Stochastic Optimal Power Flow
Project Innovation + Advantages:
Arizona State University (ASU) will develop a stochastic optimal power flow (SOPF) framework, which would integrate uncertainty from renewable resources, load, distributed storage, and demand response technologies into bulk power system management in a holistic manner. The team will develop SOPF algorithms for the security-constrained economic dispatch (SCED) problem used to manage variability in the electric grid. The algorithms will be implemented in a software tool to provide system operators with real-time guidance to help coordinate between bulk generation and large numbers of DERs and demand response. ASU’s project features unique data-analytics based short-term forecast for bulk and distributed wind and solar generation utilized by the advisory tool that generates real-time recommendations for market operators based on the SOPF algorithm outputs.
If successful, projects included in the NODES Program will develop innovative hardware and software solutions to integrate and coordinate generation, transmission, and end-use energy systems at various points on the electric grid. These control systems will enable real-time coordination between distributed generation, such as rooftop and community solar assets and bulk power generation, while proactively shaping electric load. This will alleviate periods of costly peak demand, reduce wasted energy, and increase renewables penetration on the grid.