典型配电网边缘侧光伏发电数据集

光伏发电出力受到光照强度、环境温度、光伏组件转化效率等多重因素影响，规模化光伏的接入将加剧配电网随机性和不确定性，对于配电网安全运行的影响不容忽视。因此对光伏发电功率进行准确预测，对于构建新一代电力系统，提高新能源消纳率具有重要的意义，同时对构建电力系统综合安全防御体系、实现风险控制具有重要价值。典型配电网边缘侧光伏发电数据集，来源于天津大学智能电网教育部重点实验室监测后台数据库，涵盖2018-2023年的分钟级光伏发电历史运行数据，并通过光伏发电历史数据预测出2023年4月的光伏的有功功率数据，真实性和可靠性经过同行审议评议通过。

Photovoltaic (PV) power output is affected by multiple factors such as light intensity, ambient temperature, and the conversion efficiency of PV modules. The integration of large-scale PV generation facilities will exacerbate the randomness and uncertainty of distribution networks, and its impact on the safe and stable operation of distribution networks cannot be ignored. Therefore, accurate forecasting of PV generation power is of great significance for building a new-generation power system, improving the new energy accommodation rate, and also has important value for constructing a comprehensive security defense system for power systems and realizing risk control. This typical edge-side PV generation dataset for distribution networks is sourced from the background monitoring database of the Key Laboratory of Smart Grid under the Ministry of Education, Tianjin University. It covers minute-level historical operating data of PV power generation from 2018 to 2023, and the active power data of PV in April 2023 was predicted using the historical PV power generation data. The authenticity and reliability of this dataset have been reviewed and approved through peer review.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于配电网边缘侧光伏发电，包含2018年至2023年的分钟级历史运行数据，并提供了2023年4月的光伏有功功率预测数据，旨在支持光伏发电功率预测研究，以应对新能源接入带来的电网不确定性挑战。数据来源于天津大学智能电网教育部重点实验室，经过同行审议，具有较高的真实性和可靠性，适用于电力系统自动化、新能源消纳等领域的分析。