Environmental economic dispatch method of power system based on multiobjective artificial bee colony algorithm

A multiobjective environmental economic dispatching model of power system is established with minimum economic cost and pollution emission as the optimization objectives to meet the challenges of power system dispatching caused by the global energy crisis and climate warming and promote the realization of the double carbon goal. A multiobjective artificial bee colony algorithm (MOABC) based on nondominant sorting and improved greedy criterion is designed according to the characteristics of the model. In the design of the algorithm, the Taguchi method is used to optimize the parameters, the heuristic method is used to process the constraints dynamically, and a variety of comprehensive evaluation indexes are used to evaluate the algorithm's performance. In the simulation analysis, a six-machine power system and a ten-machine power system are simulated and compared with different algorithms to verify the proposed model's rationality and effectiveness. Finally, the technique for order preference by similarity to the ideal solution (TOPSIS) method is used to determine the optimal compromise solution to provide a reference for the scientific decision-making of dispatchers. The simulation results show that the MOABC algorithm achieved the lowest economic cost (161.159 × 10³ yuan for the 6-machine system and 2.771 × 10⁴ $ for the 10-machine system) and pollution emission (194.202 kg for the 6-machine system and 3.639 × 10³ kg for the 10-machine system) compared to the multiobjective wind driven optimization, multiobjective particle swarm optimization, and NSGA-II algorithms.