Potential for Crowdsourced Weather Stations to Assess Intra-Hourly Variability of Photovoltaic Systems
Year: 2019
Type: conference-paper
Abstract: Solar power has seen significant growth in energy markets in recent years, driven largely by a substantial drop in cost. An issue with high penetrations of solar is that it, more than most other sources of energy, is liable to extreme intermittency as clouds pass over and irradiance varies. It is often difficult to assess the problem of solar intermittency as meteorological and PV generation data often lack the temporal and spatial resolution required. This investigation utilises crowd sourced meteorological data from personal weather stations, with known coordinates and five-minute resolution. The correlation between publicly available average half hour irradiance data, from weather stations and publicly available half hourly PV generation data, is analysed. A high degree of correlation is found between irradiance data from personal weather stations interpolated to the PV plants’ location and PV output over a wide range of conditions. This result allows estimation of intermittency in PV output in five-minute, rather than half hour, increments. Estimates of variation in PV output over full sun (clear sky days), intermittent sun and no sun (overcast) days are presented. This investigation is intended to study potentially undesirable effects of phase angle variation due to PV intermittency and how these problems could be alleviated with battery energy storage.
Authors: Lopez Lorente, J., Liu, X., Morrow, D.J., Brogan, P.V.
Institution: Queen's University Belfast
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2986120836