Lambda based minimum emission dispatch using hybrid genetic algorithm for utility system

The objective of the paper is to evolve simple and effective methods for minimum emission dispatch (MED) problem of thermal units. In lambda based hybrid genetic algorithm (HGA), encoding parameter is normalized system incremental cost (λ_nm). A lambda based HGA is used to solve an emission dispatch problem. The algorithm has been proposed for minimum emission of operating units. Here real coded genetic algorithm (GA) is used for global search and fine tunings are done by tabu search (TS) to direct the search towards the optimal region and local optimization. The fast decoupled load flow (FDLF) is conducted to find the losses by substituting the generation values to the respective PV buses. Then the loss is distributed among all generating units using participation factor method. Applying the results again to the load flow checks the voltage limit violation. The algorithm is tested on 66-bus utility system. Numerical results show that the proposed method is more effective than other previously developed classical method and unit based GA methods. It is observed that the proposed algorithm is superior, reliable and fast.