A high-resolution three-year dataset supporting rooftop photovoltaics (PV) generation analytics

Abstract This paper presents an open-source dataset intended to enhance the analysis and optimization of photovoltaic (PV) power generation in urban environments, serving as a valuable resource for various applications in solar energy research and development. The dataset comprises measured PV power...

Full description

Saved in:
Bibliographic Details
Main Authors: Zinan Lin, Qi Zhou, Zhe Wang, Ce Wang, Davis Boyd Bookhart, Marcus Leung-Shea
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-04397-y
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract This paper presents an open-source dataset intended to enhance the analysis and optimization of photovoltaic (PV) power generation in urban environments, serving as a valuable resource for various applications in solar energy research and development. The dataset comprises measured PV power generation data and corresponding on-site weather data gathered from 60 grid-connected rooftop PV stations in Hong Kong over a three-year period (2021-2023). The PV power generation data was collected at 5-minute intervals at the inverter-level. The meteorological data was collected at 1-minute intervals from an on-site weather station. The metadata was represented using the Brick schema, which simplifies data comprehension and the development of smart analytics applications. This paper provides a detailed description on the site specifications, data collection method, data records, and data validation. This dataset can be used in various applications - PV generation benchmarking, PV degradation analysis, PV fault detection, solar radiation and PV power generation forecasting, and the simulation and design of PV systems.
ISSN:2052-4463