A Fast and Accurate Self-Healing Scheme for Intelligent Distribution Networks Using Mixed Integer Linear Programming

Abstract

Fast and accurate self-healing after faults is an important way to improve the reliability of distribution networks. To improve the self-healing speed and accuracy of distribution networks, this paper proposes a fast and accurate self-healing scheme for distribution networks using mixed integer linear programming. Firstly, this method constructs a centralized 5G communication network architecture, which can effectively reduce the communication delay during the self-healing process. Secondly, the principle of logical algebraic transformation is utilized to linearize the switch function in the fault location model, thereby achieving equivalent transformation of the fault location model. Thirdly, using the polyhedral approximation method, the mixed integer second-order cone programming of the power supply recovery model is transformed into a mixed integer linear programming. The proposed method was validated by distribution network systems with different nodes in MATLAB/Simulink, and the results showed that the proposed method significantly improved self-healing speed and accuracy.

Keywords

• Distribution network
• fault location
• fault recovery
• self-healing
• mixed integer linear programming
• 5G communication