Optimization of Energy Storage and Charging Coordination in Distribution Networks Based on Improved Grey Wolf Algorithm

In the context of integrating renewable energy and orderly charging of electric vehicles, this paper proposes a distribution network scheduling model that includes energy storage systems and orderly charging, aiming to enhance renewable energy utilization and minimize grid operating costs. The traditional grey wolf algorithm is prone to local optima. In this work, a chaos mapping mechanism is introduced to initialize the population positions, and a nonlinear convergence factor is applied for smooth transitions. Additionally, adaptive parameter adjustments allow the algorithm to flexibly respond to different search stages. Finally, a mutation strategy based on fitness is incorporated. Compared to the traditional grey wolf algorithm, the improved grey wolf algorithm enhances global search capability and convergence speed, resulting in better solution accuracy.