Day-ahead unit commitment for hydro-thermal coordination with high participation of wind power

Abstract

The variability and uncertainty of renewable resources impose new challenges in the operational planning related to the unit commitment of generation units. The development of day‐ahead multi‐period optimal power flow, under integration of wind power, requires modelling of multiple scenarios in order to ensure an optimal power flow minimising the generation cost. A progressive hedging approach has been proposed and developed to solve efficiently the unit commitment problem as a two‐stage stochastic programming problem to update each stage in parallel. The performance of progressive hedging is compared with a standard mixed‐integer linear programming problem. The results indicate that the computation time is 50 times faster than standard mixed‐integer linear program ming. The test case system is based on a reduced version of the interconnected Colombian system. The comparative results indicate an important reduction in computational time