Multiple Time-scale Optimal Scheduling of Community Integrated Energy System Based on Model Predictive Control

In combined cooling, heating and power systems, multiple energy devices must be coordinated to optimize operations and meet energy demands economically and reliably. A reasonable and effective scheduling strategy is the key to achieving this goal. The optimal scheduling of a real community integrated energy system in winter was studied. On the basis of building detailed models of the devices, a model predictive control based two-stage scheduling strategy of multiple time-scale was developed. In the rolling optimization stage, multiple devices ware coordinated to minimize the operation cost and unit startup/shutdown penalty under the time of use tariff mechanism and the schedule of large time-scale was formulated by multi-step's rolling optimization. In the dynamic adjustment stage, the operation conditions of the devices ware adjusted based on the schedule of the rolling stage to deal with the small time-scale uncertainties of renewable energy and the loads. The analysis results show that the scheduling method in the paper can decrease the operation cost and startup times of the units by coordinating the operation of energy supply and thermal storage devices and utilizing these benefits of complementary operation of them. The introduction of the dynamic adjustment stage can response to the small time-scale changes of renewable energy and the loads quickly and meet the energy demands reliably and economically. © 2019 Chin. Soc. for Elec. Eng.