Aiming at the economic stability of substation integrated energy system

a multi-time scale optimization scheduling strategy based on model predictive control（MPC）is proposed

which combines ground source heat pump and demand response. Firstly

the system architecture is constructed and the MPC algorithm flow is described. In day-ahead scheduling

by considering the randomness of TOU and new energy

an optimization model aiming at minimizing operation cost is established

and the optimal output and energy storage plan of the unit are determined. Intra-day scheduling uses MPC algorithm to correct the day-ahead schedule in real time to reduce the impact of uncertainty on the power grid and improve the economy. The demand response characteristics and energy efficiency level of ground source heat pump are discussed by comparing different schemes through example analysis. The results show that the proposed model can optimize the system operation under the demand response environment

improve the equipment utilization rate

reduce the operating cost

and promote the consumption of renewable energy.