A New Optimal Algorithm for Multi-objective Short-Term Fixed Head Hydrothermal Scheduling with Emission Control Consideration

Abstract

With the purpose of environment protection, polluted emissions should be considered as an additional criteria, besides the fuel cost objective, to implement the optimal operation of hydrothermal power systems which are included thermal and hydro power plants. This paper proposes a novel cuckoo search algorithm (NCSA), developed from cuckoo-inspired optimization algorithm, to solve the multi-objective short-term fixed-head hydrothermal scheduling (HTS) problem which considers both fuel cost objective and emission cost objectives. In the proposed approach, there are two modifications, merging the exploration and exploitation phases and setting one rank parameter to handle the inequality constraints, to improve the convergence rate and the performance of NCSA. To verify its performance, some test systems with the quadratic fuel cost function of thermal units accompanied with emission objective functions have been implemented. The results have revealed that the NCSA method is a very promising method for solving the multi-objective short-term fixed-head HTS problem.