DefinePK

Abstract

These days, power system planners are looking for ways to reduce emission from power generating stations especially coal based thermal power plants without compromising the load factor. The economic dispatch problem allocates units for a given load without considering its emission. The present paper proposes a multi-objective optimization method, which uses Artificial Immune System based Clonal Selection Algorithm to solve problems related to emissions and economic dispatch along with unit commitment of generators in a thermal power system. A penalty factor has been imposed for violating the critical emission limits which is subject to the impact it causes on the environment. An 'Artificial Immune System' based Clonal Selection principle is used to select a suitable generator from a pool of generator units. Fitness has been evaluated for the proliferated units. EED problem involves power demand equality and inequality constraints under various operating conditions. Finally, the best units were selected and committed for a given load. The 'Clonal Selection' method has been compared with Non-Dominated Ranked Genetic Algorithm (NGDA) and Clonal Algorithms to prove its robustness and superior optimal selection. To understand the proposed method, a 'IEEE -30 bus 6 unit test system' (with and without load uncertainty) is considered for solving the EED problem using MATLAB simulation and results are compared.