To address the mismatch between supply and demand across parks caused by the spatiotemporal differences in energy sources and loads within the multi-park integrated energy system(MPIES)

a two-stage optimization dispatch strategy for MPIES is proposed based on a spatiotemporal correlation pricing mechanism.Firstly

a spatiotemporal correlated pricing mechanism

led by the upper-level energy service operator(ESO)

is proposed based on time-of-use energy prices and cross-regional transmission costs.This mechanism dynamically characterizes the linkage between electricity and gas prices

as well as the cross-park regulation capabilities of energy storage devices

to guide the MPIES in achieving optimal energy allocation across time and space. Secondly

a bi-level scheduling model based on leader-follower game equilibrium is constructed between the ESO and MPIES. The first stage focuses on maximizing the ESO's profit through upper-level scheduling among the ESO

power grid

and gas network

while the second stage minimizes the MPIES's operational costs through lower-level scheduling between the ESO and MPIES. Finally

a distributed equilibrium collaborative optimization algorithm

which combines the distributed iterative alternating direction method of multipliers(DI-ADMM)and the gradient projection method

is proposed to solve the bi-level scheduling model.Case studies demonstrate that this strategy effectively coordinates multi-energy complementarity in the MPIES

enhances economic benefits

and significantly reduces carbon emissions

holding important practical significance for advancing dual carbon goals.