Analysis and modeling of dust accumulation-composed spherical and cubic particles on PV module relative transmittance

2021 ◽  
Vol 44 ◽  
pp. 101015
Author(s):  
Ze Wu ◽  
Suying Yan ◽  
Tingzhen Ming ◽  
Xiaoyan Zhao ◽  
Na Zhang
Keyword(s):  
Pv Module ◽  
Dust Accumulation

Modeling and quantifying dust accumulation impact on PV module performance

Solar Energy ◽  
2019 ◽  
Vol 194 ◽  
pp. 86-102 ◽  
Author(s):  
Mohammad Al-Addous ◽  
Zakariya Dalala ◽  
Firas Alawneh ◽  
Christina B. Class
Keyword(s):  
Pv Module ◽  
Module Performance ◽  
Dust Accumulation

scholarly journals Impacts of Cloud Cover and Dust on the Performance of Photovoltaic Module in Niamey

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Abdoulatif Bonkaney ◽  
Saïdou Madougou ◽  
Rabani Adamou
Keyword(s):  
Cloud Cover ◽  
Photovoltaic Module ◽  
Energy Yield ◽  
Solar Pv ◽  
Solar Module ◽  
Pv Module ◽  
Long Term Effect ◽  
Daily Energy ◽  
Dust Accumulation

The sensitivity of monocrystalline solar module towards dust accumulation and cloud cover is investigated from May to August 2015 for Niamey’s environment. Two solar modules with the same characteristics have been used to assess the impacts of the dust on the solar PV module. One of the modules is being cleaned every morning and the second one was used for monitoring the effect of dust accumulation onto the surface of the unclean module for May and June. Results show that dust accumulation has a great effect on decreasing the daily energy yield of the unclean module. But this effect is a long-term effect. For the cloud cover, the effect is immediate. It was estimated that exposing the module into the environment in 23 days in June 2015 has reduced the daily energy yield by 15.29%. This limitation makes solar PV an unreliable source of power for remote devices and thus strongly suggests the challenges of cleaning the module’s surface regularly.

Simulation-based Solar PV Module Maximum Output Power and Dust Accumulation Profiles

2021 ◽  
Author(s):  
Kelebaone Tsamaase ◽  
Japhet Sakala ◽  
Edward Rakgati ◽  
Ishmael Zibani ◽  
Edwin Matlotse
Keyword(s):  
Output Power ◽  
Maximum Output Power ◽  
Maximum Output ◽  
Solar Pv ◽  
Pv Module ◽  
Simulation Based ◽  
Dust Accumulation

Investigation on particle deposition criterion and dust accumulation impact on solar PV module performance

Energy ◽  
2021 ◽  
pp. 121240
Author(s):  
Weiping Zhao ◽  
Yukun Lv ◽  
Qingwen Zhou ◽  
Weiping Yan
Keyword(s):  
Particle Deposition ◽  
Solar Pv ◽  
Pv Module ◽  
Module Performance ◽  
Dust Accumulation

Effect of Dust Accumulation on the Power Production of the PV Module at Different Heights: A Case Study

2021 ◽  
pp. 47-57
Author(s):  
Rajan Kumar ◽  
Sachin Sharma ◽  
Akshu Gupta ◽  
Indar Singh ◽  
Paras Chaudhary ◽  
...  
Keyword(s):  
Power Production ◽  
Pv Module ◽  
Dust Accumulation

Artificial Neural Network Prediction Model of Dust Effect on Photovoltaic Performance for Residential applications: Malaysia Case Study

2021 ◽  
Vol 11 (2) ◽  
pp. 365-373
Author(s):  
Emy Zairah Ahmad ◽  
Hasila Jarimi ◽  
Tajul Rosli Razak
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Prediction Model ◽  
Predictive Model ◽  
Operating Conditions ◽  
Ann Model ◽  
Pv System ◽  
Pv Module ◽  
Artificial Neural ◽  
Dust Accumulation

Dust accumulation on the photovoltaic system adversely degrades its power conversion efficiency (PCE). Focusing on residential installations, dust accumulation on PV modules installed in tropical regions may be vulnerable due to lower inclination angles and rainfall that encourage dust settlement on PV surfaces. However, most related studies in the tropics are concerned with studies in the laboratory, where dust collection is not from the actual field, and an accurate performance prediction model is impossible to obtain. This paper investigates the dust-related degradation in the PV output performance based on the developed Artificial Neural Network (ANN) predictive model. For this purpose, two identical monocrystalline modules of 120 Wp were tested and assessed under real operating conditions in Melaka, Malaysia (2.1896° N, 102.2501° E), of which one module was dust-free (clean). At the same time, the other was left uncleaned (dusty) for one month. The experimental datasets were divided into three sets: the first set was used for training and testing purposes, while the second and third, namely Data 2 and Data 3, were used for validating the proposed ANN model. The accuracy study shows that the predicted data using the ANN model and the experimentally acquired data are in good agreement, with MAE and RMSE for the cleaned PV module are as low as 1.28 °C, and 1.96 °C respectively for Data 2 and 3.93 °C and 4.92 °C respectively for Data 3.  Meanwhile, the RMSE and MAE for the dusty PV module are 1.53°C and 2.82 °C respectively for Data 2 and 4.13 °C and 5.26 °C for Data 3. The ANN predictive model was then used for yield forecasting in a residential installation and found that the clean PV system provides a 7.29 % higher yield than a dusty system. The proposed ANN model is beneficial for PV system installers to assess and anticipate the impacts of dust on the PV installation in cities with similar climatic conditions.

Parametric Study of Photovoltaic Thermal Solar Collector Using An Improved Parallel Flow

2020 ◽  
Vol 2 (1) ◽  
pp. 19-24
Author(s):  
Sakhr Mohammed Sultan ◽  
Chih Ping Tso ◽  
Ervina Efzan Mohd Noor ◽  
Fadhel Mustafa Ibrahim ◽  
Saqaff Ahmed Alkaff
Keyword(s):  
Thermal Conductivity ◽  
Energy Balance ◽  
Parametric Study ◽  
Solar Collector ◽  
Parallel Flow ◽  
Operating Conditions ◽  
Balance Equations ◽  
Conductivity Type ◽  
Pv Module ◽  
Sunny Weather

Photovoltaic Thermal Solar Collector (PVT) is a hybrid technology used to produce electricity and heat simultaneously. Current enhancements in PVT are to increase the electrical and thermal efficiencies. Many PVT factors such as type of absorber, thermal conductivity, type of PV module and operating conditions are important parameters that can control the PVT performance. In this paper, an analytical model, using energy balance equations, is studied for PVT with an improved parallel flow absorber. The performance is calculated for a typical sunny weather in Malaysia. It was found that the maximum electrical and thermal efficiencies are 12.9 % and 62.6 %, respectively. The maximum outlet water temperature is 59 oC.

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