“车-站-网”协同调控站网互动聚合响应技术研究和测试数据集

本数据集面向“车–站–网”协同运行研究构建，综合采用文献筛选、真实站级监测、行为仿真与结构化特征工程等方法，形成覆盖车辆补能行为、换电站负荷、电网交互与商业机制要素的多维数据体系。数据来源包括：基于文献调研生成的电网、换电站和换电重卡运营仿真数据；某个换电站在 2023 年 3 月 2 日至 10 月 7 日期间采集的小时级天气数据；某个换电站单月充电数据和电价数据；以及基于蒙特卡洛方法生成的 重卡全日补能行为仿真数据。本数据集所依托的监测平台通过等保三级与 ISO20000、ISO27001 认证，所有数据均经过脱敏处理；仿真数据依据国内外车辆出行特性文献校准，并与实际负荷曲线对齐验证。该数据集内容完整、结构统一、来源可靠，可支撑换电负荷预测、车辆–站–网耦合建模、站网互动调度优化、商业模式推演与系统动力学研究，适用于数据科学、交通工程、能源系统、电力经济等多学科领域。数据量27MB。

This dataset is developed for research on the coordinated operation of Vehicle-Station-Grid systems. Comprehensive methodologies including literature screening, real-world station-level monitoring, behavioral simulation and structured feature engineering are employed to establish a multi-dimensional data system covering vehicle energy replenishment behavior, battery swap station load, grid interaction and business mechanism factors. The data sources include: 1) Operational simulation data of power grids, battery swap stations and battery-swapping heavy-duty trucks generated via literature research; 2) Hourly weather data collected by a battery swap station from March 2 to October 7, 2023; 3) Monthly charging data and electricity price data of a battery swap station; 4) Full-day energy replenishment behavior simulation data of heavy-duty trucks generated using the Monte Carlo method. The monitoring platform supporting this dataset has passed the certifications of Class 3 Cybersecurity Protection Level, ISO20000 and ISO27001, and all data has undergone desensitization processing. The simulation data is calibrated against domestic and international literature on vehicle travel characteristics and validated by aligning with actual load curves. This dataset boasts complete content, unified structure and reliable sources, which can support various research topics such as battery swap load forecasting, Vehicle-Station-Grid coupling modeling, station-grid interactive scheduling optimization, business model deduction and system dynamics research. It is applicable to multidisciplinary fields including data science, transportation engineering, energy systems and power economics. The total data volume is 27 MB.

搜集汇总

背景与挑战

背景概述

该数据集面向“车-站-网”协同运行研究，通过文献筛选、真实监测与仿真方法，构建了涵盖车辆补能行为、换电站负荷及电网交互等多维数据体系。数据来源包括仿真数据、真实天气与充电数据，经过脱敏和验证，可用于负荷预测、耦合建模及调度优化等多学科领域研究。