Adaptive clonal selection algorithm for solving OPF problem with emission constraints

This paper presents an artificial immune system (AIS) based adaptive clonal selection algorithm (ACSA) to solve combined economic emission dispatch (EED) problem of thermal units in power system. In this work different emission substances like NOX and SOX are considered along with power demand equality constraints and thermal unit operating limits. The clonal selection principle is one of the models used to incorporate the behaviour of the AIS. The biological principles like clone generation, proliferation and maturation are mimicked and incorporated into this algorithm. In order to find and manage the pareto optimal set a non dominated sorting technique and crowding distance measure have been used. The proposed multi-objective ACSA (MOACSA) method has been tested on two different test systems and the results are compared with other methods reported in literature.