Comprehensive Dataset on Electrical Load Profiles for Energy Community in Ireland

计算机科学 能量(信号处理) 能源消耗 储能 环境科学 功率(物理) 统计 电气工程 工程类 物理 数学 量子力学
作者
Rohit Trivedi,Mohamed A. Bahloul,Aziz Saif,Sandipan Patra,Shafi Khadem
出处
期刊:Scientific Data [Nature Portfolio]
卷期号:11 (1): 621-621 被引量:17
标识
DOI:10.1038/s41597-024-03454-2
摘要

Abstract This paper describes a comprehensive energy-related dataset, collected from residential electricity households within an energy community in Ireland, as part of StoreNet project. The data includes local weather parameters and per household power (W) and energy (Wh) components for various aspects such as active power consumption, PV generation, grid import and export, charging and discharging, and the state of charge of energy storage. Additionally, it provides weather data for the location at a 1-minute temporal resolution for the year 2020. The dataset has been validated by comparing measurements that should yield identical results to standard load profiles, with no significant inconsistencies discovered. Validation examples have also been given through the published articles where this dataset has been used to analyse peer-to-peer energy trading benefits for the energy community and decision-making support for aggregators. The dataset aids in understanding patterns in electrical load curves and the duty cycle of energy storage within an energy community. Furthermore, it can assist in comprehending the impact on distribution networks caused by distributed energy storage.
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