Performance Optimization of Intelligent Algorithms in Integrated Energy System Dispatch

Agricultural parks are a specific application scenario with high reliability and efficiency, and their energy system optimization and dispatch needs are increasingly prominent. This article takes typical agricultural parks as the research object, with the goal of achieving sustainable development of agricultural parks. This article takes the optimal dispatch of integrated energy systems as the starting point to conduct in-depth research on the benefits and performance of intelligent algorithms. On this basis, its research focuses on the optimization dispatch effects of intelligent algorithms such as genetic algorithm, particle swarm optimization, and deep learning under different energy system structures and business requirements. By combining simulation experiments and application examples, this article verifies the effectiveness of the algorithm in improving system efficiency, optimizing energy consumption, and reducing operating costs. In addition, this article can also optimize and improve existing debugging techniques, and provide corresponding improvement plans. From 08:00 to 10:00, the energy utilization efficiency is 75%, the cost is 1500 yuan, and the environmental impact index is 0.8. The research results of this article show that through reasonable algorithm selection and parameter optimization, the energy efficiency of the system can be greatly improved, energy consumption can be reduced, and economic benefits can be maximized.