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University of Wisconsin–Madison

Reserve Energy Co-Optimization with Real-time Data from Satellites

Alternative renewable electric generation – wind and solar – is revolutionizing the power industry; the EPA’s new Clean Power Plan is one of many stimuli driving the transition. Yet as wind and solar production increase, the variations in wind speed and cloud cover lead to significant volatility in power supply. Disruptive power outages are avoided by setting aside generation capacity, so called reserves, to cover this volatility since electricity storage is currently too expensive or too limited to handle them. The “Reserve Energy Co-Optimization with Real-time Data from Satellites” project will combine satellite data with weather predictions to forecast wind and cloud cover, leading to more realistic forecasts of wind and solar power availability that can minimize the need for costly back-up generators.

The model will treat reserve capacity – the necessary but costly hedge that electric utilities must maintain to deal with contingencies such as line or power plant failure. The short-term goal is to develop a coupled cloud, wind, solar, temperature and power system modeling framework that can lead to major economic and environmental gains, while laying the groundwork for a larger, more sophisticated and fast-acting control system for the continental power grid, one that minimizes overall cost by optimal use of wind and solar power.

Principal Investigator

  • Michael C. Ferris
    Wisconsin Institutes for Discovery and Computer Sciences Department

Co-Principal Investigators

  • Christopher DeMarco
    Electrical and Computer Engineering
  • Tristan L’Ecuyer
    Atmospheric and Oceanic Sciences and Space Science and Engineering Center
  • Bernard Lesieutre
    Electrical and Computer Engineering