Direct Normal Irradiance Research Articles

Techno-economic analysis and optimization of 50 MWe linear fresnel reflector solar thermal power plant for different climatic conditions

The climate change crisis is primarily associated with carbon dioxide emissions from fossil fuel-based electricity generation, which significantly contribute to the greenhouse gas effect. The implementation of renewable energy technologies can mitigate environmental impacts and promote a sustainable future. This study aimed to conduct a techno-economic feasibility analysis and optimize performance parameters for a 50 MWe capacity Linear Fresnel Reflector (LFR) concentrated solar power plant for nine stations under various climatic conditions. The analysis was conducted based on Levelized Cost of Electricity (LCOE) and Capacity Factor (CF) to select a suitable Heat Transfer Fluid (HTF) for each station, by varying Solar Multiple (SM) from 1.0 to 6.0 and adjusting Thermal Energy Storage (TES) hours from four to sixteen. The HTFs selected for economically feasible projects at different stations were Hitec Solar Salt, Hitec, and Therminol VP-1. The combination of SM and TES hours was optimized for economic feasibility, targeting a minimum CF of 36 % and a maximum LCOE of 13.0 ¢/kWh. The optimum SM and TES hours were found to range from 2.0 to 5.8 and from six to thirteen, respectively. An LCOE of less than 7.5 ¢/kWh and a CF of more than 80 % was achieved for two stations with SM of 6.0 and TES of 16 h using Therminol VP-1. Stations with annual mean direct normal irradiance values higher than 1500 kWh/m2 and clearness index values over 0.58 are suitable for commercial power plants. This study contributes to achieving the United Nation's sustainable development goals by promoting the use of renewable energy technologies.

Optimization study of a high-proportion of solar tower aided coal-fired power generation system integrated with thermal energy storage

Solar aided coal-fired power generation technologies have proven to be effective in reducing fossil fuel consumption and greenhouse gas emission. In this research, a high-proportion solar tower aided coal-fired power generation system integrated with thermal energy storage system is proposed. According to the constraint conditions, the integration scheme with the highest solar coupling capacity is obtained, and its thermodynamic, economic and environmental performances are researched. The results indicate that the solar coupling capacity that can be accommodated by the 660 MW coal-fired unit after parameter optimization is 339.532 MWth. As the load rate decreases, the power generated from solar and solar to electricity efficiency gradually decreases while the proportion of power from solar increases. The proportion of power from solar reaches a maximum of 24.28 % at 50 % load rate. The effects of different thermal energy storage hours on the levelized cost of electricity are investigated, and the results show that the lowest levelized cost of electricity is only 41.62 $/MWh in the high-level direct normal irradiance area. The new system can reduce about 272,921 tons of CO2 emissions in a year at 100 % load rate. This study contributes to further promoting the development of a high-proportion solar aided coal-fired power generation system and realizing the low-carbon transition of coal-fired power generation industry.

Advanced Controllers for Heat Transfer Fluid Mass Flow Rate Control in Solar Tower Receivers

Efficient control strategies for managing the mass flow rate (MFR) of heat transfer fluids (HTF) during cloud transients in Solar Tower receivers play a pivotal role in optimizing plant profitability and receiver durability. This study focuses on the performance and durability of Solar Tower receivers during cloud transients. It evaluates adaptive feedback and feedforward control methods, which adjust the flow rate of heat transfer fluids based on real-time measurements of direct normal irradiance (DNI), receiver outlet and receiver panel outlet temperatures. The effectiveness of an aggressive all-sky and conservative clear-sky control strategy is explored against a conventional PI controller, emphasizing energy efficiency and receiver longevity. Simulations using a thermal Modelica model resembling a 100 MWel Crescent Dunes-like solar tower plant reveal that both advanced controllers provide precise setpoint tracking, while the PI controller struggles. The conservative controller which has a cloud standby mode prevents overheating during cloud transients by using a clear sky mass flow rate, while the aggressive controller uses the receiver panel outlet temperatures to correct for upstream tube temperature variations allowing for fast tracking correction and disturbance rejection, albeit with slight overshoots. Furthermore, the controllers significantly decrease the creep-fatigue damage accumulated in the receiver panels during cloudy days, due to limiting the increase in wall temperature spikes when cloud events end. Overall, this study underscores the pivotal role of HTF mass flow rate control systems in influencing receiver system failure modes and longevity and offers a new tool in controller design and operation assessment.

Vacuum Loss Detection of PTC in CSP Plants via Temperature-Sensors

The efficient operation of a solar field is an essential factor for the commercial operation of a concentrating solar power (CSP) plant. In addition to predictive control for the highest possible constant outlet temperature at high mass flow, efficient operation also includes early detection of defective components and heat losses. This work presents a method for non-invasive heat loss detection as a strong indication for vacuum losses, based on measured operational data of Andasol III, an operating 50 MW parabolic trough collector (PTC) plant located in southern Spain. To detect vacuum losses via this method, mass flow rate and temperature reduction are determined separately for each individual loop via the analysis of a short-term temperature rise of the heat transfer fluid (HTF) during preheating. While the temperature reduction was measured directly, the mass flow was determined via the thermal time-of-flight (ToF) method using the same installed temperature sensors. By measuring thermal step responses during the preheating of the solar field at nighttime operation, the influence of fluctuating direct normal irradiance (DNI), misalignment of the absorber tubes and an offset in collector focus was circumvented. In the scope of the presented work, single loops were detected, which show a higher heat loss at lower mass flow rate and therefore have an increased probability of a higher vacuum loss. Better localization and early detection of these vacuum losses would allow the corresponding absorber tubes to be renewed at the economically and environmentally best time, improving the efficiency of the solar field and thus the entire CSP plant.

Irradiance separation model parameter estimation from historical cloud cover statistical properties

Irradiance separation models allow the decomposition of Global Horizontal Irradiance into Diffuse Horizontal and Direct Normal Irradiances. These models need fitting to the irradiance characteristics of the location of interest using locally measured ground data. For locations that only measure Global Horizontal Irradiance, current state of the art establishes the use of parameters obtained for another location that measures the three components, with similar climate characteristics. Nevertheless, this results in a lack of localized character for estimates and requires fitting model parameters for all possible climates, which can be infeasible given data availability. This work presents a novel approach based on the hypothesis that the separation model's parameters are a function of the statistical properties of satellite-derived cloud cover estimates. The proposed methodology was evaluated in 23 sites covering all main Köppen-Geiger climatic types and different cloud coverage properties using the Boland-Ridley-Lauret diffuse fraction model. The model performs similarly as locally adjusting the model, with Root Mean Square Errors of 0.087–0.15 diffuse fraction units versus 0.077–0.127 for locally optimized parameters, and offers adequate performance across climates and cloud characteristics. These results encourage future research by generalizing parameter estimation for other diffuse fraction models. The main applications for this research are the estimation of irradiance components where no local data is available for model fitting and the enhancement or complementarity of satellite estimates of surface irradiance. Furthermore, it allows the estimation of missing irradiance components due to equipment failure in locations with insufficient data for a representative, locally adapted model.

Energy, exergy, economic, and environmental analyses and optimization of a multigeneration system considering high-temperature island environment

Renewable energy based multigeneration systems help satisfy the diverse demand for marine resources exploration in off-grid island area, where the storage of fluctuating renewable energy for continuous power supply becomes necessary. Therefore, this paper proposes a solar-driven multigeneration system for island environment integrated with energy storage and production of electricity, cooling, heating, and freshwater. The system comprises an ejector power subsystem, a multiple-effect distillation subsystem, and a CO2 binary mixture-based compressed gas energy storage subsystem. The system performance from the perspectives of energy, exergy, economics, and environment, as well as the impact on performance of the working fluid and several key system parameters, are investigated in this paper. According to the results, an increase in the mass fraction of organic in the CO2 mixture leads to an improvement in system energy efficiency and exergy density at the cost of lower system power efficiency. Increasing the high-pressure tank pressure enhances system performance except for system power efficiency. Increased low-pressure tank pressure leads to improved system energy efficiency and exergy density, accompanied by lower system power efficiency and exergy efficiency. When the ambient temperature increases from 298 K to 303 K, the system energy efficiency noticeably decreases, whereas an increase in direct normal irradiance improves various system performance indicators. Among several mixtures, CO2/R32 mixture was chosen for further analysis and optimization for its wider operating range with R32 mass fraction and better system performance. The optimal operating point had system energy efficiency, exergy density, and modified levelized cost of energy of 1.281, 22.216 kWh/m3, and 0.131 $/kWh, respectively. The proposed system in this research is proven to be a novel technical solution to meet the diverse energy demands on unique island environments.

Hybrid models for direct normal irradiance forecasting: a case study of Ghardaia zone (Algeria)

Hybrid models for direct normal irradiance forecasting: a case study of Ghardaia zone (Algeria)

Soiling, Adhesion, and Surface Characterization of Concentrated Solar Power Reflectors: Insights and Challenges in the MENA Region

Desert environments are prime locations for concentrated solar power (CSP) applications due to abundant direct normal irradiance. Despite this advantage, the accumulation and adhesion of dust on CSP mirror surfaces present significant challenges to plant efficiency. This paper comprehensively explores soiling phenomena and dust adhesion mechanisms, complemented by advanced measurement techniques tailored for CSP reflector mirrors. By elucidating the factors influencing dust accumulation and delving into the thermodynamics of self-cleaning coatings, alongside an analysis of various mirror materials, this study aims to enrich our understanding of soiling in CSP systems. This study aims to provide valuable insights that will help develop strategies to reduce dust-related efficiency losses in CSP plants, ultimately supporting the development of more reliable and sustainable solar energy solutions for the MENA region.

Regional validation of the solar irradiance tool SolaRes in clear-sky conditions, with a focus on the aerosol module

Abstract. The Solar Resource estimate (SolaRes) tool based on the Speed-up Monte Carlo Advanced Radiative Transfer code using GPU (SMART-G) has the ambition to fulfil both research and industrial applications by providing accurate, precise, and high-time-resolution simulations of the solar resource. We investigate the capacity of SolaRes to reproduce the radiation field, relying on 2 years of ground-based measurements by pyrheliometers and pyranometers acquired in northern France (Lille and Palaiseau). Our main objective is to provide, as a first step in clear-sky conditions, a thorough regional validation of SolaRes, allowing us to investigate aerosol impacts on solar resource. We perform comparisons between SolaRes-simulated and clear-sky-measured global horizontal irradiance (GHI), direct normal irradiance (DNI), diffuse horizontal irradiance (DifHI), and global and diffuse irradiance on a tilted plane (GTI, DifTI), and we even consider the circumsolar contributions. Using spectral aerosol optical thickness (AOT) data sets as input, which are delivered by the AErosol RObotic NETwork (AERONET) and the Copernicus Atmosphere Monitoring Service (CAMS), we examine the influence of aerosol input data sets in SolaRes on the comparison scores. Two aerosol models are mixed to compute aerosol optical properties. We also perform a sensitivity study on the aerosol parametrisation and investigate the influence of applying more or less strict cloud-screening methods to derive ground-based proof data sets of clear-sky moments. SolaRes is validated with the (relative) root mean square difference (RMSD) in GHI as low as 1 % and a negligible mean bias difference (MBD). The impact of the cloud-screening method in GHI is 0.5 % of RMSD and 0.3 % of MBD. SolaRes also estimates the circumsolar contribution, which improves MBD in DNI and DifHI by 1 % and 4 %, respectively, and RMSD by ∼ 0.5 %. MBD in DNI is around −1 % and RMSD around 2 %, and MBD in DifHI is 2 % and RMSD around 9 %. RMSD and MBD in both DNI and DifHI are larger than in GHI because they are more sensitive to the aerosol and surface properties. DifTI measured on a vertical plane facing south is simulated by SolaRes with an RMSD of 8 %, comparable to that obtained for DifHI. Our results suggest a strong influence of reflection by not only ground surface but also surrounding buildings. The sensitivity studies on the aerosol parameterisation show that the spectral AOT contains enough information for high performance in DNI simulations, with low influence of the choice of the aerosol models on the RMSD. However, choosing a model with smaller aerosol single scattering albedo significantly decreases SolaRes DifHI and GHI. The best combination in Lille and Palaiseau consists of continental clean mixed with desert dust. Also, complementary information on angular scattering and aerosol absorption provided by the AERONET-inverted model further improves simulated clear-sky GHI by reducing RMSD by ∼ 0.5 % and MBD by ∼ 0.8 %. Eventually, the choice of the data source has a significant influence. Indeed, using CAMS AOT instead of AERONET AOT increases the RMSD in GHI by ∼ 1 % and MBD by ∼ 0.4 % and RMSD in DNI by 5 %. The RMSD in GHI remains slightly smaller than state-of-the-art methods.

Enhancing the estimation of direct normal irradiance for six climate zones through machine learning models

The evaluation of solar radiation is essential for large-scale solar energy systems, as assessing economic feasibility early on depends on accurate solar radiation data. Accurate sensors are needed to characterize the solar resource. Due to a scarcity of solar radiation data, numerical models are commonly used to estimate solar radiation components using meteorological variables that are simple or cheap to measure. In recent years, the use of machine learning (ML) algorithms has gained significant popularity in the estimation of solar radiation components. In this study it is proposed a post-processing approach using the separation model outcomes as input variables to estimate the diffuse fraction. Three ML models are employed (XGBoost, Random Forest, and Multilayer Perceptron) to boost the accuracy in terms of three statistical indicators: nRMSE, nMBE, and R2. The employed technique takes a distinctive approach by using reference stations to train the machine learning models and, afterward, make the assessment at the site under study. The results show an improvement in terms of precision of individual separation model outcomes. Thus, the proposed methodology may serve as a reliable approach for estimating solar radiation components in cases where historical data for a specific place of interest is not accessible.

On the characterization of Cloud occurrence and its impact on solar radiation in Mbour, Senegal

The objective of this study is to evaluate the clouds seasonal occurrence characteristics, and to estimate their impact on solar radiation in Mbour, Senegal, West Africa. Here, we use datasets from various sources including: i) observations from the Clouds and Earth's Radiant Energy System satellite sensors, ii) in situ shortwave radiation measurement obtained from the Mbour station, and iii) the outgoing longwave radiation (OLR) obtained from the National Centers for Environmental Prediction reanalysis data. Results show a marked seasonality, associated with high spatial variation in terms of cloud occurrence over Senegal. The maximum cloud occurrences are observed during the wet summer season (June–October), whilst the minimum cloud occurrences are recorded during the long-dry season from November to May. During the monsoon season the cloud activity becomes more intense with a total cloud cover of about 80%, a cloud optical depth of around 7, and a high convective activity illustrated by a low OLR (below 240 W/m2). Likewise, across Senegal a strong north-south gradient of the cloud characteristics is observed. Based on quantitative comparison between cloud occurrence and radiation measurement, results show an important seasonal impact on available solar potential in Mbour. Conversely to the cloud occurrence, the maximum of both direct normal and global solar potentials is recorded during the dry season, coinciding with the period with clean sky. An investigation of the cloud influence on solar radiation on selected study cases indicates a decrease of 60% (80%) for the total (direct normal) radiation during the peak of the summer monsoon season.

A multi-generation system with integrated solar energy, combining energy storage, cooling, heat, and hydrogen production functionalities: Mathematical model and thermo-economic analysis

Increasing the proportion of renewable energy is of paramount importance for all countries in the world. In this work, a novel multi-generation system is designed to fully utilize solar energy, which includes a photovoltaic/thermal subsystem (PV/T), an absorption refrigeration cycle (ARC), a proton-exchange membrane (PEM) electrolysis, and a promising pumped thermal electricity storage (PTES) energy storage subsystem, which can simultaneously achieve the purposes of refrigeration, hydrogen production, heat production, and energy storage. Meanwhile, the solar radiation data of Wuwei City, Gansu Province, China for the year 2022 are selected for the study. According to different seasons, the thermodynamic and thermo-economic performances of the combined power, heat and hydrogen production (CPHH) mode operated in spring, autumn, winter, and the combined power, cooling and hydrogen production (CPCH) mode operated in summer are investigated, and multi-objective optimization is conducted. The results indicate that the direct normal irradiance (DNI) of solar, the area of PV/T, the thermal storage temperature of the PTES subsystem, and the pinch point temperature difference significantly affect the total energy efficiency, total exergy efficiency, and total product unit cost of the system. The multi-objective optimization results show that the optimal solutions of total energy efficiency and total product unit cost of the system are 85.90 %, 24.25 $·GJ−1 and 86.97 %, 24.25 $·GJ−1 for the CPHH mode in spring and winter, respectively, and 88.26 % and 22.21 $·GJ−1 for the CPCH mode in summer. This work can provide a valuable reference for the research of multi-generation systems with integrated renewable energy sources.

Thermodynamic analysis of a parabolic trough power plant integrating supercritical carbon dioxide Brayton cycle and direct contact membrane distillation

This research advances current efforts to develop 3rd gen concentrated solar power (CSP) systems, addressing current research and practical implementation gaps. It focuses on key challenges identified by the academic community: advanced power cycles and utilising waste heat effectively to enhance efficiency. This research introduced a novel system comprising a direct parabolic trough with supercritical carbon dioxide (sCO2) Brayton cycle, and a Direct Contact Membrane Distillation (DCMD) desalination system, aiming to overcome these barriers. The methodology entailed developing a mathematical model and conducting thermodynamic analyses to evaluate system efficiencies, the impact on water production, and the number of DCMD units needed under various conditions. The results reveal that both thermal and exergetic efficiencies decline with decreasing direct normal irradiance across all pressure ratios with the optimal efficiency observed at pressure ratios of approximately 3.1 to 3.2 with exergetic efficiency of around 0.383. Higher bulk temperature differences increased water production and reduced need for direct contact membrane distillation units. However, an initial decline and subsequent rise in water production at bulk temperature differences of 10 °C and 20 °C indicates that feed temperature alone does not determine water production capacity. The existence of an inverse correlation between the cycle’s efficiency and water production prompted the introduction of a unifying coefficient, the Integrated Performance Coefficient (IPC), peaking at 50.32 between pressure ratios of 3.1 and 3.2. High bulk feed temperatures combined with low bulk permeate temperatures enhance water production but also increase its vulnerability to variations in direct normal irradiance. Conversely, increased bulk permeate temperatures lessen the effect of direct normal irradiance changes on water production, albeit with a reduced output.

Measuring DNI with a New Radiometer Based on an Optical Fiber and Photodiode.

A new cost-effective radiometer has been designed, built, and tested to measure direct normal solar irradiance (DNI). The proposed instrument for solar irradiance measurement is based on an optical fiber as the light beam collector, a semiconductor photodiode to measure the optical power, and a calibration algorithm to convert the optical power into solar irradiance. The proposed radiometer offers the advantage of separating the measurement point, where the optical fiber collects the solar irradiation, from the place where the optical power is measured. A calibration factor is mandatory because the semiconductor photodiode is only spectrally responsive to a limited part of the spectral irradiance. Experimental tests have been conducted under different conditions to evaluate the performance of the proposed device. The measurements confirm that the proposed instrument performs similarly to the expensive high-accuracy pyrheliometer used as a reference.

Evaluation of Two Satellite Surface Solar Radiation Products in the Urban Region in Beijing, China

Surface solar radiation, as a primary energy source, plays a pivotal role in governing land–atmosphere interactions, thereby influencing radiative, hydrological, and land surface dynamics. Ground-based instrumentation and satellite-based observations represent two fundamental methodologies for acquiring solar radiation information. While ground-based measurements are often limited in availability, high-temporal- and spatial-resolution, gridded satellite-retrieved solar radiation products have been extensively utilized in solar radiation-related studies, despite their inherent uncertainties in accuracy. In this study, we conducted an evaluation of the accuracy of two high-resolution satellite products, namely Himawari-8 (H8) and Moderate Resolution Imaging Spectroradiometer (MODIS), utilizing data from a newly established solar radiation observation system at the Beijing Normal University (BNU) station in Beijing since 2017. The newly acquired measurements facilitated the generation of a firsthand solar radiation dataset comprising three components: Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), and Diffuse Horizontal Irradiance (DHI). Rigorous quality control procedures were applied to the raw minute-level observation data, including tests for missing data, the determination of possible physical limits, the identification of solar tracker malfunctions, and comparison tests (GHI should be equivalent to the sum of DHI and the vertical component of the DNI). Subsequently, accurate minute-level solar radiation observations were obtained spanning from 1 January 2020 to 22 March 2022. The evaluation of H8 and MODIS satellite products against ground-based GHI observations revealed strong correlations with R-squared (R2) values of 0.89 and 0.81, respectively. However, both satellite products exhibited a tendency to overestimate solar radiation, with H8 overestimating by approximately 21.05% and MODIS products by 7.11%. Additionally, solar zenith angles emerged as a factor influencing the accuracy of satellite products. This dataset serves as crucial support for investigations of surface solar radiation variation mechanisms, future energy utilization prospects, environmental conservation efforts, and related studies in urban areas such as Beijing.

Techno-Economic Assessment of Molten Salt-Based Concentrated Solar Power: Case Study of Linear Fresnel Reflector with a Fossil Fuel Backup under Saudi Arabia’s Climate Conditions

Concentrated solar power (CSP) has gained traction for generating electricity at high capacity and meeting base-load energy demands in the energy mix market in a cost-effective manner. The linear Fresnel reflector (LFR) is valued for its cost-effectiveness, reduced capital and operational expenses, and limited land impact compared to alternatives such as the parabolic trough collector (PTC). To this end, the aim of this study is to optimize the operational parameters, such as the solar multiple (SM), thermal energy storage (TES), and fossil fuel (FF) backup system, in LFR power plants using molten salt as a heat transfer fluid (HTF). A 50 MW LFR power plant in Duba, Saudi Arabia, serves as a case study, with a Direct Normal Irradiance (DNI) above 2500 kWh/m2. About 600 SM-TES configurations are analyzed with the aim of minimizing the levelized cost of electricity (LCOE). The analysis shows that a solar-only plant can achieve a low LCOE of 11.92 ¢/kWh with a capacity factor (CF) up to 36%, generating around 131 GWh/y. By utilizing a TES system, the SM of 3.5 and a 15 h duration TES provides the optimum integration by increasing the annual energy generation (AEG) to 337 GWh, lowering the LCOE to 9.24 ¢/kWh, and boosting the CF to 86%. The techno-economic optimization reveals the superiority of the LFR with substantial TES over solar-only systems, exhibiting a 300% increase in annual energy output and a 20% reduction in LCOE. Additionally, employing the FF backup system at 64% of the turbine’s rated capacity boosts AEG by 17%, accompanied by a 5% LCOE reduction. However, this enhancement comes with a trade-off, involving burning a substantial amount of natural gas (503,429 MMBtu), leading to greenhouse gas emissions totaling 14,185 tonnes CO₂ eq. This comprehensive analysis is a first-of-a-kind study and provides insights into the optimal designs of LFR power plants and addresses thermal, economic, and environmental considerations of utilizing molten salt with a large TES system as well as employing natural gas backup. The outcomes of the research address a wide audience including academics, operators, and policy makers.

Predictive models for photosynthetic active radiation irradiance in temperate climates

This research evaluated 10 different empirical models designed for predicting Photosynthetically Active Radiation (PAR) at higher latitudes, addressing atmospheric conditions specific to these regions. The research introduces the Musleh-Rahman (MR) model, which substitutes Diffuse Horziontal Irradiance (DHI) with Clear Direct Normal Irradiance (DNI), Ozone and Aerosol Optical Depth at 550 nm (AOD550) sourced for satellite reanalysis data, achieving a Mean Bias Deviation (MBD) of 0.19 % and Root Mean Square Error (RMSE) of 12.42 W/m2. Furthermore, when applied to six untested locations, results demonstrate that the MR model outperformed the best performing empirical model with an MBD improvement of 3.68 % and an RMSE of 4.28 W/m2, whereas, when compared to machine learning models, the Light Gradient Boost Model (LGBM), had an MBD of −3.85 %. The MR model also maintained consistency across seasonal and density evaluations, attaining an R2 value as high as 0.9709, thereby highlighting the significant benefits of integrating satellite-sourced atmospheric data into PAR prediction models. Moreover, the research illustrated that substituting DHI with Clear DNI, Ozone, and AOD550 not only reduces MBD and boosts R2 values but also amplifies the model's applicability and accuracy in capturing early PAR peaks and reducing overestimations through precise adjustments in Ozone and AOD550 levels. This highlights the benefits of incorporating satellite-derived atmospheric data into PAR predictions models.

Pseudo-transient flow path optimization of a solar tower receiver operating with supercritical carbon dioxide

Aiming to further promote the decarbonization of energy production processes, this article simulates and optimizes the pseudo-transient behavior of a cylindrical solar receiver subjected to a spatially varying concentrated heat flux. The model employed, which accounts for its thermal–hydraulic behavior, uses supercritical carbon dioxide (s-CO2) as the heat transfer fluid and is based on a literature-validated hybrid formulation that axially discretizes the tube of the receiver and simultaneously solves the 2-D temperature distribution within the cross-section of each node. The operational conditions imposed on the receiver were determined such that it can produce 10 MW in a recompression Brayton cycle. Also, the receiver’s surface was exposed to a spatially variable concentrated solar boundary condition based on the direct normal irradiance (DNI) of a representative day for each month of the year, which was selected from the typical meteorological year (TMY) in Seville (Spain). The results showed that the combined thermal–hydraulic efficiency of the receiver increases with the number of panels and that the mass flow flowing through each symmetrical side of the receiver should not necessarily be identical for achieving maximal efficiency. More importantly, the results showed that by simply changing the location of the s-CO2 inlet and outlet ports, one can increase the efficiency of the receiver by about 3 % while considering the exact same concentrated solar irradiation.

Photovoltaic Energy Production in Greenhouses With Spectral Splitting Solar Trackers

The spectral filtering low concentration photovoltaic system developed by Voltiris is an innovative solution for energy production in greenhouses without affecting food production. A first prototype was installed in the greenhouse of the agricultural research center Agroscope in Conthey, Switzerland. During an eight-month agronomic study from March to October, the yield of tomato, pepper bell and basil under this system was on a par with a control group. I-V curves were recorded to evaluate the photovoltaic system performance, and the impact of concentration and filtering. The curves showed that the prototype achieved a direct normal irradiation efficiency of 10.1 %. The specific power output of the Voltiris system inside the greenhouse was comparable to the one of a conventional solar panel placed outside. Filters with two different transmission spectra were used, both of which were matched to the absorption spectra of chlorophyll and reflected 50 % and 60 % of the incident global radiation respectively. To transfer the performance of the system to other greenhouses, the transmittance of the test greenhouse and its glass cover were measured for global and diffuse radiation. This allowed to determine the transmittance of the greenhouse specific metal structure. In the test greenhouse, the overall transmission coefficient for direct solar radiation was 0.28, hence limiting the system yield.

Thermal management of ultra high concentrator photovoltaic cells: Analysing the impact of sintered porous media microchannel heat sinks

Implementing advanced cooling strategies is essential to maintaining recommended operation conditions, enhancing energy efficiency, and extending the reliability of ultra-high concentrator photovoltaics. This study introduces a new application of sintered porous media as an effective and superior thermal management solution for ultra-high concentrator photovoltaic systems. Furthermore, predictive models for thermal and electrical performance are developed.A comprehensive three-dimensional computational fluid dynamics model was developed and verified against experimental work reported to investigate the performance of a novel sintered porous media for thermal management in ultra-high concentrator photovoltaics. Furthermore, the response surface methodology coupled with analysis of variance was used to analyze and comprehensively optimize the thermal management system. The main objective is to develop a predictive model for such systems equipped with a porous cooling system that predicts performance with a concentration ratio of up to 20000 Suns. Predictive models were formulated to outline the relationships between various independent variables: Reynolds number, concentration ratio, direct normal irradiance, wind speed, optical efficiency, fluid inlet temperature, and dependent performance metrics.This study highlights the effectiveness of sintered porous media in heat dissipation and efficiency enhancement in ultra-high concentrator photovoltaics thermal management. The results demonstrate that using sintered porous media compared to conventional channel heatsinks significantly enhances cell thermal management. Specifically, this approach reduces cell temperature by 15.3%, 8.97%, and 2% at concentration ratios of 20000, 10000, and 2000, respectively. Concurrently, implementing the new sintered porous media heatsink improves cell efficiency by 3.1%, 1.5%, and 0.3% for the same respective concentration ratio values.