Intelligent scheduling method and system for power demand side response event and medium
By using an intelligent scheduling method based on user vehicle usage monitoring records, charging demand is predicted and charging schemes are optimized, solving the problem of grid load imbalance caused by electric vehicle charging and achieving a synergistic improvement in grid load optimization and user comfort.
CN122243042APending Publication Date: 2026-06-19国网江苏省电力有限公司睢宁县供电分公司 +1
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 国网江苏省电力有限公司睢宁县供电分公司
- Filing Date
- 2026-03-12
- Publication Date
- 2026-06-19
AI Technical Summary
Technical Problem
The lack of a scientific and reasonable scheduling mechanism for electric vehicle charging behavior in existing technologies leads to uneven power grid load in residential areas, affecting power supply stability and power quality.
Method used
Based on user vehicle usage monitoring records, the system predicts vehicle usage time and distance, analyzes and generates a charging priority sequence, and optimizes the charging scheme by combining grid friendliness and user comfort goals, and implements intelligent charging control.
Benefits of technology
This achieves intelligent charging scheduling and grid load optimization in coordination, while ensuring users' vehicle usage needs, thus improving grid stability and user experience.
✦ Generated by Eureka AI based on patent content.
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Abstract
This invention discloses an intelligent scheduling method, system, and medium for power demand-side response events, relating to the field of power dispatching technology. The method includes: based on vehicle usage monitoring records of users in a residential area, reading the remaining battery power of several vehicles, and predicting several predicted usage times and predicted driving distances for several vehicles within a preset future time zone; determining several shortest charging times based on the predicted driving distances, and generating a vehicle priority sequence based on the remaining battery power; optimizing vehicle charging schemes to obtain suitable charging schemes; and intelligently controlling the charging of several vehicles according to the suitable charging scheme within the preset future time zone. This solves the technical problem of unbalanced power grid load in residential areas caused by unreasonable vehicle charging scheduling in existing technologies, achieving the technical effect of intelligent charging scheduling and coordinated power grid load optimization while ensuring users' vehicle usage needs.
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