Combined heat and power economic dispatch problem using advanced modified particle swarm optimization

In this paper, a novel optimization algorithm based on Particle Swarm Optimization (PSO) is proposed for solving the non-convex non-linear economic dispatch (ED) problem in a system integrated with combined heat and power. In the proposed method, which is known as Advanced Modified PSO (AMPSO), one third of the population is updated based on conventional PSO, and the remaining members are updated randomly based on the boundaries of variables. In order to improve the efficiency of the algorithm, the required coefficients were estimated by the Taguchi method. The optimization problem is the nonlinear non-convex ED in which the effects of steam valves and the power loss have been included. The proposed algorithm is applied on different systems, and the results are compared with those of some well-regarded methods developed by other researchers. The results show the superiority of the proposed AMPSO in comparison to other methods.In this paper, a novel optimization algorithm based on Particle Swarm Optimization (PSO) is proposed for solving the non-convex non-linear economic dispatch (ED) problem in a system integrated with combined heat and power. In the proposed method, which is known as Advanced Modified PSO (AMPSO), one third of the population is updated based on conventional PSO, and the remaining members are updated randomly based on the boundaries of variables. In order to improve the efficiency of the algorithm, the required coefficients were estimated by the Taguchi method. The optimization problem is the nonlinear non-convex ED in which the effects of steam valves and the power loss have been included. The proposed algorithm is applied on different systems, and the results are compared with those of some well-regarded methods developed by other researchers. The results show the superiority of the proposed AMPSO in comparison to other methods.

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