Power energy generation fuel cost optimization for thermal power plants using different type of fuels

This paper proposes an improved Particle Swarm optimization based on constriction factor, inertia weight factor and Cauchy distribution for power energy generation fuel cost optimization for thermal power plants using different type of fuels. The method is also compared to other versions of Particle Swarm Optimization (PSO) including original PSO and PSO based on the combination of constriction and inertia weight factors. A system with ten thermal unit systems using three fuel types is used as the main test case for investigating the performance of the proposed method. Two load levels with 2400 MW and 2500 MW are used to calculate the used power energy generation fuel cost of the three PSO methods. In addition, the proposed method is also compared to previous methods shown in the literature for conclusion of the real performance. As a result, the proposed PSO method outperforms two other PSO method and other previous methods about reaching smaller power energy generation cost and having a stronger search ability. Thus, it concludes that Cauchy distribution is very useful for PSO and it can be used for other optimization problems in power systems.