合肥市充电站价格浮动综合分析数据

通过监测充电站价格数据和充电桩实时空闲状态，结合绿色能源供给数据，为车主、运营方、政府提供三层服务：
车主：按 “价格最优、速度最快、绿电优先” 智能推荐充电站，支持即充、预约、错峰充电，兼顾省钱与低碳；
运营方：实时分析价格浮动、桩位占用等数据，动态调整电价和设备运维策略，提升充电桩利用率；
政府：汇总区域充电价格、负荷分布、绿电消纳等数据，辅助政策制定和双碳目标追踪。1、数据采集：从数据库中提取充电站关于充电收费最高价与最低价及充电桩空闲情况：2、处理数据：根据收费价格的平均值得出均价，进一步提取充电站中最高价的峰值与最低价的谷值，该峰值与谷值分别作为该数据的年最高价与年最低价，进一步将(年最高价与充电站电价的差）/充电站电价*100%，从而得出+浮动值，进一步将(年最低价与充电站电价的差）/充电站电价*100%，从而得出-浮动值，进一步根据得出的+浮动值与-浮动值确定均价的浮动区间（-浮动值~+浮动值）。

By monitoring charging station price data, real-time idle status of charging piles, and combining with green energy supply data, this dataset provides three-tier services for vehicle owners, charging station operators, and governments:
Vehicle owners: Intelligently recommend charging stations based on the principles of "optimal price, fastest charging speed, and prioritizing green energy", supporting on-demand charging, reservation-based charging, and off-peak charging to balance cost savings and low-carbon objectives;
Charging station operators: Conduct real-time analysis on data such as price fluctuations and pile occupancy, dynamically adjust electricity pricing and equipment operation and maintenance strategies to improve the utilization rate of charging piles;
Governments: Collect and summarize data such as regional charging prices, load distribution, and green energy absorption to assist in policy formulation and tracking of dual-carbon goals;
1. Data Collection: Extract the maximum and minimum charging prices of charging stations and the idle status of charging piles from the database:
2. Data Processing: Calculate the average price based on the average value of charging prices. Further extract the peak value of the maximum price and the trough value of the minimum price of the charging station, which are respectively used as the annual maximum price and annual minimum price of this dataset. Then calculate the positive fluctuation value as [(annual maximum price - charging station electricity price) / charging station electricity price] * 100%, and calculate the negative fluctuation value as [(annual minimum price - charging station electricity price) / charging station electricity price] * 100%. Finally, determine the fluctuation range of the average price as (negative fluctuation value ~ positive fluctuation value) based on the obtained positive and negative fluctuation values.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于合肥市充电站的价格浮动分析，整合了充电价格、桩位空闲状态和绿色能源供给数据，为车主、运营方和政府提供智能推荐、运营优化和政策制定支持。通过计算均价、最高价与最低价峰值谷值，并推导浮动值和浮动区间，实现价格波动的量化评估，旨在提升充电效率、促进绿色能源消纳并辅助双碳目标追踪。