Coordinated Control of Power Grid Dispatching and Renewable Energy Grid Connection Based on Artificial Intelligence

This paper researched power grid dispatching-coordinated control of renewable energy grid connection based on artificial intelligence and put forward a joint optimization model that combines the genetic algorithm with a particle swarm optimization algorithm. It optimizes the cost of power generation and improves the utilization rate of renewable energy while reducing power loss, thereby effectively solving the problems of voltage fluctuation and frequency offset with the access of renewable energy sources into the grid. Accordingly, a simulated experiment is designed based on the analysis using genuine power grid data. The results of the experiment show that an artificial intelligence optimization technique enables high-speed responses to dispatch needs arising from complex loads, with a significant improvement in the stability and economy of the power grid. While traditional methods of dispatching perform badly when renewable energy fluctuates highly, the artificial intelligence dispatching model performs very well. This will ensure not only that operation at the power grid is stable but also that renewable energy resources are utilized to their fullest potential. Herein are provided effective solutions and technical support for developing the smart grid. This paper, through detailed analysis and experimental verification of the optimization algorithm, further indicates that the application value of artificial intelligence technology is very huge and will be widely applied in the Dispatching of power grids.