Distribution fault outage cost evaluation and hotspot area recognition based on big data

Abstract

Power distribution faulting is one of the main reasons for the unplanned outage. In terms of the distribution fault outage, cost evaluation and hotspot area recognition are beneficial for utilities to develop schemes tailored for distribution operation, maintenance and upgrading. In this study, multi-source data from marketing, distribution, and dispatching fields are effectively utilised for comprehensive information collection of medium-voltage distribution network faults. A new approach to fault fuzzy location is proposed using distribution network topology and transformer outage duration. Meanwhile, fault outage cost is evaluated based on the short-term load forecast of distribution transformers, which completely considers the impact of load transferring on multi-power supply users. Furthermore, the distribution blackout events are mapped with geography information system, and the fault hotspot areas are highlighted by geographical grid virtualisation. The method proposed in this study has been validated using practical examples. This approach has been actually applied in Jiangsu distribution maintenance management.