The Sparrow search (SSA) algorithm is easy to fall into the local optimal solution in the optimization of microgrid scheduling, and the Sparrow algorithm (T-GSSA) based on the adaptive t distribution and the improved golden sine has a better performance in the optimization of scheduling. The golden sine function in mathematics is used to optimize the iteration and improve the global search ability. At the same time, the golden section coefficient is added in the process of position updating to search the local area and balance the local and global search ability. It is easier to jump out of the local optimal solution by using the adaptive T-distribution variation method to change the individual target position. With minimum operation and maintenance cost and maximum environmental benefit as optimization objectives, a multiobjective optimal scheduling model was established under the condition of power balance and output constraints of each generating unit, and SSA and t-GSSA algorithms were solved and compared. The results show that t-GSSA algorithm is superior to SSA algorithm in convergence speed and precision, which improves the overall operation efficiency of microgrid to a certain extent.
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