Bid forecasting for auxiliary services in virtual power plants

Developed a forecasting system to estimate available capacity for ancillary service participation across aggregated energy assets. The system combines historical usage patterns, real-time monitoring data, and mathematical modelling techniques to estimate future availability under varying operational conditions. By analyzing consumption behavior and device performance trends, the model provided capacity forecasts that supported downstream market participation workflows in flexible energy systems.