Abstract
The combined heating and power (CHP) plants are considered one of the promising methods to support the goal of “Carbon Peak and Carbon Neutrality”. It is an important means to take heat and power load optimal dispatch (LOD) to further reduce the energy consumption of CHP plants. To achieve a better load dispatch scheme, this paper employs a potent algorithm by integrating the grey wolf optimization (GWO) algorithm and the Levy flight (i.e., Levy−GWO algorithm) to overcome premature convergence. Moreover, the constraint condition processing method is also proposed to handle the system constraints for ensuring the results within feasible zones. To confirm the effectiveness of this algorithm, it is tested on two widely used test systems (Test system I and Test system II). The accuracy of the used algorithm is proved by comparing the obtained results and reported data in other literature. Results show that the Levy−GWO algorithm can be used to obtain relatively lower power generation costs, with the values of 9231.41 $/h (Test system I) and 10,111.79 $/h (Test system II). The proposed constraint processing method effectively solves the problem that load optimal dispatch scheduling is difficult to solve due to the existence of multiple constraints. In addition, the comparison results indicate that the Levy−GWO algorithm owns a better robustness and convergence effect and has a promising application for solving LOD problems.