A Heuristic algorithm to solve the unit commitment problem for real-life large-scale power systems

One of the main needs that power system operators around the world have is to solve complex Unit Commitment models for large-scale power systems in an acceptable computation time. This Paper presents an alternative Heuristic algorithm that successfully addresses this need. The Heuristic algorithm makes use of various optimization techniques such as Mixed Integer Linear Programming (MILP), Quadratic Programming (QP), Quadratically Constrained Programming (QCP), and Dynamic Programming (DP). CPLEX 12.2 is used as the main optimization engine for MILP, QP, and QCP. DP is an in-house algorithm used to obtain the commitment of Combined Cycle Plants (CCPs) when represented with the component-based model. This Heuristic algorithm combines the global optimality capabilities of MI (L) P formulations with the highly detailed models available for CCPs using LR–DP formulations. The Heuristic algorithm introduced in this Paper is capable of solving up to 1-week scenarios with a 1-hour time window for the complex Mexican Power System.

► Hybrid model combines MILP, QP, QCP, and DP to solve the UC problem for large-scale power systems. ► Hybrid model includes quadratic fuel constraints and represents CCP with the aggregated model. ► Finds good quality solutions within a few minutes compared to the hours taken by other approaches. ► Comparison of the Hybrid model with two direct approaches based on MIQCP.