A Hybrid Genetic Algorithm Based Lagrangian Relaxation Approach for Profit Based Unit Commitment Problem

In this paper an application of a combined method for the profit based unit commitment problem (PBUC) using Genetic Algorithm and Lagrangian Relaxation (LR) is presented. The algorithm is proposed to solve PBUC under deregulated environment with the objective of maximizing GENCO’s profit and minimizing the operating cost. The problem formulation of the unit commitment takes into consideration the minimum up and down time constraints, start-up cost, and spinning reserve. UC schedule depends on the market price in the deregulated market. However demand satisfaction is not an obligation. GENCO can consider a schedule that produce less than the predicted load demand and reserve but creates maximum profit. The LR procedure solves the UC problem by dual optimization. The Genetic Algorithm (GA) develops the optimal schedule and Lagrangian Relaxation method produces Economic Dispatch. The proposed hybrid approach improves the performance of solving the Unit Commitment problem. The resultant schedule maximizes the profit and the proposed algorithm is tested for a 10 unit system taken as an individual GENCO and the simulations are carried out using MATLAB.