English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Aiming at the problems of high cost, low real-time performance of manual identification of low-voltage station topological structure, automatic identification methods such as instantaneous power failure method and voltage correlation analysis method, which affect residents’ electricity consumption, and the success rate is limited by application scenarios, this paper proposes a method based on multiple linear regression Line impedance analysis method for automatic identification of the topology of low-voltage stations. Based on the relationship between voltage, current, and impedance, multiple linear regression analysis is used to derive the upstream topology step by step from the bottom up to the top of the topology and then determine the station membership by voltage correlation. The cloud platform based on Docker technology and Hadoop technology is used for data distributed storage calculation, and an identification model in the context of big data is established to effectively improve the efficiency of the algorithm. Finally, the correctness of the algorithm verification is judged based on the results of manual field verification.

Topology Automatic Identification Method for Low-Voltage Stations Based on Line Impedance Analysis