Xcel Energy is undertaking a pilot program with Sunairio, a software platform providing high-resolution climate simulation for energy investment and grid planning, in an effort to anticipate future energy variability and ensure grid reliability as the utility continues its transition to cleaner power sources.
Under the pilot, Xcel Energy Colorado will simulate the electric grid of Public Service Company of Colorado (PSCo) — an operating company subsidiary of Xcel Energy — as it adds significant new wind and solar generation capacity over the next 15 years. The program aims to improve the accuracy and increase the granularity of weather data used in grid planning.
The software is meant to be an improvement on traditional grid planning studies, which typically rely on historical weather data to help predict future weather events. However, Sunairio argues that historical data sets do span long enough to account for climate change or to capture potential extreme events. The pilot program aims to overcome these problems by providing high-resolution (down to 50-meter resolution) weather data that both extends further into the past (1950-present) and applies the latest intelligence from global climate models when looking to the future, Sunairio said.
Xcel Energy will start by validating Sunairio’s historical weather and renewable energy generation datasets against both known measurements and proprietary Xcel Energy generation data. Then, Sunairio will employ its climate simulation engine to simulate 1,000 probabilistic outcomes of future hourly weather. These simulations, each of which will extend to 2040, will incorporate climate trends consistent with the most current generation of physics-based global climate models (CMIP6).
Next, Sunairio will model future Xcel Energy’s customer demand, wind, and solar generation by applying energy models to the weather simulations — which is meant to enable Xcel Energy grid planners to quantify the probability and magnitude of energy events that can stress the grid.
Sunairio’s datasets can fit in four categories:
- Hourly high-resolution weather: High-resolution climate data (down to 50 meter spatial resolution) of the weather variables that drive wind generation, solar generation, and customer demand
- Hourly generation potential: Ideal weather-dependent renewable generation at the current and future utility-scale wind plants and solar plants in the Xcel Energy generation portfolio
- Hourly plant availability losses: Probabilistic simulations of wind and solar plant energy losses that result from system degradation, mechanical derates, and occasional full plant outages
Hourly customer load: Xcel Energy-Colorado customer demand simulations
