Spatiotemporal optimization and coordination of integrated energy systems based on non-cooperative game equilibrium

The core of dynamic electricity price optimization of integrated energy systems lies in the flexible electricity price to guide the consumption of the active load. Based on the current mainstream time-of-use electricity price, this paper takes the agent platform economy maximization and the follower goal as the user’s electricity cost minimization as the goal. Through the new dynamic electricity price mechanism, it guides flexible load users to actively participate in the operation of the power grid and highlights the autonomy of each subject in IES. In order to achieve this goal, the Stackelberg game model is first established for the IES system. Then the complementary relaxation condition is used for linearization to transform the game model into a mixed integer linear programming model. Finally, the power time distribution results are brought into the mixed integer second-order cone optimization model of the power grid flow for spatial collaborative optimization. Finally, the impact of incentive policy on dynamic electricity prices is quantitatively discussed through examples. It can be concluded that by providing reasonable incentive compensation for electricity prices, the cost of users’ direct electricity purchase can be effectively reduced, which is a win-win dynamic electricity price adjustment method for users and platforms.