Robust Economic Management Strategy for Power Systems Considering the Participation of Virtual Power Plants

The rapid development of new energy technologies and the randomness and intermittency of renewable energy sources, coupled with the complexity of demand-side response, have posed higher requirements for the security and scheduling of power grids. The virtual power plant (VPP), as an innovative energy management model, effectively enhances the flexibility and economy of the power system by integrating distributed energy resources and demand-side response resources to participate in the power market and grid operation as a virtual entity. This paper proposes a robust economic management strategy for power systems considering the participation of VPPs. Firstly, the uncertainty of renewable energy output is characterized through prediction deviations. Subsequently, the economic dispatch and constraints of VPPs are established. Considering the nonlinear characteristics of the model, an improved ant lion optimizer (ALO) algorithm is adopted to ensure optimal solutions. Finally, the effectiveness and feasibility of the proposed method are validated through a case study, using an improved IEEE 30-bus test system. Compared to other methods, the economic income can be increased by up to 3.2%, and the calculation time is only 12.5% of that required for scenario screening-based stochastic optimization. After introducing the carbon trading mechanism, carbon emissions are reduced by 27.7%. The proposed method achieves the goal of maximizing economic benefits while ensuring the secure and stable operation of the power grid.