Optimization Scheduling Method for Integrated Energy System Considering Weight Sensitivity and Flexible Load

The multiobjective optimization problem in the integrated energy system (IES) is crucial for achieving optimal scheduling of the system. This paper proposes a weight optimization method for IES scheduling based on the weight sensitivity (WS) index. First, an IES coupling network model is established, considering the network structure of the power grid, natural gas network, and heating network. The time-of-use price is determined based on generation resources to guide the demand for flexible load (FXL). Next, the weights of the multiobjective function are optimized using the coefficient of variation of the WS index. The analytic hierarchy process (AHP) is utilized to achieve multiobjective function weight optimization, considering environmental friendliness and installed capacity. The optimal scheduling model is solved using CPLEX, and the results of different weight optimization methods are compared. The change in the carbon emission (CE) index under the increasing permeability trend is analyzed, and the guiding effect of intraday prices based on power generation resources on FXL is studied. The simulation results demonstrate that: (1) Single-objective weight optimization based on the WS index reduces the objective function value by 0.47%, and the objective function value based on AHP, considering multiobjective weight optimization, decreases by 10.31%, indicating that the WS index is suitable for comprehensive weight optimization. (2) As the IES permeability increases by 46.31%, the IES CE decreases by 94.69%, and the demand for energy storage increases by 7.32%. (3) Under the guidance of time-of-use prices based on power generation resources, 51.47% of FXL autonomously shifts power consumption time, reducing electricity purchase fees by 24.61%. This paper provides valuable insights for utilizing the WS index to optimize IES scheduling.