Research on Optimal Scheduling of Microgrid Based on Improved Gray Wolf Algorithm

In this paper, an operation decision model based on the improved Gray Wolf optimization algorithm is proposed for the optimization problem of energy storage allocation in independent and joint parks of microgrids. The model takes into account the storage and discharge constraints of the microgrid as well as the power balance relationship, and takes cost minimization as the optimization objective to derive the most reasonable microgrid scheduling scheme. The model is solved based on the Gray Wolf optimization algorithm, which takes into account the change of the time factor and introduces the dynamic adaptability mechanism, so that the algorithm can adapt to the complex power changes, and effectively improves the convergence speed and solving accuracy. In this paper, the robustness and applicability of the model under different operating conditions are verified by sensitizing the two key parameters of battery power and energy storage capacity. The results show that the improved model can not only effectively reduce the total cost of power supply, but also provide stable optimal operation strategies under different scenarios to ensure the efficient operation of the microgrid system.