Search Results (7)

Floating photovoltaic systems (FPVSs) are gaining popularity, especially in countries with high population density and abundant solar energy resources. FPVSs provide a variety of advantages, particularly in situations where land is limited. Therefore, the main objective of the study is to evaluate the solar energy potential and investigate the techno-economic perspective of FPVSs at 15 water reservoirs in Northern Cyprus for the first time. Due to the solar radiation variations, solar power generation is uncertain; therefore, precise characterization is required to manage the grid effectively. In this paper, four distribution functions (Johnson SB, pert, Phased Bi-Weibull, and Kumaraswamy) are newly introduced to analyze the characteristics of solar irradiation, expressed by global horizontal irradiation (GHI), at the selected sites. These distribution functions are compared with common distribution functions to assess their suitability. The results demonstrated that the proposed distribution functions, with the exception of Phased Bi-Weibull, outperform the common distribution regarding fitting GHI distribution. Moreover, this work aims to evaluate the effects of floating photovoltaic systems on water evaporation rates at 15 reservoirs. To this aim, five methods were used to estimate the rate of water evaporation based on weather data. Different scenarios of covering the reservoir’s surface with an FPVS were studied and discussed. The findings showed that annual savings at 100% coverage can reach 6.21 $\times$ 10⁵ m³ compared to 0 m³ without PV panels. Finally, technical and economic assessment of FPVSs with various scales, floating assemblies, and PV technologies was conducted to determine the optimal system. The results revealed that a floating structure (North orientation-tilt 6°) and bifacial panels produced the maximum performance for the proposed FPVSs at the selected sites. Consequently, it is observed that the percentage of reduction in electricity production from fossil fuel can be varied from 10.19% to 47.21% at 75% FPV occupancy. Full article

The efficiency of solar systems, in particular photovoltaic panels, is typically low. Various environmental parameters affect solar panels, including sunlight, the ambient and module surface temperatures, the wind speed, humidity, shading, dust, the installation height, etc. Among others, the key players are indeed solar irradiance and temperature. The higher the temperature is, the higher the short-circuit current is, and the lower the open-circuit voltage is. The negative effect of lowering the open-circuit voltage is dominant, consequently lowering the power of the photovoltaic panels. Passive or active cooling systems can be provided to avoid the negative effect of temperature. This paper presents a prototype of an active cooling system dedicated to photovoltaics. The prototype of such a system was developed at the AGH University of Kraków and tested under laboratory conditions. The proposed system is equipped with air fans mounted on a plate connected to the rear part of a 70 Wp photovoltaic panel. Different configurations of the system were tested, including different numbers of fans and different locations of the fans. The artificial light source generated a irradiation value of 770 W/m². This value was present for every variant tested in the experiment. As observed, the maximum power generated in the photovoltaic panel under laboratory conditions was approx. 47.31 W. Due to the temperature increase, this power was reduced to 40.09 W (when the temperature of the uncooled panel surface reached 60 °C). On the other hand, the power generated in the photovoltaic panel equipped with the developed cooling system was approx. 44.37 W in the same conditions (i.e., it was higher by 10.7% compared to that of the uncooled one). A mathematical model was developed based on the results obtained, and simulations were carried out using the ANSYS Workbench software. After the validation procedure, several configurations of the air cooling system were developed and analyzed. The most prominent case was chosen for additional parametrical analysis. The optimum fan orientation was recognized: a vertical tilt of 7° and a horizontal tilt of 10°. For the tested module, this modification resulted in a cost-effective system (a net power increase of ~3.1%). Full article

Agrometeorological stations have horizontal solar irradiation data available, but the design and simulation of photovoltaic (PV) systems require data about the solar panel (inclined and/or oriented). Greenhouses for agricultural production, outside the large protected production areas, are usually off-grid; thus, the solar irradiation variable on the panel plane is critical for an optimal PV design. Modeling of solar radiation components (beam, diffuse, and ground-reflected) is carried out by calculating the extraterrestrial solar radiation, solar height, angle of incidence, and diffuse solar radiation. In this study, the modeling was done using Simulink-MATLAB blocks to facilitate its application, using the day of the year, the time of day, and the hourly horizontal global solar irradiation as input variables. The rest of the parameters (i.e., inclination, orientation, solar constant, albedo, latitude, and longitude) were fixed in each block. The results obtained using anisotropic models of diffuse solar irradiation of the sky in the region of Castile and León (Spain) showed improvements over the results obtained with isotropic models. This work enables the precise estimation of solar irradiation on a solar panel flexibly, for particular places, and with the best models for each of the components of solar radiation. Full article

With the growing demand for clean and economically feasible renewable energy, solar photovoltaic (PV) system usage has increased. Among many factors, the tilt and azimuth angles are of great importance and influence in determining the photovoltaic panel’s efficiency to generate electricity. Although much research was conducted related to solar PV panels’ performance, this work critically determined the tilt and azimuth angles for PV panels in all countries worldwide. The optimum tilt and azimuth angles are estimated worldwide by the photovoltaic geographic information system (PVGIS). Also, annual and average daily solar irradiation incident on the tilted and oriented plate optimally (AR1 and DR1) are calculated. Besides, annual and average daily solar irradiation incident on plate tilt optimally and oriented because of the south in the northern hemisphere and because of the north in the southern hemisphere (AR2 and DR2) are estimated. PVGIS is also used to calculate the annual and average daily solar irradiation incident on the horizontal plate (AR3 and DR3). The data collected from PVGIS are used to develop an efficient and accurate artificial neural network model based on feed-forward neural network approach. This model is an essential subpart that can be used in an embedded system or an online system for further PV system analysis and optimization. The developed neural model reflected very high accuracy in predicting the PV panels’ optimal tilt and azimuth angles worldwide. The benefit of tilting is generally increased by increasing the latitude. As the latitude increases, the tilt factor (F) increases because of the increase in the optimum tilt angle by increasing the latitude. The optimal orientation is due to the north in the southern hemisphere and due to the south in the northern hemisphere for most cities worldwide. In sum, it can be concluded that the optimum tilt angle is equal to or greater than the latitude until the latitude 30°. The optimum tilt angle becomes less than the latitude, and the difference is increased until it reaches more than 20°. Hence in this study the aim is to develop a simple neural network model which can accurately predict the annual radiation and optimum tilt and azimuth angle in any region of the world and can be easily implemented in a low-cost microcontroller. Full article

Photovoltaics modules are usually installed with a tilt angle to improve performance and to avoid water or dust accumulation. However, measured irradiance data on inclined surfaces are rarely available, since installing pyranometers with various tilt angles induces high costs. Estimating inclined irradiance of arbitrary orientations and tilt angles is important because the installation orientations and tilt angles might be different at different sites. The goal of this work is to propose a unified transfer model to obtain inclined solar irradiance of arbitrary tilt angles and orientations. Artificial neural networks (ANN) were utilized to construct the transfer model to estimate the differences between the horizontal irradiance and the inclined irradiance. Compared to ANNs that estimate the inclined irradiance directly, the experimental results have shown that the proposed ANNs with differential outputs can substantially improve the estimation accuracy. Moreover, the trained model can successfully estimate inclined irradiance with tilt angles and orientations not included in the training data. Full article

To maximize the direct insolation received by flat-plate photovoltaic (PV) modules, the tilt angle is usually the site’s latitude and the modules are oriented towards the equator. However, this may not be the optimal placement, as the local climatic conditions will influence the optimal orientation and tilt angle. Transposition models can be used to simulate the insolation on planes with various tilts and azimuths, using a single set of (horizontal) global and diffuse irradiance measurements. Following this method, five maps including optimal orientations, tilt angles, maximum annual tilted irradiations, percentage improvements of the optimally-tilted PV installation versus the conventional latitude-tilted PV installation, and annual diffuse fraction were plotted over the geographical area of Japan. Spatial patterns in these maps were observed and analyzed. The key contribution of this work is to establish a database of optimal PV installations in Japan. Compared to the conventional rule of thumb of tilting the module at latitude facing south, it is shown that the optimally tilted surface receives up to 2% additional annual solar irradiation. Full article

This work assesses the performance of five transposition models that estimate the global and diffuse solar irradiance on tilted planes based on the global horizontal irradiance. The modelled tilted irradiance values are compared to measured one-minute values from pyranometers and silicon sensors tilted at different angles at Hannover (Germany) and NREL (Golden, CO, USA). It can be recognized that the deviations of the model of Liu and Jordan, Klucher and Perez from the measurements increases as the tilt angle increases and as the sensors are oriented away from the south direction, where they receive lower direct radiation than south-oriented surfaces. Accordingly, the vertical E, W and N planes show the highest deviation. Best results are found by the models from Hay and Davies and Reindl, when horizontal pyranometer measurements and a constant albedo value of 0.2 are used. The relative root mean squared difference (rRMSD) of the anisotropic models does not exceed 11% for south orientation and low inclination angles (β = 10–60°), but reaches up to 28.9% at vertical planes. For sunny locations such as Golden, the Perez model provides the best estimates of global tilted irradiance for south-facing surfaces. The relative mean absolute difference (rMAD) of the Perez model at NREL ranges from 4.2% for 40° tilt to 8.7% for 90° tilt angle, when horizontal pyranometer measurements and a measured albedo value are used; the use of measured albedo values instead of a constant value of 0.2 leads to a reduction of the deviation to 3.9% and 6.0%, respectively. The use of higher albedo values leads to a significant increase of rMAD. We also investigated the uncertainty resulting from using horizontal pyranometer measurements, in combination with constant albedo values, to estimate the incident irradiance on tilted photovoltaic (PV) modules. We found that these uncertainties are small or negligible. Full article