William Loring Myers

A Wind Power Forecasting System to Optimize Grid Integration

Wind power forecasting can enhance the value of wind energy by improving the reliability of integrating this variable resource and improving the economic feasibility. The National Center for Atmospheric Research (NCAR) has collaborated with Xcel Energy to develop a multifaceted wind power prediction system. Both the day-ahead forecast that is used in trading and the short-term forecast are critical to economic decision making. This wind power forecasting system includes high resolution and ensemble modeling capabilities, data assimilation, now-casting, and statistical postprocessing technologies. The system utilizes publicly available model data and observations as well as wind forecasts produced from an NCAR-developed deterministic mesoscale wind forecast model with real-time four-dimensional data assimilation and a 30-member model ensemble system, which is calibrated using an Analogue Ensemble Kalman Filter and Quantile Regression. The model forecast data are combined using NCARs Dynamic Integrated Forecast System (DICast). This system has substantially improved Xcels overall ability to incorporate wind energy into their power mix.

Predicting weather and road conditions - Integrated decision-support tool for winter road-maintenance operations

Winter road-maintenance practitioners have expressed a strong interest in obtaining weather and road-condition forecasts and treatment recommendations specific to winter road-maintenance routes. These user needs led the FHWA Office of Transportation Operations Road Weather Management Program to support the development of a prototype winter road-maintenance decision-support system (MDSS). The MDSS is a unique data-fusion system designed to provide real-time treatment guidance (e.g., treatment times, types, rates, and locations) specifically regarding winter road-maintenance routes to winter maintenance decision makers. The system integrates weather and road data, weather and road-condition model output, chemical concentration algorithms, and anti-icing and deicing rules of practice. FHWA began the multiyear project in 2001 by engaging several national laboratories that had expertise in weather prediction and winter road engineering. A user-needs assessment for surface transportation weather information, performed by FHWA in 2000, formed the basis for the development effort. FHWA required that the system be developed in an open environment with significant input from the stakeholders (state transportation personnel and private-sector meteorological services). The resulting technologies have been released (in an initial version) on a nonexclusive basis to the surface transportation community. It is anticipated that the prototype MDSS will provide a springboard for the development and rapid deployment of operational systems by the private sector.

FHWA's Maintenance Decision Support System Project: Results and Recommendations

The Federal Highway Administrations Office of Transportation Operations Road Weather Management Program began a project in FY 1999 to develop a prototype winter road maintenance decision support system (MDSS). The MDSS capabilities are based on feedback received by the FHWA in 2001 from maintenance managers at a number of state departments of transportation (DOTs) as part of an initiative to capture surface transportation weather decision support requirements. The MDSS project goal is to seed the implementation of advanced decision support services provided by the private sector for state DOTs. This has been achieved by developing core software capabilities that serve as a basis for these tailored products. After the 2001 user needs assessment was completed, the MDSS program was extended with the objective of developing and demonstrating a functional prototype MDSS. Field demonstrations of the prototype MDSS were conducted in Iowa between February and April 2003, and during the winter of 2004. The performance of the prototype MDSS was much improved during the second winter. The weather and road condition predictions were more accurate, and the treatment recommendations generated by the system were reasonable given the predicted conditions. Iowa garage supervisors actively considered the treatment guidance, and on occasion they successfully used the recommended treatments without modification. This paper describes the status of the MDSS project, results and lessons learned from the field demonstrations, and future development efforts.