Chaotic particle swarm algorithm-based optimal scheduling of integrated energy systems.

• Based on the particle swarm algorithm, chaos is introduced to combine the speed advantage of the particle swarm algorithm with the ergodic advantage of the chaos idea, so that the chaotic particle swarm algorithm can find the optimal configuration of the coupled energy system quickly and accurately. • The impact of the introduction of energy storage devices on the investment cost of microgrid systems is explored. • The introduction of hydrogen energy and energy storage equipment completes the integrated energy systems. • It provides a new algorithm to solve the problem of real-time load distribution of microgrids. Integrated energy system (IES) is difficult to achieve the optimal scheduling of the system due to the coupling of multiple energy devices and the high volatility of renewable energy loads. To address the above problems, a chaos-based particle swarm algorithm is proposed, which uses a chaotic mapping of optimal particles by a Logistic algorithm to increase the anisotropy of particles and improve the search accuracy in the case of wide area multi-polarity. The example analysis shows that the chaotic particle swarm algorithm can improve the economic cost by 3.868% compared with the conventional particle swarm after increasing the number of iterations. Finally, based on this algorithm, the economic impact of the energy storage device on the integrated energy system is analyzed. The results show that the IES system based on the composite energy storage can reduce the total economic cost significantly, while avoiding the excessive use of other energy supply devices and ensuring the stability of the overall IES system operation. [ABSTRACT FROM AUTHOR]