Optimization of Economic‒emission Dispatch by Particle Swarm Optimization (PSO) Using Cubic Criterion Functions and Various Price Penalty Factors
Optimization of Economic‒emission Dispatch by Particle Swarm Optimization (PSO) Using Cubic Criterion Functions and Various Price Penalty Factors

Summary/Abstract: Various pollutants, such as sulfur dioxide (SO2), nitrogen oxides (NOX), and carbon dioxide (CO2), affect the environment. The economy‒environment dispatch problem has generally been solved by considering each objective separately or by applying the weighted sum method to both objectives. This paper formulated a solution to the dispatch PSO method that considers the impact of various pollutants and various factors, such as the price penalty min‒max, max‒max, and average in solving multi-objective problems using the cubic criterion function for the cost of fuel and emission values. The multi-objective functions method proposed in this research was validated using IEEE 30-bus systems with 6 generating units. The results of the simulation using the min‒max penalty factor indicated a lower total fuel cost value than the simulation using the max‒max and average penalty factors. In general, the comparison results were min‒max type = 100%, max‒max type = 266.9%, and average type= 191.8%; the max‒max penalty factor provided a lower emission value than the min‒max and average penalty factors. In general, the comparison results were max‒max type = 100%, min‒max type = 102%, and average type = 100.2% for ETSO, while for ETNO and ETCO they were not significantly different; the average penalty factor provided a lower fuel cost value than the max‒max and average penalty factors. The comparison resulted in average type = 100%, min‒max type = 101.8%, and max‒max type = 100.3%.

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