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酒店电动汽车充电桩功率配置优化数据

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浙江省数据知识产权登记平台2025-12-26 更新2025-12-27 收录
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本数据通过分析酒店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、早高峰总充电量、午高峰总充电量、晚高峰总充电量、低谷时段总充电量等数据。时段划分为:早高峰(7:00-9:00)、午高峰(12:00-14:00)、晚高峰(18:00-21:00)、低谷(0:00-6:00)、平峰(其余时段),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: 早高峰需求指数=早高峰总充电量/早高峰时长(2小时) 午高峰需求指数=午高峰总充电量×0.8(午高峰权重)/午高峰时长(2小时) 晚高峰需求指数=晚高峰总充电量×1.2(晚高峰权重)/晚高峰时长(3小时) 低谷时段需求指数=低谷时段总充电量×0.2(低谷时段权重)/低谷时段时长(6小时) 平峰时段需求指数=平峰总充电量×0.4(平峰时段权重)/平峰时段时长(11小时) 计算功率匹配度: 功率匹配度=(早高峰需求指数×1.4+午高峰需求指数×1.1+晚高峰需求指数×1.6+低谷需求指数+平峰需求指数)/(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>1.6:功率匹配度情况分类为""功率不足"",功率配置优化策略:早高峰时段:快充桩锁定100%功率,慢充桩+25%超频;午高峰时段:快充桩保持100%,慢充桩+15%超频;晚高峰时段:快充桩锁定100%功率,慢充桩+30%超频;低谷时段:慢充桩降功40%;平峰时段:维持标准功率 1.2≤匹配度≤1.6:功率匹配度情况分类为""配置基本合理"",功率配置优化策略:早高峰时段:快充桩保持95%功率;午高峰时段:快充桩保持90%功率;晚高峰时段:快充桩保持95%功率;低谷时段:慢充桩降功25%;平峰时段:维持标准功率 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:早高峰时段:快充桩保持85%功率;午高峰时段:快充桩保持80%功率;晚高峰时段:快充桩保持85%功率;低谷时段:全桩降功50%;平峰时段:全桩降功35%

This dataset analyzes the charging demand characteristics of hotel charging facilities across different time periods to provide decision support for the optimization of charging infrastructure. Its main applications are as follows: guiding operators to dynamically adjust the power configuration of charging piles based on the calculated results of power matching degree across different time periods; identifying high-load stations to prioritize expansion, and discovering areas with underutilized equipment for optimization; rationally allocating electric 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 allocation and efficient utilization of charging resources. 1. Data Collection and Processing This dataset collects management data from the enterprise's self-owned charging pile equipment, including charging station ID, city name, deployment area, charging pile configuration details, statistical date, total charging volume during morning peak, midday peak, evening peak, and off-peak period, etc. The time periods are divided as: morning peak (7:00-9:00), midday peak (12:00-14:00), evening peak (18:00-21:00), off-peak period (0:00-6:00), and flat peak period (remaining time). Data cleaning is conducted to eliminate abnormal and invalid records such as charging sessions shorter than 5 minutes. 2. Core Calculations Demand Index Calculation: Morning Peak Demand Index = Total Morning Peak Charging Volume / Morning Peak Duration (2 hours) Midday Peak Demand Index = (Total Midday Peak Charging Volume × 0.8 [Midday Peak Weight]) / Midday Peak Duration (2 hours) Evening Peak Demand Index = (Total Evening Peak Charging Volume × 1.2 [Evening Peak Weight]) / Evening Peak Duration (3 hours) Off-peak Period Demand Index = (Total Off-peak Charging Volume × 0.2 [Off-peak Weight]) / Off-peak Duration (6 hours) Flat Peak Period Demand Index = (Total Flat Peak Charging Volume × 0.4 [Flat Peak Weight]) / Flat Peak Duration (11 hours) Power Matching Degree Calculation: Power Matching Degree = (Morning Peak Demand Index ×1.4 + Midday Peak Demand Index ×1.1 + Evening Peak Demand Index ×1.6 + Off-peak Demand Index + Flat Peak Demand Index) / (Total Fast Charging Pile Power + Total Slow Charging Pile Power) 3. Power Matching Degree Classification and Charging Pile Power Configuration Optimization Strategies When Power Matching Degree > 1.6: The situation is classified as "Insufficient Power". The optimization strategies are: - Morning peak period: Fast charging piles locked at 100% rated power, slow charging piles overclocked by +25%; - Midday peak period: Fast charging piles maintained at 100% rated power, slow charging piles overclocked by +15%; - Evening peak period: Fast charging piles locked at 100% rated power, slow charging piles overclocked by +30%; - Off-peak period: Slow charging piles power reduced by 40%; - Flat peak period: Maintain standard rated power. When 1.2 ≤ Power Matching Degree ≤ 1.6: The situation is classified as "Basically Reasonable Configuration". The optimization strategies are: - Morning peak period: Fast charging piles maintained at 95% rated power; - Midday peak period: Fast charging piles maintained at 90% rated power; - Evening peak period: Fast charging piles maintained at 95% rated power; - Off-peak period: Slow charging piles power reduced by 25%; - Flat peak period: Maintain standard rated power. When Power Matching Degree < 1.2: The situation is classified as "Excessive Power". The optimization strategies are: - Morning peak period: Fast charging piles maintained at 85% rated power; - Midday peak period: Fast charging piles maintained at 80% rated power; - Evening peak period: Fast charging piles maintained at 85% rated power; - Off-peak period: All charging piles power reduced by 50%; - Flat peak period: All charging piles power reduced by 35%.

创建时间:
2025-09-30
搜集汇总
数据集介绍
酒店电动汽车充电桩功率配置优化数据 数据集图片
背景与挑战
背景概述
该数据集聚焦于酒店电动汽车充电桩的功率配置优化,通过分析不同时段(如早高峰、午高峰、晚高峰、低谷和平峰)的充电需求特征,计算功率匹配度以评估现有配置的合理性。它提供了基于匹配度分类的详细优化策略,帮助运营商动态调整功率、识别高负荷站点并合理分配电力资源,从而提升充电设施的整体运营效率和资源利用率。
以上内容由遇见数据集搜集并总结生成
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