- Email: [email protected]
Characterization of soiling on PV modules in the Atacama Desert
Available online at www.sciencedirect.com Available online at www.sciencedirect.com
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Energy Procedia 00 (2017) 000–000 Available online www.sciencedirect.com Available online atatwww.sciencedirect.com Energy Procedia 00 (2017) 000–000
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Energy (2017) 000–000 547–553 EnergyProcedia Procedia124 00 (2017) www.elsevier.com/locate/procedia
7th International Conference on Silicon Photovoltaics, SiliconPV 2017 7th International Conference on Silicon Photovoltaics, SiliconPV 2017
Characterization of soiling on PV modules in the Atacama Desert Characterization of soiling on PV modules in the Atacama Desert
Thea*15th Internationala Symposium on District Heating anda Cooling b c Douglas Olivares a*, Pablo Ferradaa, Camila de Matosb, Aitor Marzoa, Enrique Cabrerac, a d Douglas Olivares , Pablo Ferrada Camila ,de Matos , Aitor Marzo , Enrique Cabrera , Carlos,Portillo a Jaime Llanosd Assessing the feasibility of using heat demand-outdoor Carlos Portillo , Jaimethe Llanos a
Centro de Desarrollo Energético Antofagasta (CDEA), Universidad de Antofagasta, Angamos #601 Antofagasta, Chile
Centro de Desarrollo Energético Universidad3721, de Antofagasta, Angamos Antofagasta, Chile LaborelecAntofagasta Chile Lab), Apoquindo O.32, Santiago, Chile#601 temperature function for(ENGIE a (CDEA), long-term district heat demand forecast a
b
c c
b Laborelec ChileCenter (ENGIE Lab), Apoquindo 3721, O.32, Santiago, Chile15 D78467, Germany International Solar energy Research Konstanz (ISC Konstanz), Rudolph-Diesel-Str. d International Solar energy Research Center Konstanz (ISCdel Konstanz), 15 D78467, Departamento de Química, Universidad Norte, Angamos #610, Antofagasta, a,b,c a aCatólica bRudolph-Diesel-Str. c ChileGermany d Departamento de Química, Universidad Católica del Norte, Angamos #610, Antofagasta, Chile
I. Andrić a
*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Correc
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b
Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Abstract The soling can negatively affect the performance of photovoltaic systems. We studied the species, which deposit on photovoltaic The caninnegatively affect (Atacama the performance photovoltaic systems. We studied thebase species, which deposit of ondust photovoltaic (PV)soling modules northern Chile Desert).ofThe environmental conditions are the for the interaction particles (PV) modules in northern Chile (Atacama Desert). The environmental conditions are the base for the interaction of dust particles and the module’s surfaces. We considered 4 locations for the study. We determined that the particle size of the dust to deposit on Abstract and modules the module’s surfaces. locations forsites. the study. We determined that the particle size of the deposit on PV is smaller thanWe 63considered μm for all4the selected However, the morphology varies from place to dust placetoinfluencing PV modules is smaller thanare 63 commonly μm all addressed the selected However, fromsolutions place to place influencing optical response ofnetworks the modules. Afterfor4 months dust accumulation the transmittance PVvaries glass reduced by 55%. District heating in sites. the literature asthe onemorphology of theofmost effective for decreasing the optical response of the modules. After 4 months dust accumulation the transmittance of PV glass reduced by 55%. greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat ©sales. 2017 The Authors. Published by Elsevier Ltd. to the changed climate conditions © 2017 Due The Authors. Published by Elsevier Ltd. and building renovation policies, heat demand in the future could decrease, © 2017 The Authors. Published byperiod. Elsevier Ltd. of SiliconPV 2017 under responsibility of PSE AG. Peer review scientific conference committee prolonging thethe investment Peer review by by the scientificreturn conference committee of SiliconPV 2017 under responsibility of PSE AG. Peer review by the scientific conference committee of SiliconPV under responsibility PSE AG. function for heat demand The main scope of this paper is to assess the feasibility of using 2017 the heat demand – outdooroftemperature
Keywords: PV modules; soil composition; losses(Portugal), was used as a case study. The district is consisted of 665 forecast. Soiling; The district of Alvalade, located optical in Lisbon Keywords: Soiling; PV modules; soil composition; optical losses
buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were 1.compared Introduction with results from a dynamic heat demand model, previously developed and validated by the authors. 1.The Introduction results showed that when only weather change is considered, the margin of error could be acceptable for some applications The process by demand which dust and dirt accumulates onconsidered). the surfaceHowever, of a photovoltaic (PV) renovation module, (the error in annual was lower thandeposits 20% for and all weather scenarios after introducing The process by value which dust and deposits and accumulates onproduction the renovation surface a photovoltaic (PV)considered). module, scenarios, error increased up dirt to 59.5% (depending on of theenergy weather and combination referred as the soiling, can lead to detrimental effects in terms [1].ofscenarios The soiling is therefore one of referred as of soiling, lead energy toincreased detrimental effectsincrease in terms ofrange energy production [1].per The soilingthat is therefore one Themajor value slope can coefficient on losses average within theupon of 3.8% upThe to 8% decade, corresponds to of the the concerns since yield exposure. soiling process can be dissimilar decrease the the number of heating hours of 22-139h during theupon heating seasonUrban (depending on (dominated the combination of weather and the majorin concerns since energy losses exposure. The areas soiling process can dissimilar depending on environment at yield which a PVincrease system is installed. by be coal-derived renovation scenarios considered). other ahand, increased for 7.8-12.7% per decade by (depending on the depending on agricultural the environment at the which PV function system ismain installed. Urban areas (dominated coal-derived contaminants), areasOn and deserts represent threeintercept environments producing different kind of negative coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and contaminants), agricultural areas and deserts represent three main environments producing different kind of negative improve the accuracy of heat demand estimations. *
© 2017 The Authors. Published by Elsevier Ltd.
Douglas Olivares. Tel.: +56 55 512530. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * E-mail address: [email protected] Douglas Olivares. Tel.: +56 55 512530. Cooling. E-mail address: [email protected] 1876-6102 2017demand; The Authors. Published bychange Elsevier Ltd. Keywords:©Heat Forecast; Climate 1876-6102 The Authors. Published by Elsevier Ltd. Peer review©by2017 the scientific conference committee of SiliconPV 2017 under responsibility of PSE AG. Peer review by the scientific conference committee of SiliconPV 2017 under responsibility of PSE AG.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer review by the scientific conference committee of SiliconPV 2017 under responsibility of PSE AG. 10.1016/j.egypro.2017.09.263
Douglas Olivares et al. / Energy Procedia 124 (2017) 547–553 Douglas Olivares / Energy Procedia 00 (2017) 000–000
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agents against PV performance. With this regard, the magnitude by which the performance of a PV system decreases can depend on the morphology and composition of the pollutants at each site [2]. It is pointed out that an equal surface density of several soil compositions may lead to different effects. Consequently, the prediction of energy yield for a PV system must consider studies of the specific place. The knowledge about the physical and chemical properties of soiling material can be relevant to determine cleaning schedules for optimal performance and discern which kind of environments are more harmful for PV modules [3]. Concerning deserts, these areas offer an opportunity for PV implementation and huge potential for electricity generation due to the high global irradiance. However, PV modules and balance of system (BOS) components must face extreme environment conditions. To mention some of these factors are the arid environments, strong winds and possible storms producing abrasion, high ultraviolet content producing polymer degradation, extreme temperature fluctuations leading to material stress and dust reducing the transmittance of PV glass [4]. The Atacama Desert in Chile receives the highest solar radiation levels placing this region to be one of the most attractive locations for PV implementation. The global horizontal irradiation reaches values of at least 2500 kWh/m2 [5]. According to local measurements the mean clearness index of this region is 3%, which is in agreement with [6], a study about the Atacama Desert, reporting low annual precipitations (below 50 mm). That study shows that during winter, mean temperatures are between 10 ºC and 20 ºC and, whereas during summer, 20 ºC to 30 ºC are measured, with the air temperature remaining below 38 ºC. The maximum air temperature recorded was below 38 ºC and the minimum was -5.7 ºC. Winds averaged from a few meters per second to strong winds from the west reaching values above 12 m/s [6]. The aim of this work is the characterization of the dust, which deposits on PV modules at different locations in the Atacama Desert, Chile, and finding the impact of the deposited dust and the optical response of PV glass. Nomenclature a b c d e f g h i
Albite Anorthite Calcite Cristobalite Gypsum Halite Quartz Muskovite Orthoclase
NaAlSi3O8 CaAl2Si2O8 CaCO3 SiO2 CaSO4·2H2O NaCl SIO2 KAl2(AlSi3O10)(OH)2 KAlSi3O8
2. Experimental We analyzed dust from 4 locations in the Atacama Desert (Table 1) exhibiting different climatologic characteristics. The locations denoted as L1, L2, L3 were selected to collect dust from the ground and from the module surface. We analyzed samples from each case through laser diffraction spectroscopy (LDS), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD) to compare the deposited dust with the dust collected from the ground. The transmittance loss was measured with portable spectrophotometer (250-850 nm) for PV glass installed at location L4 after 4 months dust accumulation. Table 1. Locations and climates at each location. Location Long name L1 Arica L2 Industrial environment L3 Antofagasta L4 PSDA
Climate Normal desert Desert landscape with mining influence Coastal desert Normal desert
Douglas Olivares et al. / Energy Procedia 124 (2017) 547–553 Douglas Olivares / Energy Procedia 00 (2017) 000–000
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3. Results 3.1. Particle size distribution Fig. 1a shows the particle size distribution for L1, L2 and L3 locations obtained via sieving. It was determined that the dust accumulating on PV modules has an average particle size less than 50 μm. Fig. 1b shows also the particle size distribution for same locations obtained via LDS. It was found that particle size was smaller than 63 μm. Location L2 is influenced by a mining environment and therefore a finer dust with a characteristic particle size of 16 μm was found.
Fig 1 (a) Particle size distribution through sieving. (b) Particle size distribution through LDS. In both cases characteristic particle size of dust to deposit was smaller than 60 μm.
Through the EDX characterization, the particle size distribution of the deposited dust was classified according to the Udden-Wentworth [7] scale, shown in Table 2. The higher percentage on the module surface corresponds to lime in all classifications, except at L2, where a 14% is clay. This result can be directly linked to the location of the PV installation. In this place (L2), there is a continuous soil movement due to the industrial and mining activities. Table 2. Size distribution measurements collected for each dust sample. Diameter, D (µm) L1 L2 250-125 2.3% 0% 125-63 15.2% 2.3% 63-31 47.2% 15.4% 31-16 22.6% 26.9% 16-8 9.8% 27.3% 8-4 2.6% 13.3% 0.4% 14.1% <4
L3 2.0% 8.3% 39.2% 27.5% 16.7% 5.0% 1.3%
Grain type Fine grained Very fine grained Coarse silt Medium silt Fine silt Very fine silt Clay
3.2. SEM analysis In order to analyze and to gain a deeper insight into the particle size distribution, SEM images were obtained. Fig. 2 shows a comparison of locations L1, L2 and L3. These samples collected do not exhibit uniformity in the size and shape. The SEM images reveal a tendency for spherical and prismatic geometry. The morphology of each particle is related with the dust deposition on the module surface. Starting from a clean glass surface, first layer of dust particles may deposit randomly, exhibiting any shape. As the space available turns limited, fine dust particles of spherical geometry may fill the small gaps between the pre-existing deposited material.
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L1
L2
L3
Fig. 2. SEM images for locations L1, L2 and L3. Particles with prismatic geometry marked in red are less frequent than particles with spherical geometry marked in blue.
3.3. Elemental analysis The dust, which deposits on the PV modules, may originate from the ground of each location. The solid fraction is variable in size and composition. The samples collected at L1, L2 and L3 locations exhibit fragments of mineral rocks or several types. These materials are residuals of consolidated rock after years of geological processes creating minerals and soils with different properties. Consequently, it is necessary to determine which are the crystalline species in the deposited dust. In order to determine the elemental composition of ground samples, EDX analysis was used.
Fig 3. Percentage of elements in the dust samples collected from the ground through EDX for locations L1, L2 and L3.
The existence of the elements in Fig. 3 is due to the fact that the sample was collected from the ground surface where ions such as O-2, Si+4, Al+3, Fe+3, Fe+2, Ca+2, Mg+2, Na+ and K+ are found and constituting 98.5% of the soil [8]. The latter allows corroborating the results since oxygen and silicon are the dominating elements in the Earth crust. Additionally, chlorine was encountered, which is an element usually present in the Chilean coasts and also shown in Fig. 3. The presence of Si, O and Cl are responsible for chemical properties of the dust. One of its characteristics is the salinity given by the excess of chlorides, sulphates and oxides. These compounds can be in the form of precipitated crystals or at intramolecular spaces at a trace level (i.e. low concentration). There are traces of other elements but with concentrations below the limit for quantification. For instance, traces of copper were found at L2 as Fig. 4 shows.
Douglas Olivares et al. / Energy Procedia 124 (2017) 547–553 Douglas Olivares / Energy Procedia 00 (2017) 000–000
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Fig 4. EDX for sample from L2. A copper signal of low intensity is found.
3.4. Identification of minerals The minerals present in samples collected from the ground and module surface were studied by means of XRD. The analysis was based on the compounds derived from Andesite, a subvolcanic material, and from other primary minerals such as albite, anorthite, muskovite and quartz. A total of 9 main minerals were found: albite (a silicate), anorthite (an aluminosilicate of calcium), calcite (a type of calcium carbonate), cristobalite (a form of quartz), gypsum (an hydrated calcium sulphate), halite (a rock salt), quartz (silicon oxide), muskovite (a phyllosilicate) and orthoclase (a tectosilicate). Fig. 5 shows diffractograms for dust samples collected from the ground and from the module surface. It was observed that the dust samples at the different locations of northern Chile share a similar particle size and similar elemental composition. However, the minerals present in the sample will be different at each place, due to their climatic and geological characteristics. In the case of L1 there is no presence of albite but it is found in L2 and L3. The same case occurs for the cristobalite which is present only at L1 but not at L2 and L3. Muscovite was found at L1 and L2 but not in L3. The mineralogical characteristics of the material present at each site may produce different interactions on the PV module glass surface, for example, increasing corrosion rates and abrasion of the glass due to the hardness of the particle. With this regard, the presence of chlorides () ି݈ܥ, sulphates (ܱܵସଶି ) and nitrites (ܱܰଷି ) may produce corrosion of the PV device [9]. An investigation on corrosion of PV modules with transparent conducting layers (TCO) [10] came to the conclusion that when the module is positively biased from the frame, little damage was produced. This result was attributed to the dependence of the corrosion on the direction of the internal electric fields. Another finding was that frameless modules with mounting points to the backsheet exhibited no damage. It has been shown that humidity and temperature play a major role in this process [11]. 3.5. Soiling composition from the ground and module surface The samples collected were analyzed by XRD to determine if there is a difference between te composition of the dust from the ground the dust deposited on the module surface. The results are depicted in the diffractograms of Fig. 5. It can be observed that same composition was found for samples from ground and module surface. The comparison of diffractograms shows signals (peaks) at the same position (2θ-axis), indicating the presence of the same compound, but having signals of different intensity. This phenomenon is caused by differences in the concentration of compounds that exist between dust from the ground and dust deposited on the module surface. In addition, an overlap between signals can be observed, mainly produced by the characteristics of each sample, which are a mixture of compounds.
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Fig 5. Diffractograms for the compound composition of the dust collected from the ground and dust collected from the module surface, for locations L1, L2 and L3. Based on the analysis of samples collected from the ground, the comparison between locations reveal differences in compund composition. For a same location, the presence of same minerals but different intensities at same position (2θ-axis) indicates no fundamental difference between dust from the ground and from the module surface.
3.6. Transmittance losses Table 3 shows the transmittance loss measured for PV glass installed at L4 location. The PV glass was installed in spring and its transmittance was monitored for the next seasons. In summer, the transmittance reduced by 10.6% relative. After 4 months, corresponding to autumn, the transmittance reduced by 55% relative loss, with respect to the transmittance before any exposition to the environment. Table 3. Transmittance Losses. Day
Date
Season
Transmittance (250-850) nm
Loss transmittance
0 52 124
20/10/2015 21/01/2016 1/04/2016
Spring Summer Autumn
85% 76% 47%
10.6% 55.0%
4. Discussion The particle size and morphology for L1, L2 and L3 locations, exhibiting different climatic conditions, is expected to be in the range 20-63 μm. This is the size to stick on the PV glasss reducing power performance. However, locations differentiate from each other due to the existence and non-existence of specific mineral compound. The geographical characteristics of a place such as wind, humidity, temperature and pressure can determine the chemical composition of the soil [12,13]. In this study, the dust deposited on the PV modules and the dust from the ground exhibit the same chemical composition. Altough L2 is placed at an industrial environment and L3 is at a urban zone, results showed no important traces of contaminants derived from the mining activity or carbon derived pollutants. Transmittance losses in northern Chile can be an issue, which was observed at L4 location, reducing the output current and power [14].
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5. Conclusion The dust, which deposits on PV modules in the Atacama Desert in Chile, shows a particle size of less than 63 μm. The conditions of the location where the PV system is installed can determine that dust particles to deposit have a smaller size, such as the location at industrial/mining environment. The morphology of the deposited dust particles exhibits a tendency for spherical geometry. The chemical composition of the dust collected from the module surface and from the ground was found to be similar, indicating no presence of dust from other locations. However, the composition can differ from place to place. For instance, cuprite was found only at the location with a industrial/mining influence. The transmittance is affected by dust accumulation It was found that the relative transmittance loss was 55% after 4 month dust accumulation. Acknowledgements This work was supported in part by CORFO, in part by FONDECYT/CONICYT Project Number 3160190, in part by CONICYT/FONDAP/15110019 “Solar Energy Research Center” SERC-Chile and in part by the BMBF Solar Collaboration between Chile and Deutschland (Solar ChilD) project number 01DN14005. The authors acknowledge the support provided within these frameworks. References [1] Adinoyi MJ, Said SAM. Effect of Dust accumulation on the power outputs of solar photovoltaic modules, Renewable Energy 2013;60:633636. [2] Kaldellis J, Fragos P, Kapsali M. Systematic experimental study of the pollution deposition impact on the energy yield of photovoltaic installations. Renew. Energy 2011;36(10):2717–2724. [3] Mani M, Pillai R. Impact of dust on solar photovoltaic (PV) performance: Research status, challenges and recommendations, Renewable and Sustainable 2010;14:3124-3131. [4] Herrmann J, Lorenz T, Slamova K, Klimm E, Koehl M, Weiss KA. Desert Applications of PV Modules. 40th IEEE PVSC, 8-13 June 2014, Denver, Colorado, USA. [5] Escobar R, Cortes C, Pino A, Pereira EB, Ramos Martins F, Cardemil JM. Solar energy resource assessment in Chile: Satellite estimation and ground station measurements., Renewable Energy 2014;71:324–332. [6] Mckay CP, Friedmann EI, Gómez-Silva B, Cáceres-Villanueva L, Andersen DT, Landheim R. Temperature and moisture conditions for life in the extreme arid region of the Atacama desert: four years of observations including the El Niño of 1997–1998. Astrobiology 2003;3(2):393–406. [7] Udden, JA. Mechanical composition of clastic sediments. Geological Society of America Bulletin 1914;25(1):655–744. [8] Mile M and Mitkova T. Soil Moisture Retention Changes in Terms of Mineralogical Composition of Clays Phase. In: Valaškova M and Martynkova GS, editors , Clay Minerals in Nature - Their Characterization, Modification and Application. InTech; 2012. p. 101-118. [9] Mathiak G, Althaus J, Menzler S, Lichtschläger L, Herrmann W. PV Module Corrosion from Ammonia and Salt Mist - Experimental Study With Fullsize Modules. 27th EU PVSEC 24-28 September 2012, Frankfurt, Germany. [10] McMahon & Osteward (2003). Electrochemical corrosion of SnO2:F Transparent conducting layer in the thin-film photovoltaic modules. Solar Energy Materials and Solar Cells 2003;79:21-33. [11 Ndiayea A, Charki A, Kobi A, Kébéa CMF, Ndiaye PA, Sambou V. Degradations of silicon photovoltaic modules: A literature review. Solar Energy 2013;96:140-151. [12] Mekhilef S, Saidur R, Kamalisarvestani M. Effect of dust and air velocity on efficiency of photovoltaic cells. Renewable and Sustainable Energy Reviews 2012;16:2920-2925. [13] Ghazi S, Sayigh A, Ip K. Dust effect on flat surfaces – A review paper. Renewable and Sustainable Energy Reviews 2014;33:742-751. [14] Maghami MR, Hizam H, Gomes C, Radzi MA, Rezadad MI, Hajighorbani S. Power loss due to soiling on solar panel: A review. Renewable and Sustainable Energy Reviews 2016;59:1307–1316.
ScienceDirect ScienceDirect
Energy Procedia 00 (2017) 000–000 Available online www.sciencedirect.com Available online atatwww.sciencedirect.com Energy Procedia 00 (2017) 000–000
ScienceDirect ScienceDirect
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Energy (2017) 000–000 547–553 EnergyProcedia Procedia124 00 (2017) www.elsevier.com/locate/procedia
7th International Conference on Silicon Photovoltaics, SiliconPV 2017 7th International Conference on Silicon Photovoltaics, SiliconPV 2017
Characterization of soiling on PV modules in the Atacama Desert Characterization of soiling on PV modules in the Atacama Desert
Thea*15th Internationala Symposium on District Heating anda Cooling b c Douglas Olivares a*, Pablo Ferradaa, Camila de Matosb, Aitor Marzoa, Enrique Cabrerac, a d Douglas Olivares , Pablo Ferrada Camila ,de Matos , Aitor Marzo , Enrique Cabrera , Carlos,Portillo a Jaime Llanosd Assessing the feasibility of using heat demand-outdoor Carlos Portillo , Jaimethe Llanos a
Centro de Desarrollo Energético Antofagasta (CDEA), Universidad de Antofagasta, Angamos #601 Antofagasta, Chile
Centro de Desarrollo Energético Universidad3721, de Antofagasta, Angamos Antofagasta, Chile LaborelecAntofagasta Chile Lab), Apoquindo O.32, Santiago, Chile#601 temperature function for(ENGIE a (CDEA), long-term district heat demand forecast a
b
c c
b Laborelec ChileCenter (ENGIE Lab), Apoquindo 3721, O.32, Santiago, Chile15 D78467, Germany International Solar energy Research Konstanz (ISC Konstanz), Rudolph-Diesel-Str. d International Solar energy Research Center Konstanz (ISCdel Konstanz), 15 D78467, Departamento de Química, Universidad Norte, Angamos #610, Antofagasta, a,b,c a aCatólica bRudolph-Diesel-Str. c ChileGermany d Departamento de Química, Universidad Católica del Norte, Angamos #610, Antofagasta, Chile
I. Andrić a
*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Correc
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b
Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Abstract The soling can negatively affect the performance of photovoltaic systems. We studied the species, which deposit on photovoltaic The caninnegatively affect (Atacama the performance photovoltaic systems. We studied thebase species, which deposit of ondust photovoltaic (PV)soling modules northern Chile Desert).ofThe environmental conditions are the for the interaction particles (PV) modules in northern Chile (Atacama Desert). The environmental conditions are the base for the interaction of dust particles and the module’s surfaces. We considered 4 locations for the study. We determined that the particle size of the dust to deposit on Abstract and modules the module’s surfaces. locations forsites. the study. We determined that the particle size of the deposit on PV is smaller thanWe 63considered μm for all4the selected However, the morphology varies from place to dust placetoinfluencing PV modules is smaller thanare 63 commonly μm all addressed the selected However, fromsolutions place to place influencing optical response ofnetworks the modules. Afterfor4 months dust accumulation the transmittance PVvaries glass reduced by 55%. District heating in sites. the literature asthe onemorphology of theofmost effective for decreasing the optical response of the modules. After 4 months dust accumulation the transmittance of PV glass reduced by 55%. greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat ©sales. 2017 The Authors. Published by Elsevier Ltd. to the changed climate conditions © 2017 Due The Authors. Published by Elsevier Ltd. and building renovation policies, heat demand in the future could decrease, © 2017 The Authors. Published byperiod. Elsevier Ltd. of SiliconPV 2017 under responsibility of PSE AG. Peer review scientific conference committee prolonging thethe investment Peer review by by the scientificreturn conference committee of SiliconPV 2017 under responsibility of PSE AG. Peer review by the scientific conference committee of SiliconPV under responsibility PSE AG. function for heat demand The main scope of this paper is to assess the feasibility of using 2017 the heat demand – outdooroftemperature
Keywords: PV modules; soil composition; losses(Portugal), was used as a case study. The district is consisted of 665 forecast. Soiling; The district of Alvalade, located optical in Lisbon Keywords: Soiling; PV modules; soil composition; optical losses
buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were 1.compared Introduction with results from a dynamic heat demand model, previously developed and validated by the authors. 1.The Introduction results showed that when only weather change is considered, the margin of error could be acceptable for some applications The process by demand which dust and dirt accumulates onconsidered). the surfaceHowever, of a photovoltaic (PV) renovation module, (the error in annual was lower thandeposits 20% for and all weather scenarios after introducing The process by value which dust and deposits and accumulates onproduction the renovation surface a photovoltaic (PV)considered). module, scenarios, error increased up dirt to 59.5% (depending on of theenergy weather and combination referred as the soiling, can lead to detrimental effects in terms [1].ofscenarios The soiling is therefore one of referred as of soiling, lead energy toincreased detrimental effectsincrease in terms ofrange energy production [1].per The soilingthat is therefore one Themajor value slope can coefficient on losses average within theupon of 3.8% upThe to 8% decade, corresponds to of the the concerns since yield exposure. soiling process can be dissimilar decrease the the number of heating hours of 22-139h during theupon heating seasonUrban (depending on (dominated the combination of weather and the majorin concerns since energy losses exposure. The areas soiling process can dissimilar depending on environment at yield which a PVincrease system is installed. by be coal-derived renovation scenarios considered). other ahand, increased for 7.8-12.7% per decade by (depending on the depending on agricultural the environment at the which PV function system ismain installed. Urban areas (dominated coal-derived contaminants), areasOn and deserts represent threeintercept environments producing different kind of negative coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and contaminants), agricultural areas and deserts represent three main environments producing different kind of negative improve the accuracy of heat demand estimations. *
© 2017 The Authors. Published by Elsevier Ltd.
Douglas Olivares. Tel.: +56 55 512530. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * E-mail address: [email protected] Douglas Olivares. Tel.: +56 55 512530. Cooling. E-mail address: [email protected] 1876-6102 2017demand; The Authors. Published bychange Elsevier Ltd. Keywords:©Heat Forecast; Climate 1876-6102 The Authors. Published by Elsevier Ltd. Peer review©by2017 the scientific conference committee of SiliconPV 2017 under responsibility of PSE AG. Peer review by the scientific conference committee of SiliconPV 2017 under responsibility of PSE AG.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer review by the scientific conference committee of SiliconPV 2017 under responsibility of PSE AG. 10.1016/j.egypro.2017.09.263
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agents against PV performance. With this regard, the magnitude by which the performance of a PV system decreases can depend on the morphology and composition of the pollutants at each site [2]. It is pointed out that an equal surface density of several soil compositions may lead to different effects. Consequently, the prediction of energy yield for a PV system must consider studies of the specific place. The knowledge about the physical and chemical properties of soiling material can be relevant to determine cleaning schedules for optimal performance and discern which kind of environments are more harmful for PV modules [3]. Concerning deserts, these areas offer an opportunity for PV implementation and huge potential for electricity generation due to the high global irradiance. However, PV modules and balance of system (BOS) components must face extreme environment conditions. To mention some of these factors are the arid environments, strong winds and possible storms producing abrasion, high ultraviolet content producing polymer degradation, extreme temperature fluctuations leading to material stress and dust reducing the transmittance of PV glass [4]. The Atacama Desert in Chile receives the highest solar radiation levels placing this region to be one of the most attractive locations for PV implementation. The global horizontal irradiation reaches values of at least 2500 kWh/m2 [5]. According to local measurements the mean clearness index of this region is 3%, which is in agreement with [6], a study about the Atacama Desert, reporting low annual precipitations (below 50 mm). That study shows that during winter, mean temperatures are between 10 ºC and 20 ºC and, whereas during summer, 20 ºC to 30 ºC are measured, with the air temperature remaining below 38 ºC. The maximum air temperature recorded was below 38 ºC and the minimum was -5.7 ºC. Winds averaged from a few meters per second to strong winds from the west reaching values above 12 m/s [6]. The aim of this work is the characterization of the dust, which deposits on PV modules at different locations in the Atacama Desert, Chile, and finding the impact of the deposited dust and the optical response of PV glass. Nomenclature a b c d e f g h i
Albite Anorthite Calcite Cristobalite Gypsum Halite Quartz Muskovite Orthoclase
NaAlSi3O8 CaAl2Si2O8 CaCO3 SiO2 CaSO4·2H2O NaCl SIO2 KAl2(AlSi3O10)(OH)2 KAlSi3O8
2. Experimental We analyzed dust from 4 locations in the Atacama Desert (Table 1) exhibiting different climatologic characteristics. The locations denoted as L1, L2, L3 were selected to collect dust from the ground and from the module surface. We analyzed samples from each case through laser diffraction spectroscopy (LDS), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD) to compare the deposited dust with the dust collected from the ground. The transmittance loss was measured with portable spectrophotometer (250-850 nm) for PV glass installed at location L4 after 4 months dust accumulation. Table 1. Locations and climates at each location. Location Long name L1 Arica L2 Industrial environment L3 Antofagasta L4 PSDA
Climate Normal desert Desert landscape with mining influence Coastal desert Normal desert
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3. Results 3.1. Particle size distribution Fig. 1a shows the particle size distribution for L1, L2 and L3 locations obtained via sieving. It was determined that the dust accumulating on PV modules has an average particle size less than 50 μm. Fig. 1b shows also the particle size distribution for same locations obtained via LDS. It was found that particle size was smaller than 63 μm. Location L2 is influenced by a mining environment and therefore a finer dust with a characteristic particle size of 16 μm was found.
Fig 1 (a) Particle size distribution through sieving. (b) Particle size distribution through LDS. In both cases characteristic particle size of dust to deposit was smaller than 60 μm.
Through the EDX characterization, the particle size distribution of the deposited dust was classified according to the Udden-Wentworth [7] scale, shown in Table 2. The higher percentage on the module surface corresponds to lime in all classifications, except at L2, where a 14% is clay. This result can be directly linked to the location of the PV installation. In this place (L2), there is a continuous soil movement due to the industrial and mining activities. Table 2. Size distribution measurements collected for each dust sample. Diameter, D (µm) L1 L2 250-125 2.3% 0% 125-63 15.2% 2.3% 63-31 47.2% 15.4% 31-16 22.6% 26.9% 16-8 9.8% 27.3% 8-4 2.6% 13.3% 0.4% 14.1% <4
L3 2.0% 8.3% 39.2% 27.5% 16.7% 5.0% 1.3%
Grain type Fine grained Very fine grained Coarse silt Medium silt Fine silt Very fine silt Clay
3.2. SEM analysis In order to analyze and to gain a deeper insight into the particle size distribution, SEM images were obtained. Fig. 2 shows a comparison of locations L1, L2 and L3. These samples collected do not exhibit uniformity in the size and shape. The SEM images reveal a tendency for spherical and prismatic geometry. The morphology of each particle is related with the dust deposition on the module surface. Starting from a clean glass surface, first layer of dust particles may deposit randomly, exhibiting any shape. As the space available turns limited, fine dust particles of spherical geometry may fill the small gaps between the pre-existing deposited material.
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L1
L2
L3
Fig. 2. SEM images for locations L1, L2 and L3. Particles with prismatic geometry marked in red are less frequent than particles with spherical geometry marked in blue.
3.3. Elemental analysis The dust, which deposits on the PV modules, may originate from the ground of each location. The solid fraction is variable in size and composition. The samples collected at L1, L2 and L3 locations exhibit fragments of mineral rocks or several types. These materials are residuals of consolidated rock after years of geological processes creating minerals and soils with different properties. Consequently, it is necessary to determine which are the crystalline species in the deposited dust. In order to determine the elemental composition of ground samples, EDX analysis was used.
Fig 3. Percentage of elements in the dust samples collected from the ground through EDX for locations L1, L2 and L3.
The existence of the elements in Fig. 3 is due to the fact that the sample was collected from the ground surface where ions such as O-2, Si+4, Al+3, Fe+3, Fe+2, Ca+2, Mg+2, Na+ and K+ are found and constituting 98.5% of the soil [8]. The latter allows corroborating the results since oxygen and silicon are the dominating elements in the Earth crust. Additionally, chlorine was encountered, which is an element usually present in the Chilean coasts and also shown in Fig. 3. The presence of Si, O and Cl are responsible for chemical properties of the dust. One of its characteristics is the salinity given by the excess of chlorides, sulphates and oxides. These compounds can be in the form of precipitated crystals or at intramolecular spaces at a trace level (i.e. low concentration). There are traces of other elements but with concentrations below the limit for quantification. For instance, traces of copper were found at L2 as Fig. 4 shows.
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Fig 4. EDX for sample from L2. A copper signal of low intensity is found.
3.4. Identification of minerals The minerals present in samples collected from the ground and module surface were studied by means of XRD. The analysis was based on the compounds derived from Andesite, a subvolcanic material, and from other primary minerals such as albite, anorthite, muskovite and quartz. A total of 9 main minerals were found: albite (a silicate), anorthite (an aluminosilicate of calcium), calcite (a type of calcium carbonate), cristobalite (a form of quartz), gypsum (an hydrated calcium sulphate), halite (a rock salt), quartz (silicon oxide), muskovite (a phyllosilicate) and orthoclase (a tectosilicate). Fig. 5 shows diffractograms for dust samples collected from the ground and from the module surface. It was observed that the dust samples at the different locations of northern Chile share a similar particle size and similar elemental composition. However, the minerals present in the sample will be different at each place, due to their climatic and geological characteristics. In the case of L1 there is no presence of albite but it is found in L2 and L3. The same case occurs for the cristobalite which is present only at L1 but not at L2 and L3. Muscovite was found at L1 and L2 but not in L3. The mineralogical characteristics of the material present at each site may produce different interactions on the PV module glass surface, for example, increasing corrosion rates and abrasion of the glass due to the hardness of the particle. With this regard, the presence of chlorides () ି݈ܥ, sulphates (ܱܵସଶି ) and nitrites (ܱܰଷି ) may produce corrosion of the PV device [9]. An investigation on corrosion of PV modules with transparent conducting layers (TCO) [10] came to the conclusion that when the module is positively biased from the frame, little damage was produced. This result was attributed to the dependence of the corrosion on the direction of the internal electric fields. Another finding was that frameless modules with mounting points to the backsheet exhibited no damage. It has been shown that humidity and temperature play a major role in this process [11]. 3.5. Soiling composition from the ground and module surface The samples collected were analyzed by XRD to determine if there is a difference between te composition of the dust from the ground the dust deposited on the module surface. The results are depicted in the diffractograms of Fig. 5. It can be observed that same composition was found for samples from ground and module surface. The comparison of diffractograms shows signals (peaks) at the same position (2θ-axis), indicating the presence of the same compound, but having signals of different intensity. This phenomenon is caused by differences in the concentration of compounds that exist between dust from the ground and dust deposited on the module surface. In addition, an overlap between signals can be observed, mainly produced by the characteristics of each sample, which are a mixture of compounds.
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Fig 5. Diffractograms for the compound composition of the dust collected from the ground and dust collected from the module surface, for locations L1, L2 and L3. Based on the analysis of samples collected from the ground, the comparison between locations reveal differences in compund composition. For a same location, the presence of same minerals but different intensities at same position (2θ-axis) indicates no fundamental difference between dust from the ground and from the module surface.
3.6. Transmittance losses Table 3 shows the transmittance loss measured for PV glass installed at L4 location. The PV glass was installed in spring and its transmittance was monitored for the next seasons. In summer, the transmittance reduced by 10.6% relative. After 4 months, corresponding to autumn, the transmittance reduced by 55% relative loss, with respect to the transmittance before any exposition to the environment. Table 3. Transmittance Losses. Day
Date
Season
Transmittance (250-850) nm
Loss transmittance
0 52 124
20/10/2015 21/01/2016 1/04/2016
Spring Summer Autumn
85% 76% 47%
10.6% 55.0%
4. Discussion The particle size and morphology for L1, L2 and L3 locations, exhibiting different climatic conditions, is expected to be in the range 20-63 μm. This is the size to stick on the PV glasss reducing power performance. However, locations differentiate from each other due to the existence and non-existence of specific mineral compound. The geographical characteristics of a place such as wind, humidity, temperature and pressure can determine the chemical composition of the soil [12,13]. In this study, the dust deposited on the PV modules and the dust from the ground exhibit the same chemical composition. Altough L2 is placed at an industrial environment and L3 is at a urban zone, results showed no important traces of contaminants derived from the mining activity or carbon derived pollutants. Transmittance losses in northern Chile can be an issue, which was observed at L4 location, reducing the output current and power [14].
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5. Conclusion The dust, which deposits on PV modules in the Atacama Desert in Chile, shows a particle size of less than 63 μm. The conditions of the location where the PV system is installed can determine that dust particles to deposit have a smaller size, such as the location at industrial/mining environment. The morphology of the deposited dust particles exhibits a tendency for spherical geometry. The chemical composition of the dust collected from the module surface and from the ground was found to be similar, indicating no presence of dust from other locations. However, the composition can differ from place to place. For instance, cuprite was found only at the location with a industrial/mining influence. The transmittance is affected by dust accumulation It was found that the relative transmittance loss was 55% after 4 month dust accumulation. Acknowledgements This work was supported in part by CORFO, in part by FONDECYT/CONICYT Project Number 3160190, in part by CONICYT/FONDAP/15110019 “Solar Energy Research Center” SERC-Chile and in part by the BMBF Solar Collaboration between Chile and Deutschland (Solar ChilD) project number 01DN14005. The authors acknowledge the support provided within these frameworks. References [1] Adinoyi MJ, Said SAM. Effect of Dust accumulation on the power outputs of solar photovoltaic modules, Renewable Energy 2013;60:633636. [2] Kaldellis J, Fragos P, Kapsali M. Systematic experimental study of the pollution deposition impact on the energy yield of photovoltaic installations. Renew. Energy 2011;36(10):2717–2724. [3] Mani M, Pillai R. Impact of dust on solar photovoltaic (PV) performance: Research status, challenges and recommendations, Renewable and Sustainable 2010;14:3124-3131. [4] Herrmann J, Lorenz T, Slamova K, Klimm E, Koehl M, Weiss KA. Desert Applications of PV Modules. 40th IEEE PVSC, 8-13 June 2014, Denver, Colorado, USA. [5] Escobar R, Cortes C, Pino A, Pereira EB, Ramos Martins F, Cardemil JM. Solar energy resource assessment in Chile: Satellite estimation and ground station measurements., Renewable Energy 2014;71:324–332. [6] Mckay CP, Friedmann EI, Gómez-Silva B, Cáceres-Villanueva L, Andersen DT, Landheim R. Temperature and moisture conditions for life in the extreme arid region of the Atacama desert: four years of observations including the El Niño of 1997–1998. Astrobiology 2003;3(2):393–406. [7] Udden, JA. Mechanical composition of clastic sediments. Geological Society of America Bulletin 1914;25(1):655–744. [8] Mile M and Mitkova T. Soil Moisture Retention Changes in Terms of Mineralogical Composition of Clays Phase. In: Valaškova M and Martynkova GS, editors , Clay Minerals in Nature - Their Characterization, Modification and Application. InTech; 2012. p. 101-118. [9] Mathiak G, Althaus J, Menzler S, Lichtschläger L, Herrmann W. PV Module Corrosion from Ammonia and Salt Mist - Experimental Study With Fullsize Modules. 27th EU PVSEC 24-28 September 2012, Frankfurt, Germany. [10] McMahon & Osteward (2003). Electrochemical corrosion of SnO2:F Transparent conducting layer in the thin-film photovoltaic modules. Solar Energy Materials and Solar Cells 2003;79:21-33. [11 Ndiayea A, Charki A, Kobi A, Kébéa CMF, Ndiaye PA, Sambou V. Degradations of silicon photovoltaic modules: A literature review. Solar Energy 2013;96:140-151. [12] Mekhilef S, Saidur R, Kamalisarvestani M. Effect of dust and air velocity on efficiency of photovoltaic cells. Renewable and Sustainable Energy Reviews 2012;16:2920-2925. [13] Ghazi S, Sayigh A, Ip K. Dust effect on flat surfaces – A review paper. Renewable and Sustainable Energy Reviews 2014;33:742-751. [14] Maghami MR, Hizam H, Gomes C, Radzi MA, Rezadad MI, Hajighorbani S. Power loss due to soiling on solar panel: A review. Renewable and Sustainable Energy Reviews 2016;59:1307–1316.