An Hourly-Scale Adaptation of the KSTS Algorithm for Synthesizing Extreme Weather Scenarios

As the power grid decarbonizes, electricity is increasingly produced by solar and wind power plants with the support of energy storage facilities, which smooth out weather-driven production variability and intermittency. Decarbonization removes firm generation capacity such as coal power plants and methane-powered thermal plants. The decline in firm generation capacity will require system operators to mitigate extended renewable droughts to guarantee resource adequacy and system reliability. In practical operation, it is not uncommon to experience lack of wind energy or solar irradiance to sustain renewable resource energy production. Planning for renewable droughts generally relies on stochastic modeling of wind and solar production on an hour-by-hour basis to include hourly renewable variability and intermittency. This work extends a proof-of-concept stochastic weather and renewables production simulation algorithm. The resulting hourly synthetic solar and wind production profiles can be used in resource adequacy simulations to verify that proposed generation portfolios will meet system reliability standards during a variety of weather scenarios. The source code is published as an open-source project.