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

The electric vehicle charging load forecasting is influenced by many factors and full of randomness and complexity based on the charging operation history data and according to the different types of charging power of different charging behavior, we propose Monte Carlo simulation calculation method which extracts the initial state of charge and the start time of charging. The behavior of different charging methods and different vehicles are classified according to the charging requirements, we selected the starting time and duration of charging as the key factors affecting the charging load time distribution, combined with the statistical analysis of users’ charging behavior, to establish the charging load time distribution model. On this basis, we divided the charging load areas to establish the time and space distribution model of charging load. Through the examples analysis, we predicted the temporal and spatial distribution of the load level of the electric vehicle in Chongqing. The analysis results show that with the development of electric vehicle in Chongqing, the charging load will have great influence on the operation and planning of power grid. The charging load has obvious peak to valley difference, and the potential of load regulation is great.

Time and Space Distribution Prediction of Electric Vehicle Charging Load Based on Statistical Analysis