Neuro-hybrid genetic algorithm based economic dispatch for utility system

A neuro hybrid Genetic Algorithm (GA) is used to solve an economic dispatch problem. The algorithm has been proposed for minimum cost of operating units. Here Real Coded 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 participated among all generating units using participation factor method. Applying the results again to the load flow checks the voltage limit violation. Artificial Neural Network (ANN) is applied to the Hybrid GA . The algorithm is tested on IEEE 6-bus system and 66-bus utility system. It is observed that the proposed algorithm is optimal, reliable and fast.