农贸市场电动汽车充电桩功率配置优化数据
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本数据通过分析农贸市场不同时段的充电需求特征，为充电基础设施优化提供决策支持。主要应用于：指导运营商根据不同时段的功率匹配度计算结果，动态调整充电桩功率配置；识别高负荷站点优先扩容，发现闲置设备可优化区域；合理分配电力资源，提升整体运营效率。同时可为管理部门提供充电设施使用时段分析报告，助力实现充电资源的精准配置与高效利用。 1.数据采集与处理 采集企业自有充电桩设备管理数据，包括充电站编号、城市名称、部署区域、充电桩配置情况、统计日期、早市时段总充电量、日间时段总充电量、晚市时段总充电量等数据。时段划分为：早市时段（5:00-9:00）、日间时段（9:00-16:00）、晚市时段（16:00-19:00），通过数据清洗剔除＜5分钟充电记录等其他异常值与无效记录。 2.核心计算 计算需求指数： 早市时段需求指数=早市时段总充电量/早市时段时长（4小时） 日间时段需求指数=日间时段总充电量×0.6（日间权重）/日间时段时长（7小时） 晚市时段需求指数=晚市时段总充电量×0.8（晚市权重）/晚市时段时长（3小时） 计算功率匹配度： 功率匹配度=（早市时段需求指数×1.5+日间时段需求指数+晚市时段需求指数×0.7）/（快充桩总功率+慢充桩总功率） 3.功率匹配度情况分类及充电桩功率配置优化策略 功率匹配度＞1.8：功率匹配度情况分类为""功率不足""，功率配置优化策略：早市时段：快充桩锁定100%功率，慢充桩+30%超频；日间时段：快充桩动态降功（负载＜50%时降至80%）；晚市时段：快充恢复100%，慢充关闭50% 1.2≤匹配度≤1.8：功率匹配度情况分类为""配置基本合理""，功率配置优化策略：早市时段：快充桩保持90%功率；日间时段：维持标准功率；晚市时段：慢充降功20% 匹配度＜1.2：功率匹配度情况分类为""功率过剩""，功率配置优化策略：早市时段：快充桩保持80%功率；日间时段：快充允许降50%；晚市时段：全桩降功30%
This dataset analyzes the charging demand characteristics across different time periods at farmers' markets to provide decision support for charging infrastructure optimization. Its main applications are as follows: guiding operators to dynamically adjust charging pile power configurations based on the calculated power matching degree results for different time periods; identifying high-load stations for priority capacity expansion, and discovering areas where idle equipment can be optimized; rationally allocating power resources to improve overall operational efficiency. Additionally, it can provide charging facility usage time period analysis reports for management departments, helping to achieve precise configuration and efficient utilization of charging resources. 1. Data Collection and Processing Collect management data from the enterprise's own charging pile equipment, including charging station ID, city name, deployment area, charging pile configuration status, statistical date, total charging volume during morning market hours, total charging volume during daytime hours, total charging volume during evening market hours, and other relevant data. The time periods are divided as: morning market period (5:00-9:00), daytime period (9:00-16:00), evening market period (16:00-19:00). Data cleaning is performed to remove outliers and invalid records such as charging records shorter than 5 minutes. 2. Core Calculations Calculate the demand index: Morning market period demand index = Total charging volume during morning market period / Duration of morning market period (4 hours) Daytime period demand index = (Total charging volume during daytime period × 0.6 (daytime weight)) / Duration of daytime period (7 hours) Evening market period demand index = (Total charging volume during evening market period × 0.8 (evening market weight)) / Duration of evening market period (3 hours) Calculate the power matching degree: Power matching degree = (Morning market period demand index × 1.5 + Daytime period demand index + Evening market period demand index × 0.7) / (Total power of fast charging piles + Total power of slow charging piles) 3. Power Matching Degree Classification and Charging Pile Power Configuration Optimization Strategies - When power matching degree > 1.8: Classified as "Insufficient Power". Optimization strategies: Morning market period: Fast charging piles locked at 100% power, slow charging piles overclocked by 30%; Daytime period: Fast charging piles dynamically reduce power (drop to 80% when load < 50%); Evening market period: Fast charging piles restored to 100% power, 50% of slow charging piles turned off. - When 1.2 ≤ matching degree ≤ 1.8: Classified as "Basically Reasonable Configuration". Optimization strategies: Morning market period: Fast charging piles maintain 90% power; Daytime period: Maintain standard power; Evening market period: Slow charging piles reduce power by 20%. - When matching degree < 1.2: Classified as "Excessive Power". Optimization strategies: Morning market period: Fast charging piles maintain 80% power; Daytime period: Fast charging piles allowed to reduce power by 50%; Evening market period: All charging piles reduce power by 30%.
