, the power company with the largest wind capacity in the United States. The wind power forecasting system includes advanced modeling capabilities, data assimilation, nowcasting, and statistical post-processing technologies. The system ingests both external model data and observations. NCAR produces a deterministic mesoscale wind forecast of hub height winds on a very fine resolution grid using the Weather Research and Forecasting (WRF) model, run using the Real Time Four Dimensional Data Assimilation (RTFDDA) system. In addition, a 30 member ensemble system is run to both improve forecast accuracy and provide an indication of forecast uncertainty. The deterministic and ensemble model output plus data from various global and regional models are ingested by NCAR’s Dynamic, Integrated, Forecast System (DICast®), a statistical learning algorithm. DICast® produces forecasts of wind speed for each wind turbine. These wind forecasts are then fed into a power conversion algorithm that has been empirically derived for each Xcel power connection node. In addition, a ramp forecasting technology fine-tunes the capability to accurately predict the time, magnitude, and duration of a ramping event. This basic system has consistently improved Xcel’s ability to optimize the economics of incorporating wind energy into their power system.
Sponsorship	Advanced Energy Systems Division and Solar Energy Division
Starting Page	2215
Ending Page	2222
Page Count	8
File Format	PDF
ISBN	9780791854686
DOI	10.1115/ES2011-54773
Volume Number	ASME 2011 5th International Conference on Energy Sustainability, Parts A, B, and C
Conference Proceedings	ASME 2011 5th International Conference on Energy Sustainability
Language	English
Publisher Date	2011-08-07
Publisher Place	Washington, DC, USA
Access Restriction	Subscribed
Subject Keyword	Economics Wind Uncertainty Algorithms Wind energy Wind power forecasting Power systems (machinery) Energy conversion Wind velocity Resolution (optics) Wind turbines Modeling
Content Type	Text
Resource Type	Article

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