Intelligent Decision-Making Model for Power Grid Maintenance Plan Under High Proportion of Renewable Energy Access

With the continuous increase in the proportion of renewable energy in the power grid, the formulation of power grid maintenance plans faces unprecedented challenges. This paper proposes an intelligent decision-making model for power grid maintenance plans with a high proportion of renewable energy access, which comprehensively considers factors such as renewable energy consumption benefits, transmission channel capacity, and power balance during maintenance. The model establishes a consumption model for distributed energy such as wind power and photovoltaic power, and combines a multi-objective optimization function to minimize the loss of renewable energy consumption caused by maintenance. By considering the uncertainty of renewable energy power prediction, a multi-scenario safety verification method is proposed to ensure the safety of maintenance plans in different scenarios. This paper also designs an intelligent maintenance suggestion generation and risk warning mechanism to achieve dynamic adjustment and risk assessment of maintenance plans. The effectiveness and feasibility of the model are verified through case analysis based on the IEEE 39-node system. The results show that the optimized maintenance plan has significant advantages in reducing the loss of renewable energy consumption. This study provides new theoretical support and technical path for power grid maintenance plans with a high proportion of renewable energy access, which has important engineering application value.