Security constrained unit commitment strategy for wind/thermal units using Lagrangian relaxation based Particle Swarm Optimization

System security in the generation market is one of the important aspects in power system operation under deregulated environment. It becomes more crucial when thermal power system is integrated with wind system. This paper presents an approach to determine the security constrained unit commitment (SCUC) for thermal units integrated with wind power system. A Lagrangian relaxation based algorithm with Particle Swarm Optimization (PSO) has been applied to solve this model. The method initially decomposes the load demand hours into several groups based on their homogeneity. Then instead of solving hourly SCUC, this method solves SCUC for each group. Lagrangian formulations are applied to relax the constraints with objective function using multipliers. PSO is then applied to solve UC. Since security constraints including transmission flow and voltage limits are considered, an iterative sub problem is introduced to minimize the security constraint violation using a simplified heuristic method. The Lagraingian multipliers are updated using gradient method. The process will continue until the difference between the primal and dual problem comes to a tolerable limit. To compromise the uncertainty of wind power, it is injected with the provided supply using a Gaussian distribution stochastic function. The simulation provides some analysis of the proposed method with two test systems (IEEE 6-bus and and 31-bus).