Abstract:Demand-side load participation in scheduling based on the peak-to-valley tariff difference is an important means of source-load balance and renewable energy consumption, while the impact of source-load uncertainty on the management of power supply capacity in an integrated energy system should not be ignored. This paper proposes a two-stage robust optimal allocation strategy for multi-subject integrated energy systems that takes into account the source-load uncertainty and demand-side response. The first stage focuses on optimizing the capacity allocation of wind power, photovoltaic (PV) and energy storage, and the second stage focuses on planning the actual output of wind power, PV, energy storage and gas turbines. The model integrates the demand response operational constraints of diverse loads and types and coordinates the control of these constraints. In addition, the degree of fluctuation in source-load uncertainty is characterized by introducing an uncertainty adjustment parameter. In order to address the nonlinear and nonconvex characteristics of the original model, this paper uses integer variables to convert the model into a mixed-integer linear optimization problem and applies the double-layer column generation CC G loop algorithm to solve it. The simulation results show that the strategy proposed in this paper is able to flexibly calculate the microgrid power allocation scheme and output working conditions by changing the uncertainty regulation parameters, which provides theoretical support for the power capacity allocation strategy of multi-source microgrids and stimulates the flexible interaction between the demand side and the grid.