Real-time rolling regulation model of integrated energy system based on model predictive control theory

The integrated energy system in the park faces challenges in producing and consuming renewable energy on a large scale as well as in achieving equilibrium between supply and demand for energy, making it a novel form in the study of integrated energy systems. The study takes the integrated energy system of the park as an example, and constructs a real-time rolling regulation model of two-layer optimal dispatch with multiple time scales. The model includes an upper-layer rolling economic optimization scheduling model and a lower-layer dynamic performance optimization control model, which takes economy and real-time as the objectives and realizes dynamic rolling optimization through model predictive control theory. The electric chillers are producing power to give cold energy during the whole dispatching cycle, while the absorption chillers produce power to supply cold energy only during the peak cold load period. The cold storage tank lowers the system’s operational costs by storing cold energy during low hours and releasing it during portions of the system’s high cold load hours. For the park's integrated energy system's primary energy exchange nodes 1 and 2, the micro gas turbine, and the gas boiler. The dynamic response process of the output power of the equipment takes a long time in model 2, with a value of about 10 min, while the time for the output value to reach the desired value is greatly reduced in model 1, with a value of about 4 min, and at the same time, it can foresee the change of the output power in advance, and make adjustments accordingly. The model constructed in the study has a more rapid calculation process and higher calculation accuracy in a short period of time, which has obvious advantages in online real-time prediction operation.