Low-carbon Scheduling of Islanded Microgrid Using Enhanced Sparrow Search Algorithm
A low-carbon scheduling optimization method based on enhanced sparrow search algorithm(ESSA)is proposed for the economic and environmental collaborative optimization of islanded microgrids.Firstly,an islanded microgrid model with a carbon capture device is established to solve the issue of high carbon emission in existing models.Secondly,the integration of elite opposition-based learning and golden sine strategy into sparrow search algorithm(SSA)overcomes the disadvantages of low population diversity and poor local search capability in the original algorithm,six typical benchmark functions from CEC2017 evaluate the superior performance of ESSA.Finally,ESSA is applied to the low-carbon scheduling optimization problem of islanded microgrid and compared with six advanced bird swarm intelligence optimization algorithms.The results show that the islanded microgrid model with carbon capture device can effectively reduce the carbon emission,ESSA is more suitable for microgrid low-carbon scheduling optimization.
万方数据
维普
