Research on Heating and Power Load Optimal Dispatch Based on the Particle Swarm Optimization Algorithm Combined with the Levy Flight

Abstract

Optimal dispatch of heat and power loads for combined heat and power (CHP) power plants is an effective solution to further improve energy efficiency and reduce energy consumption. To obtain a better load dispatch effect, this paper used the Particle Swarm Optimization (PSO) algorithm based on Levy flight (Levy-PSO algorithm) to solve the optimal dispatch problem. Meanwhile, the constraint condition processing method which is based on the characteristics of the internal thermoelectric load and external total load of electricity and heat network of thermoelectric units is also proposed to combine with the Levy-PSO algorithm for solving the problem. The optimal results are obtained via using the PSO and Levy-PSO algorithms for a typical CHP plant of seven units. The results show that the power generation cost obtained from the Levy-PSO algorithm is the lowest (10121.84$), which is close to the results of the literature and is better than the optimization results of the traditional PSO algorithm. Moreover, the results show that the constraint processing method adopted in this paper can well solve the characteristics of multiple constraints of load optimal dispatch problem. Meanwhile, the comparison results between the PSO algorithm and Levy-PSO algorithm indicate that the Levy-PSO algorithm has more obvious advantages in the performance of the algorithm. When combining with the proposed constraint processing scheme, the Levy-PSO algorithm shows better convergence and robustness, which is more suitable for solving similar practical engineering problems of heating and power optimal load distribution.