Abstract
In recent years, many studies have studied economic dispatch problem in power systems. However, most of them have not considered the environmental pollution caused by fossil fuels. In this study, the use of an evolutionary search algorithm called multi-objective particle swarm optimization algorithm is proposed to solve the economic dispatch problem in power systems while considering environmental pollution. The proposed method is validated in terms of its accuracy and convergence speed based on comparisons with the results obtained using the classic nonlinear programming method. The proposed strategy is applied to a realistic power system under various conditions. Overall, six generating units are investigated along the corresponding constraints. The results obtained reveal that costs of operation and pollution with/without power loss are reduced significantly by the proposed approach. Obtained results show a good compromise can be established between two contradicting functions of exploitation cost and pollution by optimizing them simultaneously. Values of these function without considering their loss is 46,112.09 $/h and 682.32 kg/h, respectively. And if losses are considered, these values would be 48,381.09 $/h and 726.52 kg/h, respectively.
Highlights
Emissions from the fossil fuels consumed by power plants lead to increased operational costs, as well as requiring much attention to minimize pollution
The proposed approach was applied to the system under various load conditions and the results obtained were compared with those produced by the classic nonlinear programming (NLP) method
Simultaneous minimization of the operating cost and emission cost functions we present the results obtained by simultaneously minimizing the operating and emission cost functions in two modes: with and without system power loss
Summary
Emissions from the fossil fuels consumed by power plants lead to increased operational costs, as well as requiring much attention to minimize pollution. Various approaches have been proposed that consider emissions from power plants to address the ED problem. Finnegan and Fouad considered the emissions from power plants for the first time in 1974 [2], where they treated emissions as a constraint within a permissible range Later, this strategy was used to control pollution in related studies [3]. In [15], the PSO-SIL algorithm was used to obtain an economical power flow with the optimum costs These methods differ in terms of their speed and accuracy. We propose an analytical strategy for simultaneously minimizing costs and the emissions from power plants. This multi-objective problem is solved using a multi-objective PSO (MOPSO) algorithm.
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