Effect of dust and weather conditions on photovoltaic performance in Doha, Qatar

Guo, Bing; Javed, Wasim; Figgis, Benjamin; Mirza, Talha

doi:10.1109/sgre.2015.7208718

Cited by 111 publications

(53 citation statements)

References 12 publications

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“…Second, Ref. [5] showed poor correlation between adjacent measurements of the daily PM 10 and the daily soiling rate, and Ref. [52] showed that on-site PM 10 measurements were only able to predict 9% of the variation of the mass loading rate on PV glass.…”

Section: Discussionmentioning

confidence: 99%

“…Reported annual losses for the United States have ranged from 0 to 6% [1][2][3][4], while annual losses are not readily available for some of the dustiest regions of the world, like the Middle East, India, or China. In these locations, peak losses have been reported ranging between 20 and 70% [5][6][7][8][9][10], but these values do not directly translate to annual losses, which are typically much lower. Annual PV soiling losses are generally the result of considering the soiling rate (typically the increase in loss per day) for a site in combination with rainfall patterns or other cleaning events.…”

Section: Introductionmentioning

confidence: 99%

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An investigation of the key parameters for predicting PV soiling losses

Micheli

Muller

2017

Progress in Photovoltaics

124

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One hundred and two environmental and meteorological parameters have been investigated and compared with the performance of 20 soiling stations installed in the USA, in order to determine their ability to predict the soiling losses occurring on PV systems. The results of this investigation showed that the annual average of the daily mean particulate matter values recorded by monitoring stations deployed near the PV systems are the best soiling predictors, with coefficients of determination (R 2 ) as high as 0.82. The precipitation pattern was also found to be relevant: among the different meteorological parameters, the average length of dry periods had the best correlation with the soiling ratio. A preliminary investigation of two-variable regressions was attempted and resulted in an adjusted R 2 of 0.90 when a combination of PM 2.5 and a binary classification for the average length of the dry period was introduced.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An investigation of the key parameters for predicting PV soiling losses

Micheli

Muller

2017

Progress in Photovoltaics

124

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“…This is a significant factor as the region frequently experiences sand storms and the performance of the solar systems degrade significantly. For instance according to a study conducted at Qatar Foundation (QF) [25], the power loss is around 10 − 15% per month on average. Similarly, research activities in QF include developing anti-dust technologies such as hydrophobic coatings, robotic cleaners, and electrical shields.…”

Section: Barriersmentioning

confidence: 99%

Smart Grids and Load Profiles in the GCC Region

Bayram

2017

EAI Endorsed Transactions on Smart Cities

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The members of the Gulf Cooperation Council (GCC), namely Qatar, Bahrain, Saudi Arabia, Kuwait, Oman, and United Arab Emirates (UAE), are facing challenges to meet the growing electricity demand and reduce the associated hydrocarbon emissions. Recently, there has been a pressing need for a shift towards smart power grids, as smart grids can reduce the stress on the grid, defer the investments for upgrades, improve the power system efficiency, and reduce emissions. Accordingly, the goal of this paper is to delineate an overview of current smart grid efforts in the GCC region. First, we present a detailed overview of the current state of the power grids. Then, we classify the efforts into three broad categories: (i) energy trading and exchange through GCC interconnection; (ii) integration of renewable resources; and (iii) demand side management technologies for shaping the demand profile. Furthermore, we provide the details of our API object level real-time GCC power demand automated program that creates the database for the load profiles of the GCC members. Accessing such information for research and development purposes is a critical step in the region, because due the conservative structure of the governing institutes, there is no publicly available dataset. Therefore, the data provided in this paper is critical and will serve as a main reference for the future research efforts.

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“…The Air Conditioning (AC) systems in this region are highly mandatory for daily life through the year. The local weather has some significance of representing a unique desert and coastline climate, which attract a lot of research interests in various fields such as building efficiency, health, urban environment, and renewable energy [1][2][3][4][5][6][7][8][9][10][11]. As elaborated in [12], in GCC region such as Saudi Arab, more than 60% of the electricity consumed by local buildings goes to Air conditioning (AC).…”

Section: Introductionmentioning

confidence: 99%

An Optimal Air-Conditioner On-Off Control Scheme under Extremely Hot Weather Conditions

et al. 2020

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Being reliant on Air Conditioning (AC) throughout the majority of the year, desert countries with extremely hot weather conditions such as Qatar are facing challenges in lowering weariness cost due to AC On-Off switching while maintaining an adequate level of comfort under a wide-range of ambient temperature variations. To address these challenges, this paper investigates an optimal On-Off control strategy to improve the AC utilization process. To overcome complexities of online optimization, a Elman Neural Networks (NN)-based estimator is proposed to estimate real values of the outdoor temperature, and make off-line optimization available. By looking up the optimum values solved from an off-line optimization scheme, the proposed control solutions can adaptively regulate the indoor temperature regardless of outdoor temperature variations. In addition, a cost function of multiple objectives, which consider both Coefficient of Performance (COP), and AC compressor weariness due to On-Off switching, is designed for the optimization target of minimum cost. Unlike conventional On-Off control methodologies, the proposed On-Off control technique can respond adaptively to match large-range (up to 20 ∘ C) ambient temperature variations while overcoming the drawbacks of long-time online optimization due to heavy computational load. Finally, the Elman NN based outdoor temperature estimator is validated with an acceptable accuracy and various validations for AC control optimization under Qatar’s real outdoor temperature conditions, which include three hot seasons, are conducted and analyzed. The results demonstrate the effectiveness and robustness of the proposed optimal On-Off control solution.

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Effect of dust and weather conditions on photovoltaic performance in Doha, Qatar

Cited by 111 publications

References 12 publications

An investigation of the key parameters for predicting PV soiling losses

An investigation of the key parameters for predicting PV soiling losses

Smart Grids and Load Profiles in the GCC Region

An Optimal Air-Conditioner On-Off Control Scheme under Extremely Hot Weather Conditions

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