A Novel Strategy-Based Hybrid Binary Artificial Bee Colony Algorithm for Unit Commitment Problem

In this paper, a hybrid approach based on a novel binary artificial bee colony (NBABC) algorithm and local search (LS) is developed to solve the unit commitment problem (UCP). Also, the ramp rate constraints are taken into account in the solution of UCP by performing conventional economic dispatch with modifying unit generating capacities over the entire scheduling time horizon. The proposed NBABC–LS method differs from its counterparts in three main aspects: (i) it utilizes a novel strategy which measures the dissimilarity between two binary strings for generating the new binary strings for UCP; (ii) it uses an intelligent scout bee phase; (iii) A LS module is hybridized with the NBABC algorithm. These modifications result in three major advantages: (i) it avoids the problem of slow and premature convergence and thus does not fall into the local optimum solutions; (ii) it can quickly find the near global optimum solution for UCP; (iii) accuracy and robustness of the solution are achieved. The proposed approach is successfully applied to the test systems up to 100 thermal units over 24-h scheduling time horizon and the real Turkish interconnected power system consisting of eight thermal units over 8-h scheduling time horizon. The obtained results confirm the quality solution in terms of total generation cost compared with the other methods reported in the literature.