Effect of dust and shadow on performance of solar photovoltaic modules : Experimental analysis

This study presents an experimental performance of a solar photovoltaic module under clean, dust, and shadow conditions. It is found that there is a significant decrease in electrical power produced (40% in the case of dust panels and 80% in the case of shadow panels) and a decrease in efficiency of around 6% in the case with dust and 9% in the case with the shadow, as compared to the clean panel. From the results, it is clear that there is a substantial effect of a partial shadow than dust on the performance of the solar panel. This is due to the more obstruction of the sunlight by the shadowed area compared to the dust. The dust being finer particles for the given local experimental condition did not influence the panel than the shadow. The main outcome of this study is that the shadowing effect may cause more harm to the PV module than dust for the given experimental conditions. However, Further long-term studies on the effect of dust and shadow are needed to understand the effect on performance degradation and module life

Sustainable passive cooling strategy for PV module: A comparative analysis

This paper presents the experimental studies of different passive cooling techniques to analyze the electrical power improvement and temperature reduction of a 50 W polycrystalline PV module. Plant cooling, greenhouse cooling, greenhouse + plant cooling, coir pith, and phase change material cooling are the various approaches are used in the analysis. The percentage of electrical power improvement and temperature of various passive cooling techniques are compared with solar modules without cooling. The maximum percentage power improvement (11.34%) was found to be in coir pith cooling with an average maximum power of 36.38 W. The maximum temperature reduction was observed to be 14 °C in case of plant cooling with a greenhouse. Considering the electrical power improvement and temperature reduction, coir cooling and plant cooling were found to be best suited for the given climatic conditions amongst all cooling techniques. The results also showed that the reduction in temperature does not always give rise to the increase in power as it was depicted in the case of greenhouse net cooling and plant cooling with greenhouse. This kind of cooling technique is best suited for agro-based countries in tropical regions

Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters

One of the challenging tasks in modern aquatic remote sensing is the retrieval of near-surface concentrations of Total Suspended Solids (TSS). This study aims to present a Statistical, inherent Optical property (IOP) -based, and muLti-conditional Inversion proceDure (SOLID) for enhanced retrievals of satellite-derived TSS under a wide range of in-water bio-optical conditions in rivers, lakes, estuaries, and coastal waters. In this study, using a large in situ database (N \u3e 3500), the SOLID model is devised using a three-step procedure: (a) water-type classification of the input remote sensing reflectance (Rrs), (b) retrieval of particulate backscattering (bbp) in the red or near-infrared (NIR) regions using semi-analytical, machine-learning, and empirical models, and (c) estimation of TSS from bbp via water-type-specific empirical models. Using an independent subset of our in situ data (N = 2729) with TSS ranging from 0.1 to 2626.8 [g/m3], the SOLID model is thoroughly examined and compared against several state-of-the-art algorithms (Miller and McKee, 2004; Nechad et al., 2010; Novoa et al., 2017; Ondrusek et al., 2012; Petus et al., 2010). We show that SOLID outperforms all the other models to varying degrees, i.e.,from 10 to \u3e100%, depending on the statistical attributes (e.g., global versus water-type-specific metrics). For demonstration purposes, the model is implemented for images acquired by the MultiSpectral Imager aboard Sentinel-2A/B over the Chesapeake Bay, San-Francisco-Bay-Delta Estuary, Lake Okeechobee, and Lake Taihu. To enable generating consistent, multimission TSS products, its performance is further extended to, and evaluated for, other missions, such as the Ocean and Land Color Instrument (OLCI), Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), and Operational Land Imager (OLI). Sensitivity analyses on uncertainties induced by the atmospheric correction indicate that 10% uncertainty in Rrs leads to \u3c20% uncertainty in TSS retrievals from SOLID. While this study suggests that SOLID has a potential for producing TSS products in global coastal and inland waters, our statistical analysis certainly verifies that there is still a need for improving retrievals across a wide spectrum of particle loads

Power Quality Enhancement in Sensitive Local Distribution Grid Using Interval Type-II Fuzzy Logic Controlled DSTATCOM

In the current scenario, integration of renewables, growth of non-linear industrial and commercial loads results in various power quality issues. Among commercial utilities connected to the grid, hospital-operated loads include sensitive, linear, non-linear, and unbalanced loads. These loads are diverse as well as prioritized, which also causes major power quality issues in the local distribution system. Due to its widespread divergence, it leads to harmonic injection and reactive power imbalance. Distribution Static Compensator (DSTATCOM) is proposed as a solution for harmonic mitigation, load balancing, reactive power imbalances, and neutral current compensation. The present work utilizes Interval Type-2 Fuzzy Logic Controller (IT2FLC) with Recursive Least Square (RLS) filter for generating switching pulses for IGBT switches in the DSTATCOM to improve power quality in the Local Distribution Grid. The proposed approach also shows superior performance over Type 1 fuzzy logic controller and Conventional PI controller in mitigating harmonics. For effective realization, the proposed system is simulated using MATLAB software

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring

ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters

Atmospheric correction over inland and coastal waters is one of the major remaining challenges in aquatic remote sensing, often hindering the quantitative retrieval of biogeochemical variables and analysis of their spatial and temporal variability within aquatic environments. The Atmospheric Correction Intercomparison Exercise (ACIX-Aqua), a joint NASA – ESA activity, was initiated to enable a thorough evaluation of eight state-of-the-art atmospheric correction (AC) processors available for Landsat-8 and Sentinel-2 data processing. Over 1000 radiometric matchups from both freshwaters (rivers, lakes, reservoirs) and coastal waters were utilized to examine the quality of derived aquatic reflectances (̂ρw). This dataset originated from two sources: Data gathered from the international scientific community (henceforth called Community Validation Database, CVD), which captured predominantly inland water observations, and the Ocean Color component of AERONET measurements (AERONET-OC), representing primarily coastal ocean environments. This volume of data permitted the evaluation of the AC processors individually (using all the matchups) and comparatively (across seven different Optical Water Types, OWTs) using common matchups. We found that the performance of the AC processors differed for CVD and AERONET-OC matchups, likely reflecting inherent variability in aquatic and atmospheric properties between the two datasets. For the former, the median errors in ̂ρw(560) and ̂ρw(664) were found to range from 20 to 30% for best-performing processors. Using the AERONET-OC matchups, our performance assessments showed that median errors within the 15–30% range in these spectral bands may be achieved. The largest uncertainties were associated with the blue bands (25 to 60%) for best-performing processors considering both CVD and AERONET-OC assessments. We further assessed uncertainty propagation to the downstream products such as near-surface concentration of chlorophyll-a (Chla) and Total Suspended Solids (TSS). Using satellite matchups from the CVD along with in situ Chla and TSS, we found that 20–30% uncertainties in ̂ρw(490 ≤ λ ≤ 743 nm) yielded 25–70% uncertainties in derived Chla and TSS products for topperforming AC processors. We summarize our results using performance matrices guiding the satellite user community through the OWT-specific relative performance of AC processors. Our analysis stresses the need for better representation of aerosols, particularly absorbing ones, and improvements in corrections for sky- (or sun-) glint and adjacency effects, in order to achieve higher quality downstream products in freshwater and coastal ecosystems

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring.Additional co-authors: Courtney Di Vittorio, Nathan Drayson, Reagan M. Errera, Virginia Fernandez, Dariusz Ficek, Cédric G. Fichot, Peter Gege, Claudia Giardino, Anatoly A. Gitelson, Steven R. Greb, Hayden Henderson, Hiroto Higa, Abolfazl Irani Rahaghi, Cédric Jamet, Thomas Jordan, Kersti Kangro, Jeremy A. Kravitz, Arne S. Kristoffersen, Raphael Kudela, Lin Li, Martin Ligi, Hubert Loisel, Steven Lohrenz, Ronghua Ma, Daniel A. Maciel, Tim J. Malthus, Bunkei Matsushita, Mark Matthews, Camille Minaudo, Deepak R. Mishra, Sachidananda Mishra, Tim Moore, Wesley J. Moses, Hà Nguyễn, Evlyn M. L. M. Novo, Stéfani Novoa, Daniel Odermatt, David M. O’Donnell, Leif G. Olmanson, Michael Ondrusek, Natascha Oppelt, Sylvain Ouillon, Waterloo Pereira Filho, Stefan Plattner, Antonio Ruiz Verdú, Salem I. Salem, John F. Schalles, Stefan G. H. Simis, Eko Siswanto, Brandon Smith, Ian Somlai-Schweiger, Mariana A. Soppa, Elinor Tessin, Hendrik J. van der Woerd, Andrea Vander Woude, Ryan A. Vandermeulen, Vincent Vantrepotte, Marcel R. Wernand, Kyana Young & Linwei Yu

Modelling of underwater light fields in turbid and eutrophic waters: application and validation with experimental data

A reliable radiative transfer (RT) model is an essential and indispensable tool for understanding the radiative transfer processes in homogenous and layered waters, analyzing measurements made by radiance sensors and developing remote-sensing algorithms to derive meaningful physical quantities and biogeochemical variables in turbid and productive coastal waters. Existing radiative transfer models have been designed to be applicable to either homogenous waters or inhomogeneous waters. To overcome such constraints associated with these models, this study presents a radiative transfer model that treats a homogenous layer as a diffuse part and an inhomogeneous layer as a direct part in the water column and combines these two parts appropriately in order to generate more reliable underwater light-field data such as upwelling radiance (Lu), downwelling irradiance (Ed) and upwelling irradiance (Eu). The diffuse model assumes the inherent optical properties (IOPs) to be vertically continuous and the light fields to exponentially decrease with depth, whereas the direct part considers the water column to be vertically inhomogeneous (layer-by-layer phenomena) with the vertically varying phase function. The surface and bottom boundary conditions, source function due to chlorophyll and solar incident geometry are also included in the present RT model. The performance of this model is assessed in a variety of waters (clear, turbid and eutrophic) using the measured radiometric data. The present model shows an advantage in terms of producing accurate Lu, Ed and Eu profiles (in spatial domain) in different waters determined by both homogenous and inhomogeneous conditions. The feasibility of predicting these underwater light fields based on the remotely estimated IOP data is also examined using the present RT model. For this application, vertical profiles of the water constituents and IOPs are estimated by empirical models based on our in situ data. The present RT model generates Lu, Ed and Eu spectra closely consistent with the measured data. These results lead to a conclusion that the present RT model is a viable alternative to existing RT models and has an important implication for remote sensing of optically complex waters