Solar Radiation Measurements Research Articles

An in-depth analysis of two common methodologies used to derive hourly solar radiation values from daily ones: pros and cons

Solar radiation comprises the primary renewable source of energy on Earth and has so been exploited in the last 20 years. Despite this, solar radiation measurements are scarce worldwide, thus giving space to modelling. Nevertheless, modelling solar radiation at an hourly level is nowadays required for a short-term output forecast from solar installations. The daily global solar radiation decomposition models are one category of solar models that convert daily solar radiation values to hourly ones. The Collares-Pereira and Rabl (CPR) and Collares-Repeira, Rabl and Gueymard (CPRG) models have shown to provide a better performance than others at individual sites without exhibiting any sign of universality on the other hand. The current study looks at this gap. In this regard, twelve sites are selected around the world. To estimate hourly values, the CPR and CPRG models are applied to daily solar radiation estimates for each site in particular years. Hourly data sets that are openly accessible provide the daily values. Additionally, daily and monthly values are derived from the estimated and observed hourly values. The hourly, daily, and monthly scales are used to compare the two models’ performances. The CPR model outperforms the CPRG model across all sites and time scales. A universal coefficient of correction is used to further enhance the CPR performance, bringing the CPR-estimated solar radiation very close to the observed one.

Development of a fixed-order controller for a robust P&O-MPPT strategy to control poly-crystalline solar PV energy systems

This paper presents a novel approach to modeling and controlling a solar photovoltaic conversion system(SPCS) that operates under real-time weather conditions. The primary contribution is the introduction of an uncertain model, which has not been published before, simulating the SPCS’s actual functioning. The proposed robust control strategy involves two stages: first, modifying the standard Perturb and Observe (P&O) algorithm to generate an optimal reference voltage using real-time measurements of temperature, solar irradiance, and wind speed. This modification leads to determining and linearizing the nonlinear current-voltage (I-V) characteristics of the photovoltaic (PV) array near standard test conditions (STC), resulting in an uncertain equivalent resistance used to synthesize an overall model. In the second stage, a robust fixed-order controller is designed based on this uncertain model, with frequency-domain specifications framed as a weighted-mixed sensitivity problem. The optimal solution provides the controller parameters, ensuring good reference tracking dynamics, noise suppression, and attenuation of model uncertainties. Performance assessments at STC compare the standard and robust P&O-MPPT strategies, demonstrating the proposed method’s superiority in performance and robustness, especially under sudden meteorological changes and varying loads. Experiment results confirm the new control strategy’s effectiveness over the standard approach.

Assessing a Hybrid Wind-Solar Irrigation System for Kiwi Orchards in Northern Iran: Feasibility, Environmental Impact, and Economic Viability

In this research, the viability of hybrid wind and solar energy for irrigating kiwi orchards in Guilan province, located in the northern part of Iran is explored. Analysis of wind speed data reveals that wind energy can be utilized for irrigation purposes for more than six months annually. The wind power density, peaking at 467 W/m², supports the feasibility of wind energy for irrigation over ten months each year. Solar irradiance measurements estimate an energy generation of approximately 5.23 kWh/m² from January to July. The average daily temperature, peaking at 29.7°C, suggests optimal conditions for the efficient operation of solar panels. The net water requirement for the kiwi orchard during the irrigation period was calculated based on garden area and other relevant parameters, ensuring accurate irrigation planning. Using the calculated net water requirements and meteorological data, the necessary pumping power was determined, leading to the design of a hybrid wind-solar irrigation system. An environmental impact assessment estimated a significant reduction in CO2 emissions over a 25-year period. Additionally, a life-cycle cost analysis demonstrated that the hybrid irrigation system would incur only 60% of the total cost of a conventional system over the same period, highlighting its economic feasibility.

A quality control scheme for solar irradiance measurements on facades in urban environments

A quality control scheme for solar irradiance measurements on facades in urban environments

Reconstruction of High-Resolution Solar Spectral Irradiance Based on Residual Channel Attention Networks

The accurate measurement of high-resolution solar spectral irradiance (SSI) and its variations at the top of the atmosphere is crucial for solar physics, the Earth’s climate, and the in-orbit calibration of optical satellites. However, existing space-based solar spectral irradiance instruments achieve high-precision SSI measurements at the cost of spectral resolution, which falls short of meeting the requirements for identifying fine solar spectral features. Therefore, this paper proposes a new method for reconstructing high-resolution solar spectral irradiance based on a residual channel attention network. This method considers the stability of SSI spectral features and employs residual channel attention blocks to enhance the expression ability of key features, achieving the high-accuracy reconstruction of spectral features. Additionally, to address the issue of excessively large output features from the residual channel attention blocks, a scaling coefficient adjustment network block is introduced to achieve the high-accuracy reconstruction of spectral absolute values. Finally, the proposed method is validated using the measured SSI dataset from SCIAMACHY on Envisat-1 and the simulated dataset from TSIS-1 SIM. The validation results show that, compared to existing scaling coefficient adjustment algorithms, the proposed method achieves single-spectrum super-resolution reconstruction without relying on external data, with a Mean Absolute Percentage Error (MAPE) of 0.0302% for the reconstructed spectra based on the dataset. The proposed method achieves higher-resolution reconstruction results while ensuring the accuracy of SSI.

Solar Ultraviolet Radiation Exposure Among Opencast Miners in Namibia with the Use of Electronic Dosimeters: A Feasibility Study.

Importance: The lack of information on exposure of opencast mineworkers to solar ultraviolet radiation, a group I carcinogen, was addressed. The feasibility of using electronic dosimeters in the determination of exposure to solar ultraviolet radiation was investigated. Objective: The objective of the study was to determine the feasibility of measuring the occupational exposure of opencast mineworkers to solar ultraviolet radiation using electronic dosimeters. Design: The study followed a cross‑sectional design. Setting: Measurements were carried out at two opencast diamond mining operations hereafter referred to as site A and B, located in the Karas region of Namibia. Participants: Workers from all four outdoor occupations (bedrock, engineering, metallurgy and security) were recruited to participate in the study. Measurements: The study was conducted over four days at each site during winter (site A: 28 June to 4 July 2018 and site B: 6-11 July 2018) in the Karas region of Namibia with 28 consenting workers taking part. The AlGaN photodiode‑based electronic dosimeters were worn above clothing on the dorsal wrists (one) and two placed on the horizontal, unshaded area from 08:00 to 16:00 for the measurement of personal and ambient solar ultraviolet radiation, respectively. Historical meteorological data for the measurement period were obtained from Solcast and Ozone Monitoring Instrument (OMI) NASA. Results: Overall, clear skies and surface reflectivity of 0.19 were observed for both study sites. The mean ultraviolet indices were 2.43 (0.06-4.51) and 2.24 (0.09-4.88) for site A and B, respectively. Findings of valid measurements from nine participants showed the mean total daily personal solar ultraviolet radiation exposure of 1.9 ± 1.0 (1.01-1.57) standard erythemal dose (SED) for site A and 3.4 ± 2.6 (3.39-7.28) SED for site B. Conclusions and Relevance: Personal solar ultraviolet radiation exposure above the occupational exposure limit (OEL) demonstrated the need to include the winter season in planning for protective measures for skin and eyes, since workers are at risk of excessive exposure to solar ultraviolet radiation.

Solar-optical and thermal behavior of photochromic glazing: Small-scale testing under real sky conditions

The poor performance of conventional building glazing, which is usually responsible for large climatization needs and glare problems, has been promoting the development of innovative smart glazing technologies with an improved performance. Photochromic glazing, a type of smart glazing, exhibits a dynamic behavior by darkening/bleaching in reaction to the presence/absence of solar radiation. The aim of this study is to evaluate the thermal and solar-optical behavior of a photochromic filmed clear glazing, against the same glazing without film, through experimental tests. The transmittance and reflectance spectra of the glazing solutions were initially measured with a spectrophotometer. Then two small-scale models were used to assess the behavior of the glazing solutions under real sky conditions (clear and overcast). The thermal behavior was assessed through air and surface temperature measurements. The solar-optical behavior was investigated through solar radiation and illuminance measurements, which were also used to compute the solar and visible transmittance of the glazing systems, respectively. The dynamic behavior of the photochromic film resulted on a reduction of 14 % of the interior temperature. Interior illuminance and irradiance levels were significantly reduced with the film, corresponding to 10–50 % and 15–35 % visible and solar transmittance values of the photochromic glazing, respectively.

Reconstruction of the Total Solar Irradiance During the Last Millennium

Solar irradiance variations across various timescales, from minutes to centuries, represent a potential natural driver of past regional and global climate cold phases. To accurately assess the Sun’s effect on climate, particularly during periods of exceptionally low solar activity, known as grand minima, an accurate reconstruction of solar forcing is essential. While direct measurements of the total solar irradiance (TSI) only began in the late 1970s, with the advent of space radiometers, indirect evidence from various historical proxies suggests that the Sun’s magnetic activity has undergone possible significant fluctuations over much longer timescales. Employing diverse and independent methods for TSI reconstruction is essential to gaining a comprehensive understanding of this issue. This study employs a semi-empirical model to reconstruct TSI over the past millennium. Our approach uses an estimated open solar magnetic field (F o ), derived from cosmogenic isotope data, as a proxy for solar activity. We reconstruct the cyclic variations of TSI, due to the solar surface magnetic features, by correlating F o with the parameter of active region functional form. We obtain the long-term TSI trend by applying the empirical mode decomposition algorithm to the reconstructed F o to filter out the 11 yr and 22 yr solar variability. We prepare a reconstructed TSI record, spanning 971 to 2020 CE. The estimated departure from modern TSI values occurred during the Spörer minimum (around 1400 CE), with a decrease of approximately 2.3 Wm−2. A slightly smaller decline of 2.2 Wm−2 is reported during the Maunder minimum, between 1645 and 1715 CE.

Smartphone Light Sensors as an Innovative Tool for Solar Irradiance Measurements.

In recent years, the teaching of experimental science and engineering has been revolutionized by the integration of smartphone sensors, which are widely used by a large portion of the population. Concurrently, interest in solar energy has surged. This raises the important question of how smartphone sensors can be harnessed to incorporate solar energy studies into undergraduate education. We provide comprehensive guidelines for using smartphone sensors in various conditions, along with detailed instructions on how to calibrate them with widely accessible clear-sky satellite data. This smartphone-based method is also compared with professional reference measurements to ensure consistency. This experiment can be easily conducted with most smartphones, basic materials, and a clear, open location over a few hours (methods). The findings demonstrate that smartphones, combined with simple resources, can accurately measure solar irradiance and support experiments on solar radiation physics, atmospheric interactions, and variations in solar energy across locations, cloud cover, and time scales. This approach provides a practical and accessible tool for studying solar energy, offering an innovative and engaging method for measuring solar resources.

An enhanced method for reconstruction of full SIF spectrum for near-ground measurements

Recently the applications of remotely sensed Solar-Induced chlorophyll Fluorescence (SIF) in the study of photosynthesis, stress conditions, and gross primary production have increased significantly. The full SIF spectrum spans over a spectral region of 650 ∼ 850 nm with two characteristic peaks around 685 nm and 740 nm. Over recent decades, many retrieval algorithms have been developed to estimate SIF at Top-Of-Canopy (TOC) using in-situ measurements of solar irradiance and canopy radiance spectra. Although the majority of retrieval methods retrieve SIF at a narrow spectral window, there exists a potential for retrieval of SIF in the full emission spectrum. Moreover, solar irradiance and canopy radiance spectra should ideally be measured at the same time but are usually measured sequentially with a certain time lag, raising potential errors in SIF retrieval. In this study, an enhanced retrieval algorithm of the full SIF spectrum at TOC is proposed. The proposed algorithm attempts to minimize the errors owing to time mismatch in measurements of solar irradiance and canopy radiance spectra. As an improvement to the previous algorithm (advanced Fluorescence Spectrum Reconstruction, aFSR), this proposed algorithm (aFSR-SVE) models the SIF-free contribution with principal components using the singular value decomposition technique. The optimal parameter settings in the forward model were determined for the experimental data collected by spectrometers used in the study. Firstly, the proposed algorithm was used to reconstruct full SIF spectrum for simulated data. The results were compared with known reference SIF values. After achieving satisfying results from simulated data, the proposed algorithm was compared with retrievals from established algorithms using experimental data. The results show improved SIF retrieval accuracy, without the need to simultaneously measure solar irradiance and canopy radiance spectra. The retrieval values comply with the results of previous algorithms in terms of spectral shape, diurnal trend, and temporal variations. The induced errors in SIF retrievals due to non-simultaneous measurements of solar irradiance and canopy radiance spectra were also investigated and the proposed algorithm was found to be less prone to such errors. Hence, the proposed algorithm is an improvement in reconstructing the full SIF spectrum with near-ground measurements. With the help of the proposed algorithm, field measurements using sequential systems and automated measurements of multiple targets can be performed effectively as it relaxes the requirement of concurrent measurement of solar irradiance and canopy radiance spectra. For future work, the applicability of this method can be investigated under more variable illumination conditions, like high cirrus clouds, passing clouds or persistent thin clouds.

Experimental investigation of a nano coating efficiency for dust mitigation on photovoltaic panels in harsh climatic conditions

Dust accumulation on photovoltaic (PV) panels in arid regions diminishes solar energy absorption and panel efficiency. In this study, the effectiveness of a self-cleaning nano-coating thin film is evaluated in reducing dust accumulation and improving PV Panel efficiency. Surface morphology and elemental analysis of the nano-coating and dust are conducted. Continuous measurements of solar irradiances and ambient temperature have been recorded. SEM analysis of dust revealed irregularly shaped micron-sized particles with potential adhesive properties, causing shading effects on the PV panel surface. Conversely, the coating particles exhibited a uniform, spherical shape, suggesting effective prevention of dust adhesion. Solar irradiance ranged from 120 W/m² to a peak of 720 W/m² at noon. Application of the self-cleaning nano-coating thin film consistently increased short circuit current (Isc), with the coated panel averaging 2.8 A, which is 64.7% higher than the uncoated panel’s 1.7 A. The power output of the coated panel ranged from 7 W to 38 W, with an average of approximately 24.75 W, whereas the uncoated panel exhibited a power output between 3 W and 23 W, averaging around 14 W. These findings highlight the substantial potential of nano-coating for effective dust mitigation, particularly in dusty environments, thus enhancing PV system reliability.

Ensemble Learning Algorithms for Solar Radiation Prediction in Santo Domingo: Measurements and Evaluation

Solar radiation is a fundamental parameter for solar photovoltaic (PV) technology. Reliable solar radiation prediction has become valuable for designing solar PV systems, guaranteeing their performance, operational efficiency, safety in operations, grid dispatchment, and financial planning. However, high quality ground-based solar radiation measurements are scarce, especially for very short-term time horizons. Most existing studies trained machine learning (ML) models using datasets with time horizons of 1 h or 1 day, whereas very few studies reported using a dataset with a 1 min time horizon. In this study, a comprehensive evaluation of nine ensemble learning algorithms (ELAs) was performed to estimate solar radiation in Santo Domingo with a 1 min time horizon dataset, collected from a local weather station. The ensemble learning models evaluated included seven homogeneous ensembles: Random Forest (RF), Extra Tree (ET), adaptive gradient boosting (AGB), gradient boosting (GB), extreme gradient boosting (XGB), light gradient boosting (LGBM), histogram-based gradient boosting (HGB); and two heterogeneous ensembles: voting and stacking. RF, ET, GB, and HGB were combined to develop voting and stacking ensembles, with linear regression (LR) being adopted in the second layer of the stacking ensemble. Six technical metrics, including mean squared error (MSE), root mean squared error (RMSE), relative root mean squared error (rRMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and coefficient of determination (R2), were used as criteria to determine the prediction quality of the developed ensemble algorithms. A comparison of the results indicates that the HGB algorithm offers superior prediction performance among the homogeneous ensemble learning models, while overall, the stacking ensemble provides the best accuracy, with metric values of MSE = 3218.27, RMSE = 56.73, rRMSE = 12.700, MAE = 29.87, MAPE = 10.60, and R2 = 0.964.

Estimation of Aerosol Characteristics from Broadband Solar Radiation Measurements Carried Out in Southern Algeria

Aerosols in the atmosphere significantly reduce the solar radiation reaching the Earth’s surface through scattering and absorption processes. Knowing their properties becomes essential when we are interested in measuring solar radiation at a given location on the ground. The commonly used parameters that characterize their effects are the Aerosol Optical Depth τ, the Angstrom exponent α, and the Angstrom coefficient β. One method for estimating these parameters is to fit ground-based measurements of clear-sky direct solar radiation using a model on which it depends. However, the choice of model depends on its suitability to the atmospheric conditions of the site considered. Eleven empirical solar radiation models depending on α and β were thus chosen and tested with solar radiation measurements recorded between 2005 and 2014 in Tamanrasset in southern Algeria. The results obtained were compared to measurements made with the AERONET solar photometer on the same site during the same period. Among the 11 models chosen, the best performing ones are REST2 and CPCR2. They proved to be the best suited to estimate β with approximately the same RMSE of 0.05 and a correlation coefficient R with respect to AERONET of 0.95. The results also highlighted good performances of these models for the estimation of τ with an RMSE of 0.05 and 0.04, and an R of 0.95 and 0.96, respectively. The values of α obtained from the fitting of these models were, however, less good, with R around 0.38. Additional treatments based on a Recurrent Neural Network (RNN) were necessary to improve its estimation. They provided promising results showing a significant improvement in α estimates with R reaching 0.7 when referring to AERONET data. Furthermore, this parameter made it possible to identify different types of aerosols in Tamanrasset such as the presence of maritime, dust, and mixed aerosols representing, respectively, 31.21%, 3.25%, and 65.54%, proportions calculated over the entire period studied. The seasonal analysis showed that maritime aerosols are predominant in the winter in Tamanrasset but decrease with the seasons to reach a minimum in the summer (JJA). Dust aerosols appear in February and persist mainly in the spring (MAM) and summer (JJA), then disappear in September. These results are also consistent with those obtained from AERONET.

Effect of the dimensions (width and radius) of the shading ring on the measurement of diffuse solar irradiance with the MEO shading ring measurement method

Diffuse irradiance was monitored by the Melo–Escobedo–Oliveira shading ring measurement method (MEO method) and requires the application of two corrections: one geometric and one atmospheric. The latter occurs from the interaction of radiation with atmospheric constituents and is known as circumsolar radiation, which is also obstructed by the ring. Thus, the objective of this work is to verify if geometrical aspects of the shading ring, such as width and radius, interfere in the quantification of these atmospheric corrections. Two Kipp & Zonen pyranometers were used to monitor the diffuse irradiance, one with 10/40 cm (width/radius) and one with 5/20 cm (width/radius). The values measured by the rings were compared with the diffuse irradiance obtained by the difference method. Studies were carried out under all atmospheric sky cover conditions: cloudy sky, partially cloudy sky, and clear sky. The results showed the highest atmospheric corrections were obtained for the clear sky coverage. Despite the two assemblies having the same width/radius ratio of 0.250, the assembly with the largest radius showed the lowest atmospheric correction. The application of atmospheric corrections is conditioned to the geometrical aspects of the ring, mainly the radius, to guarantee the quality of measurements carried out by the shading ring method.

The cooling effect of vertical greening systems using solar radiation measurement

The cooling effect of vertical greening systems using solar radiation measurement

Multivariate Imputation Chained Equation on Solar Radiation in Automatic Weather Station

Solar radiation is one of the crucial weather observation variables Its variable has a role in renewable energy solutions, agriculture, meteorology, and hydrology. AWS is one of instrument that use to observing weather especially solar radiation. AWS has a pyranometer sensor used to measure solar radiation. Unfortunately, the instrument has problem like the igh cost of supplying, installing, maintaining, and calibrating the equipment. Due to this, there is a lot of empty data, and the actual data cannot be properly measured. Imputation of solar radiation data using MICE algorithm can be solution. This study using BLR, NRR and RFR estimator to estimating solar radiation data. AWS Staklim Banten as target and other AWS as input. The period from January 1, 2018 - February 12, 2024. The performance evaluation of the solar radiation imputation estimator is still according to WMO operational requirements for solar radiation measurements, which can be seen from the resulting MAPE value < 8%.

Evaluating the representation of Arctic cirrus solar radiative effects in the Integrated Forecasting System with airborne measurements

Abstract. In two case studies, airborne measurements of broadband solar irradiances above and below Arctic cirrus are compared to simulations of the Integrated Forecasting System (IFS) operated by the European Centre for Medium-Range Weather Forecasts (ECMWF) using offline runs of ECMWF's operational radiation scheme, “ecRad”. Furthermore, independent of the solar irradiances, cirrus properties are derived from collocated airborne active remote sensing observations to evaluate the optical and microphysical parameterizations in ecRad. The data were collected in the central Arctic over sea ice (81–90° N) with instrumentation installed aboard the High Altitude LOng range research aircraft (HALO) during a campaign in March and April 2022. Among others, the HALO instrumentation included upward- and downward-looking pyranometers to measure broadband solar irradiances, a cloud radar, and a multi-wavelength water vapour differential absorption lidar. Extended horizontal flight legs above and below single-layer cirrus were performed. The solar radiation measurements are used to evaluate ecRad in two case studies of optically thin and thick cirrus, with an average transmissivity of 0.9 and 0.6, respectively. Different ice optics parameterizations optionally available in ecRad are applied to test the match between simulation and measurements. Furthermore, the IFS-predicted ice water content and ice effective radius are replaced by values retrieved with the radar and lidar. The choice of ice optics parameterizations does not significantly improve the model–measurement agreement. However, introducing the retrieved ice microphysical properties brings measured and modelled irradiances in closer agreement for the optically thin cirrus, while the optically thick cirrus case is simulated as too thick. It is concluded that the ice water content simulated by the IFS is realistic and that the mismatch between observed and simulated solar irradiances mostly originates from the assumed or parameterized ice effective radius.

Solar Radiation Measurement Tools and Their Impact on In Situ Testing—A Portuguese Case Study

Accurate knowledge of solar radiation data or its estimation is crucial to maximize the benefits derived from the Sun. In this context, many sectors are re-evaluating their investments and plans to increase profit margins in line with sustainable development based on knowledge and estimation of solar radiation. This scenario has drawn the attention of researchers to the estimation and measurement of solar radiation with a low level of error. Various types of models, such as empirical models, time series, artificial intelligence algorithms and hybrid models, for estimating and measuring solar radiation have been continuously developed in the literature. In general, these models require atmospheric, geographical, climatic and historical solar radiation data from a specific region for accurate estimation. Each analysis model has its advantages and disadvantages when it comes to estimating solar radiation and, depending on the model, the results for one region may be better or worse than for another. Furthermore, it has been observed that an input parameter that significantly improves the model’s performance in one region can make it difficult to succeed in another. The research gaps, challenges and future directions in terms of solar radiation estimation have substantial impacts, but regardless of the model, in situ measurements and commercially available equipment consistently influence solar radiation calculations and, subsequently, simulations or estimates. This article aims to exemplify, through a case study in a multi-family residential building located in Viana do Castelo, a city in the north of Portugal, the difficulties of capturing the spectrum of radiations that make up the total radiation that reaches the measuring equipment or site. Three pieces of equipment are used—a silicon pyranometer, a thermopile pyranometer and a solar meter—on the same day, in the same place, under the same meteorological conditions and with the same measurement method. It is found that the thermopile pyranometer has superior behavior, as it does not oscillate as much with external factors such as the ambient temperature, which influence the other two pieces of equipment. However, due to the different assumptions of the measurement models, the various components of the measurement site make it difficult to obtain the most accurate and reliable results in most studies. Despite the advantages of each model, measurement models have gained prominence in terms of the ease of use and low operating costs rather than the rigor of their results.

Analysis and Development of an IoT System for an Agrivoltaics Plant

This article illustrates the development of SolarFertigation (SF), an IoT (Internet of Things) solution for precision agriculture. Contrary to similar systems on the market, SolarFertigation can monitor and optimize fertigation autonomously, based on the analysis of data collected through the cloud. The system is made up of two main components: the central unit, which enables the precise deployment and distribution of water and fertilizers in different areas of the agricultural field, and the sensor node, which oversees collecting environmental and soil data. This article delves into the evolution of the system, focusing on structural and architectural changes to develop an infrastructure suitable for implementing a predictive model based on artificial intelligence and big data. Aspects concerning both the sensor node, such as energy management, accuracy of solar radiation readings, and qualitative soil moisture measurements, as well as implementations to the hydraulic system and the control and monitoring system of the central unit, are explored. This article provides an overview of the results obtained from solar radiation and soil moisture measurements. In addition, the results of an experimental campaign, in which 300 salad plants were grown using the SolarFertigation system in a photovoltaic field, are presented. This study demonstrated the effectiveness and applicability of the system under real-world conditions and highlighted its potential in optimizing resources and increasing agricultural productivity, especially in agrivoltaic settings.

In situ performance evaluation of a solar water heating system for a hospital laundry in the Sahel

There is a limited number of empirical studies on the actual energy output of solar water heating systems (SWHSs). In the Sahel, where solar potential is abundant, the transition to sustainable energy solutions requires comprehensive evaluations of SWHSs, including their economic viability. Such assessments are crucial for informed decision-making by stakeholders and for facilitating the widespread adoption of SWHSs, including their integration into industrial processes. This paper presents a year-round experimental study assessing the real-world performance and economic viability of a SWHS integrated into a hospital laundry in Ouagadougou, Burkina Faso. The primary aim of the study is to analyse the practical performance of the integrated collector storage (ICS) SWHS and evaluate its economic viability. The performance of the ICS SWHS is monitored over the course of a year. Data collection included measurements of solar irradiation, ambient temperature, inlet and outlet water temperatures, and energy output of the SWHS. Economic assessments considered factors such as installation costs, energy savings, and payback periods. Environmental implications were evaluated through the estimation of avoided CO2 emissions. The ICS SWHS achieved an efficiency of 38 % and a solar fraction of 17 %, resulting in approximately 1.3 t of avoided CO2 emissions annually. Economic assessments revealed extended payback periods, leading to exploration of alternatives. Subsequently, a water-in-glass evacuated tube collector (ETC) system, deemed more cost-effective, was selected and it indicated superior energy production. Preliminary results suggest compelling payback periods for the ETC system, ranging from 3.1 to 4.5 years under realistic scenarios. The study underscores the significance of practical experimentation, appropriate technology selection, and improved market regulations for informed decision-making. SWHSs present a promising avenue for sustainable energy solutions in the Sahelian region and beyond, offering both economic benefits and environmental impact.