Inverse time overcurrent optimization of distribution network with DG based on improved gray wolf algorithm

• DOI: 10.1016/j.egyr.2022.09.095
• Publication Date: 2022-10-10T13:21:13Z
• Authors: Yang Yu; Ruien Bian; Tongwen Wang; Wei Wang; Jun Zhang
• Keywords: Overcurrent; Initialization

Inverse time overcurrent protection can be applied to distribution networks with distributed power sources because of its superior characteristics, but limit coordination and value setting are complicated, which limits large-scale engineering application. Therefore, this paper proposes an inverse strategy for network(DN) based on improved gray wolf optimizer (GWO) algorithm. Firstly, the current optimization model operation characteristics established considering reliability, rapidity selectivity. Secondly, GWO algorithm is by introducing population initialization elite backward learning, adaptive weights variation Cauchy operator traditional easy trap in local optimum low convergence accuracy. The does not introduce new parameters achieves a balance between global local. Finally, case study results represent that has high accuracy stability both two-phase short-circuit three-phase scenarios, good practical applicability.