The planning and operation of electricity grids is carried out by solving various forms of con- strained optimization problems. With the increasing variability of system conditions due to the integration of renewable and other distributed energy resources, such optimization problems are growing in complexity and need to be repeated daily, often limited to a 5 minute solve-time. To address this, we propose a meta-optimizer that is used to initialize interior-point solvers. This can significantly reduce the number of iterations to converge to optimality.

# Meta-Optimization of Optimal Power Flow

Browse the Paper archive. Researcher: Alex Robson, Cozmin Ududec, Frames Catherine White, James Requeima, Letif Mones, Mahdi Jamei. Research Category: Electricity Grids, Machine Learning. Bookmark the permalink.