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Numerical and outdoor real time experimental investigation of performance of PCM based PVT system
摘要： Photovoltaic power generation is a suitable option to counter depleting and environmentally hazardous fossil fuels. However, increased cell temperature of the photovoltaic module reduces the electrical performance. Therefore, for enhancing the electrical performance as well as to obtain the useful thermal, a combined photovoltaic thermal system is suitable technology. Furthermore, the addition of phase change materials into photovoltaic thermal systems adds more dual benefits in terms of cooling of PV cell as well as heat storage. Hence, there are still issues to transfer heat from the system efficiently, which cause lower performance of PVT and PVT-PCM systems. In this paper, the aluminium material of thermal collector is used by introducing a novel design to enhance heat transfer performance, which is assembled in PVT and PVT-PCM systems. Experimental validation is carried out for the 3D FEM-based numerical analysis with COMSOL Multiphysics? at 200 W/m2 to 1000 W/m2 varying irradiation levels while keeping mass flow rate fixed at 0.5LPM and inlet water temperature at 32 °C. The experiment is carried out at outdoor free weather conditions with passive cooling of the module by an overhead water tank scheme. A good agreement in numerical and experimental results is achieved through experimental validation. Cell temperature reduction of 12.6 °C and 10.3 °C is achieved from the PV module in case of the PVT-PCM system. The highest value of the electrical efficiency achieved is 13.72 13.56% for PV and 13.85 and 13.74% for PVT numerically and experimentally respectively. Similarly, for PVT-PCM, electrical efficiency is achieved as 13.98 and 13.87% numerically and experimentally respectively. In the case of the PVT system, electrical performance is improved as 6.2 and 4.8% and for PVT-PCM, it is improved as 7.2 and 7.6% for numerically and experimentally respectively.
关键词： PCM,PV/T,Performance,Solar irradiation
更新于2025-09-23 15:23:52
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Some Applications of ANN to Solar Radiation Estimation and Forecasting for Energy Applications
摘要： In solar energy, the knowledge of solar radiation is very important for the integration of energy systems in building or electrical networks. Global horizontal irradiation (GHI) data are rarely measured over the world, thus an artificial neural network (ANN) model was built to calculate this data from more available ones. For the estimation of 5-min GHI, the normalized root mean square error (nRMSE) of the 6-inputs model is 19.35%. As solar collectors are often tilted, a second ANN model was developed to transform GHI into global tilted irradiation (GTI), a difficult task due to the anisotropy of scattering phenomena in the atmosphere. The GTI calculation from GHI was realized with an nRMSE around 8% for the optimal configuration. These two models estimate solar data at time, t, from other data measured at the same time, t. For an optimal management of energy, the development of forecasting tools is crucial because it allows anticipation of the production/consumption balance; thus, ANN models were developed to forecast hourly direct normal (DNI) and GHI irradiations for a time horizon from one hour (h+1) to six hours (h+6). The forecasting of hourly solar irradiation from h+1 to h+6 using ANN was realized with an nRMSE from 22.57% for h+1 to 34.85% for h+6 for GHI and from 38.23% for h+1 to 61.88% for h+6 for DNI.
关键词： solar irradiation,estimation,meteorological data,short time step,forecasting
更新于2025-09-23 15:22:29
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An inverse approach to identify selective angular properties of retro-reflective materials for urban heat island mitigation
摘要： This work presents the preliminary stages of a wider study aiming at assessing the potentials of retro-re?ective (RR) materials to mitigate urban heat island e?ects. Th study herewith reported is based on an inverse approach, which originates from the evaluation of the solar irradiation incident on urban surfaces (i.e. fa?ade, roof, and paving) and leads to the identi?cation of the optimal angular properties required to activate such a material. The solar radiation geometry and the solar irradiation collected by the south-exposed vertical and the horizontal surfaces, were assessed by solar dynamic simulation tools. Furthermore, the angular distribution of the solar direct irradiation component and the direct to global solar irradiation ratio were estimated. The analyses were carried out for nine locations between Oulu (Finland) and Doha (Qatar), with an increment of 5° latitude between two locations. The results demonstrate that the application of RR materials to horizontal surfaces can always be e?ective, whereas when applied on the vertical surface, the solar geometry in?uences to a much greater extent the performance of these materials. The main ?ndings of this study show that the selective angular properties of an ideal RR material should be in the angular interval between 25° and 55° and between 30° and 90°, in case of vertical surfaces and horizontal surfaces, respectively. Best practices related to the application of RR materials and the activation of their selective angular properties in di?erent climate zones are also reported.
关键词： Solar irradiation,Retro-re?ective materials,Selective angular properties,Urban heat island
更新于2025-09-23 15:21:21
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The influence of the solar radiation database and the photovoltaic simulator on the sizing and economics of photovoltaic-diesel generators
摘要： This study evaluated the outcome differences when adopting five different solar irradiation databases on the sizing of hybrid solar photovoltaic-diesel generators designed to supply electricity to isolated minigrids. To do this, the two most widely adopted photovoltaic (PV) simulation packages in the market, namely PVsyst? and HOMER Energy? were used. The different origins, data timespan, space and time resolution, of the five most relevant solar irradiation databases available for the region were compared. A case study was presented to illustrate the influences of the solar irradiation database and the solar simulation tool on the resulting PV generator. Furthermore, the hourly behavior of the energy supply to an existing load in a minigrid in the Brazilian Amazon was evaluated, together with the savings in diesel obtained with the resulting PV generator. Evaluating the five options of solar radiation databases, for the same PV plant configuration, variations of up to 19.7% were found in the expectation of PV generation. When the simulation software package was varied, the combined effect (radiation database X PV system sizing tool) showed differences of up to 20.6%. This demonstrates that despite having different algorithms, computational tools have a small influence (less than 1%) on results. These combined differences, taking into account the load curve behavior and the total diesel generation capacity installed at the site, resulted in over 100% differences in the optimum PV generator size in the case study. The total savings in diesel fuel, over a 15-years period, ranged from $ 6.5 million to over $ 16 million (> 2.5 times) for the smallest PV system. This demonstrates the importance of the correct choice of database. These evaluations can be extended to minigrids of any size elsewhere. The novelty and originality of this study is to demonstrate and quantify for the first time the influence of the solar radiation database and the PV simulator package on the sizing of PV-diesel generators. The consequences of this study are not only of scientific and academic importance, but of economic and commercial interest as well.
关键词： Photovoltaic simulation tool,Hybrid photovoltaic-diesel power plant,Solar database,Minigrids,Solar irradiation
更新于2025-09-23 15:21:01
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Synthesis, Characterization of SiO2/TiO2 and SiO2/Al2O3 Nano-Composites for the Photo-Degradation of Acid Brown- 43 dye with Irradiation of Solar Light
摘要： In this study we have found that photo degradation of Acid brown- 43 dye with irradiation Solar light Using synthesized SiO2/ TiO2 and SiO2/Al2O3 Nano-composites which prepared by chemical precipitation technique using microwave irradiation. The structure and morphology of SiO2/TiO2 and SiO2/Al2O3) Nano composites were characterized by SEM, EDAX & TEM analysis. The similarities in photo degradation mechanism, SiO2, Al2O3 and TiO2 have as good as band gap energy, and possess worthy standing as photo-catalysts. SiO2/TiO2 and SiO2/Al2O3 nanoparticles have large surface area and thus provide a large number of active sites for interaction among the particles of different oxides. This synthesized Nano-composites of SiO2/TiO2 and SiO2/Al2O3 photo-catalyst sample showed tremendous photo-catalytic activity for the degradation of Acid Blue-43 under direct exposure to solar irradiation with respect to exposed time and dose of Nano-composites.
关键词： Acid brown–43,Photo-degradation,solar irradiation,Nano-composite
更新于2025-09-23 15:21:01
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Proceedings of the 2nd International Conference on BioGeoSciences (Modeling Natural Environments) || Tilt and Orientation of a Flat Solar Collector to Capture Optimal Solar Irradiation in Chilean Latitudes
摘要： The use of solar technologies is growing steadily throughout the world since solar radiation is recognized as an inexpensive and local renewable source of energy. At the same time, it helps to reduce the great environmental impact caused by the exploitation of non-renewable energy sources. Accurate information about incident solar radiation over an inclined surface is important for selection and installation of solar technologies. In this study, seasonal and annual total irradiation values received on a ?at solar collector were calculated by varying the inclination angle from 0° to 90°, and the azimuth angle from ?180° to 180° for 12 cities in Chile, based in one typical meteorological year. The study provides useful information about the in?uence of the tilt and azimuth angles to the total seasonal and annual solar energy collected. Several cities of Chile located from north to south were selected for the study, including Arica, Calama, Antofagasta, Vallenar, La Serena, Valparaíso, Talca, Concepción, Los Angeles, Valdivia, Puerto Montt, and Puerto Natales. The isotropic sky model was used to calculate the total irradiances. The results showed that during the summer months the average irradiation values were above 150 kWh/m2 in all cities. During the summer months, the device may be inclined between 0° and 30°, whereas during the winter months it is recommended to reset the inclination angle between 30° and 60°. The estimated annual solar radiation gains, based on tilt and azimuth angles, compared to a horizontal surface, increase toward the south with a maximum gain 10.08% for the city of Puerto Natales. The lowest gain was for the city of Arica with 0.55%, which shows that its best use is close to the horizontal surface. Although, the range of inclination and azimuth angles to achieve optimal irradiation values is wide, it is recommended to set the tilt angle of the ?at solar collector between 0° (cid:1) b (cid:1) 60° and the azimuth angle from ?60° (cid:1) c (cid:1) 60°. For losses smaller than 5% of irradiation, the azimuth angle can oscillate between ±30° without a signi?cant impact on the total irradiation captured by a ?at solar collector.
关键词： Flat solar collector,Tilt angle,Solar irradiation,Chile,Renewable energy
更新于2025-09-23 15:19:57
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Forecasting the Performance of a Photovoltaic Solar System Installed in other Locations using Artificial Neural Networks
摘要： Photovoltaic solar energy has been spread all over the world, and in Brazil this energy source has been getting considerable space in the last years, being driven mainly by the energy crises. However, when installed in regions with low incidence of solar irradiation, this technology presents a loss of efficiency in the generation of energy. As an alternative to this consideration, a power prediction study could be conducted prior to its installation, based on local climate information that directly influences power generation, verifying the feasibility of system implementation and avoiding unrewarded investment. Therefore, the objective of this work is to predict the viability of the installation of a photovoltaic system of 3kWp in different places, with the assist of an Artificial Neural Network. Thus, the feedforward network was used for the training, being trained and validated with the support of MatlabVR , and inserting samples of temperature and solar irradiation as input variables. Through the performance methods, the results are favorable for this application, presenting validations with RMSE% in the range of 13-20% and R of not less than 0.93. The predictions presented RMSE% around 19-25% and average powers close to the real values generated by the PV system.
关键词： solar irradiation,renewable energy,electrical systems,energy efficiency,power forecasting,feedforward,artificial neural network,root mean square error,solar photovoltaic system,distributed generation
更新于2025-09-19 17:13:59
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Comparison of Power Output Forecasting on the Photovoltaic System Using Adaptive Neuro-Fuzzy Inference Systems and Particle Swarm Optimization-Artificial Neural Network Model
摘要： The power output forecasting of the photovoltaic (PV) system is essential before deciding to install a photovoltaic system in Nakhon Ratchasima, Thailand, due to the uneven power production and unstable data. This research simulates the power output forecasting of PV systems by using adaptive neuro-fuzzy inference systems (ANFIS), comparing accuracy with particle swarm optimization combined with artificial neural network methods (PSO-ANN). The simulation results show that the forecasting with the ANFIS method is more accurate than the PSO-ANN method. The performance of the ANFIS and PSO-ANN models were verified with mean square error (MSE), root mean square error (RMSE), mean absolute error (MAP) and mean absolute percent error (MAPE). The accuracy of the ANFIS model is 99.8532%, and the PSO-ANN method is 98.9157%. The power output forecast results of the model were evaluated and show that the proposed ANFIS forecasting method is more beneficial compared to the existing method for the computation of power output and investment decision making. Therefore, the analysis of the production of power output from PV systems is essential to be used for the most benefit and analysis of the investment cost.
关键词： solar irradiation,adaptive neuro-fuzzy inference systems,PVs power output forecasting,particle swarm optimization-artificial neural networks
更新于2025-09-19 17:13:59
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Evaluation of Photovoltaic Power Generation by using Deep Learning in Solar Panels Installed in Buildings
摘要： Southern Taiwan has excellent solar energy resources that remain largely unused. This study incorporated a measure that aids in providing simple and effective power generation efficiency assessments of solar panel brands in the planning stage of installing these panels on roofs. The proposed methodology can be applied to evaluate photovoltaic (PV) power generation panels installed on building rooftops in Southern Taiwan. In the first phase, this study selected panels of the BP3 series, including BP350, BP365, BP380, and BP3125, to assess their PV output efficiency. BP Solar is a manufacturer and installer of photovoltaic solar cells. This study first derived ideal PV power generation and then determined the suitable tilt angle for the PV panels leading to direct sunlight that could be acquired to increase power output by panels installed on building rooftops. The potential annual power outputs for these solar panels were calculated. Climate data of 2016 were used to estimate the annual solar power output of the BP3 series per unit area. The results indicated that BP380 was the most efficient model for power generation (183.5 KWh/m2-y), followed by BP3125 (182.2 KWh/m2-y); by contrast, BP350 was the least efficient (164.2 KWh/m2-y). In the second phase, to simulate meteorological uncertainty during hourly PV power generation, a surface solar radiation prediction model was developed. This study used a deep learning–based deep neural network (DNN) for predicting hourly irradiation. The simulation results of the DNN were compared with those of a backpropagation neural network (BPN) and a linear regression (LR) model. In the final phase, the panel of module BP3125 was used as an example and demonstrated the hourly PV power output prediction at different lead times on a solar panel. The results demonstrated that the proposed method is useful for evaluating the power generation efficiency of the solar panels.
关键词： solar irradiation,deep learning,photovoltaic solar energy,prediction
更新于2025-09-16 10:30:52
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Uncertainty Model for Total Solar Irradiance Estimation on Australian Rooftops
摘要： The installations of solar panels on Australian rooftops have been in rise for the last few years, especially in the urban areas. This motivates academic researchers, distribution network operators and engineers to accurately address the level of uncertainty resulting from grid-connected solar panels. The main source of uncertainty is the intermittent nature of radiation, therefore, this paper presents a new model to estimate the total radiation incident on a tilted solar panel. Where a probability distribution factorizes clearness index, the model is driven upon clearness index with special attention being paid for Australia with the utilization of best-fit-correlation for diffuse fraction. The assessment of the model validity is achieved with the adoption of four goodness-of-fit techniques. In addition, the Quasi Monte Carlo and sparse grid methods are used as sampling and uncertainty computation tools, respectively. High resolution data resolution of solar irradiations for Adelaide city were used for this assessment, with an outcome indicating a satisfactory agreement between actual data variation and model.
关键词： diffuse fraction correlation,goodness of fit,Solar irradiation prediction,tilted surface
更新于2025-09-09 09:28:46