Unit Commitment using Nearest Neighbor as a Short-Term Proxy

Montefiore Institute - Department of Electrical Engineering and Computer Science University of Li ege, L.Wehenkel@ulg.ac.be Abstract--We devise the Unit Commitment Nearest Neighbor (UCNN) algorithm to be used as a proxy for quickly approximating outcomes of short-term decisions, to make tractable hierarchical long-term assessment and planning for large power systems. Experimental results on an updated versions of IEEE-RTS79 and IEEE-RTS96 show high accuracy measured on operational cost, achieved in run-times that are lower in several orders of magnitude than the traditional approach. Unit commitment (UC) is solved daily by Transmission System Operators (TSO) worldwide as part of the market clearing process, to ensure safe operation. Typically, the resulting mathematical problem is either a deterministic or stochastic Mixed Integer-Linear Program (MILP). It is solved accurately for the following day, taking into account all available information on generation and demand, along with exogenous factors such as renewable generation forecast. As intermittent generation capacity is increasing regularly in recent years, more stochasticity is involved in power system operation, affecting the way planning is done not only in the day-ahead time horizon, but in all different time horizons [1], [2], [3]. The complex dependence between the different time-horizons and the high uncertainty in long time-horizons makes long-term planning challenging.