Qatar Dust Atlas Project: Deployment of a National Field Soiling and Environmental Parameters Monitoring Network
Year: 2024
Type: conference-paper
Abstract: The impact of soiling on PV power production exhibits significant spatial and temporal variability on both large and small scales, even within the radius of a solar power plant [1]. Variations in soiling are prominent across different locations in a country like Qatar, influenced by specific environmental and meteorological conditions. To enhance the accuracy, cost-effectiveness, and reliability of soiling monitoring, a new class of sensors has emerged, leveraging the optical characteristics of dust particles on PV glass. These stand-alone sensors, exemplified by Atonometrics' Mars Soiling Sensor and Kipp & Zonen's Dust IQ, require minimal maintenance and have no moving parts. Since 2013, Qatar environment and energy research institute (QEERI) has become a regional leader in PV soiling research, with focus put on desert environments, exploring both experimental (characterization, innovative measurement methods, mapping) and modeling aspects (sandstorm prediction, dust deposition) [2]. The Qatar Dust Atlas project, carried out at QEERI's Energy Center, is dedicated to evaluating the spatio-temporal mapping of soiling across Qatar and forecasting it using Machine Learning and WRF-CHEM modeling. Key elements addressed in the Dust Atlas encompass a thorough understanding of soiling in Qatar through real world data, incorporating atmospheric aerosol (primarily PM10), field-soiling data, and Albedo [3]. This effort leads to the creation of a spatio-temporal map of dust particles, alongside the development of a land suitability index and a soiling-risk map for prospective PV installations. This paper provides an overview of recent developments and common outcomes from the Dust Atlas project, with a focus on the initiation and establishment of a "National Soiling and Environmental Parameters Monitoring Network". This network integrates monitoring stations and advanced sensors to directly assess soiling and other influential factors, playing a pivotal role in crafting AI-based solutions for forecasting soiling on PV solar panels at diverse spatial and temporal resolutions throughout Qatar.
Source: EU PVSEC
Authors: Aissa, Brahim, Abdelrahim, Mohamed, Subeh, Mosab, Abdallah, Amir A., Figgis, Benjamin W., Lopez-Garcia, Juan, Bermudez Benito, Veronica
Language: English
Field: Energy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6947896320
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