Optimal scheduling of islanded microgrids based on improved dung beetle optimization algorithm

As renewable energy advances rapidly, the optimal scheduling problem of islanded microgrids has become a research hotspot due to its high dimensionality, nonlinear and multi-constraint characteristics. This study introduces an Improved Dung Beetle Optimization Algorithm (IDBO). This greatly enhances the global search capabilities of the original method by utilizing a golden sine technique. Additionally, the algorithm achieves an optimal balance between exploration and exploitation phases by incorporating adaptive weighting factors during the position updates of the thieving beetle population. To reduce microgrid expenses—fuel, maintenance, and environmental, a 24-hour dispatch model is developed and solved by combining the constraints such as power balance and rate of climb. The experimental results show that the integrated operating cost of IDBO is $4.1 \%$ lower than that of the basic DBO, which verifies its advantages in convergence accuracy and stability. The optimized dispatch scheme prioritizes the use of wind and photovoltaic power generation, reasonably allocates micro gas turbine and fuel cell outputs, and improves the system economy through battery charging and discharging strategies, which provides a new idea for the efficient dispatch of microgrids.