Optimization method for response time of distribution network fault self-healing logic in oil and gas production scenarios

Abstract

During the self-healing process of distribution network faults, the slow response time for different switching action sequences affects the compliance rate. Therefore, this paper studies an optimization method for the self-healing response time of distribution network faults in oil and gas production scenarios. A predictive triggering mechanism based on a fault mode library is designed to wake up the self-healing module in advance using the timing characteristics of oil and gas loads. A regional distributed collaborative judgment architecture is introduced, decentralizing the traditional centralized master station communication decision-making to node-local collaboration. An improved heuristic search algorithm that integrates critical load priorities is adopted to dynamically plan the optimal recovery path and switching action sequence. Experimental results show that the overall response time score improved from 0.2 to 0.92, and the average response time under the four fault types was controlled within 30 ms. The compliance rate of the four typical oil and gas scenarios all exceeded 90%, with the highest reaching 98% (maximum 29.5 ms) for oil production platforms with distributed power sources, and the lowest being 90% (maximum 36.8 ms) for the medium-pressure system of the joint station, verifying the universality and effectiveness of the method in oil and gas production scenarios.