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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
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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%
