Solar Panel Temperature Research Articles

An Expermental Study of Solar Panel Performance Using Heat Pipe and Thermoelectric Generator

Solar energy is the main source of energy that is expected to play a vital role in fulfilling the future global demand for electricity. Design of advanced photovoltaic (PV) system with high electric conversion efficiency is the key for collecting solar energy. A major obstacle hindering useful PV utilization is the deterioration of solar cell efficiency with temperature. In this paper, the performance of solar panel using a micro flat heat pipe (HP) and thermoelectric generator (TEG) is proposed and experimentally investigated. In order to operate HP and TEG at highest possible efficiency, the condensation section of HP is innovatively cooled by utilizing the condensed water inside the evaporator of the air conditioner (which is usually between 5-7 °C). Two different types of silicon panel are used in the study: monocrystalline solar panel and polycrystalline solar panel. The results showed that a reduction in average solar panel temperature up to 25% is obtained. In addition, the produced power was increased by as much as 50% when the solar panel was cooled by the heat pipe. In order to test the performance of the cooling system combined with the solar panel, the feasibility study and cost analysis is carried out using SAM software.

A simple stochastic method for modelling the uncertainty of photovoltaic power production based on measured data

This paper describes statistical quantification tools for predicting photovoltaic (PV) production considering uncertainty in PV production at same irradiation levels and PV panel temperatures. When analysing measured data, it is observed that there are different PV power production levels for the same irradiation levels and panel temperatures. These PV power spread out can be caused by different causes, such as dust deposition over the panel, non-ideal working of maximal power point tracking devices, device efficiencies' dependence on power, different temperatures over the PV panel, and others. Due to the stochastic character of these occurrences, they can be challenging when considered in the deterministic mathematical models usually used for PV power prediction. The probabilistic method for PV power production is proposed based on the probability density function with respect to the solar irradiation and the panel temperature. The simulation results are compared among the different models based on the probability density function with respect to the solar irradiation and panel temperature. The best overlapping between measured and calculated PV power production gives the proposed stochastic models dependent only on irradiance. The proposed stochastic model gives a PV energy prediction on a yearly basis with an error of less than 1%.

Enhancement the Performance of PV Panel by Using Fins as Heat Sink

In this paper, theoretical and experimental study of the performance enhancement of PV panels has been presented by utilizing fins for cooling module’s temperature at climate conditions operation. To satisfactory cool off for the solar panel as a passive technique, heat sink which has a rectangular variable cross section fins (ribs) attached on the back side of the panel. Analytical thermal model is formulated for heat dissipation from heat sink in order to predict PV panel temperature. A comparison between experimental and theoretical results was carried out for solar panels without and with fins, in order to investigate the proposed thermal model and study the effect of operating temperature on the power output from the panel. The results shows that using fin cooling technique causes a significant dropped in average solar panel temperature about 5.7°C and an enhancement in the average of module output power about 15.3%.

Efficiency enhancement of silicon solar cells using highly porous thermal cooling layer

In summer season, temperature of solar panels increases thereby decreases the working efficiencies of the solar cells by a larger factor, sometime even up to 3–4%. The present research paper reports a carbon-based porous thermal cooling layer, which acts as a heat dissipating agent beneath the poly-crystalline silicon solar cell. The thermal cooling layer has highly porous structure with average interpore and intrapore size to be 6 µm–0.6 µm and 11.5 Å, respectively, which enhances the surface area (798.35 m2/g) and generates numbers of air channels within the sheet for higher heat dissipation. Thermal cooling layer’s thickness-dependent studies confirm that an optimum thickness of 14 mm shows the highest cooling efficiency. The thermal cooling layer beneath the solar cell decreases the working temperature of the cell up to 18.5°C. The open-circuit voltage recorded for the solar cell (with optimized thickness of thermal cooling layer beneath the cell) increases to 0.56 V from 0.52 V (device without thermal cooling layer) at real time condition, which leads to increase the working efficiency of the cell by 9.6%. The theoretically calculated and experimentally measured efficiency of the solar cell at various temperatures are compared and shows good agreement between experimental data and theory. This investigation reveals that the used thermal cooling layer can significantly improve the device working efficiency in a simple and cost-effective manner.

Anomaly detection and predictive maintenance for photovoltaic systems

Abstract We present a learning approach designed to detect possible anomalies in photovoltaic (PV) systems in order to let an operator to plan predictive maintenance interventions. The anomaly detection algorithm presented is based on the comparison between the measured and the predicted values of the AC power production. The model designed to predict the AC power production is based on an Artificial Neural Network (ANN), that is capable of estimating the AC power production using solar irradiance and PV panel temperature measurements, and that is trained using a dataset previously gathered from the plant to be monitored. Live trend data coming from the PV system are then compared with the output of the model and the vector of residuals is analyzed to detect anomalies and generate daily predictive maintenance alerts; there residuals are aggregated over 1-day and processed to detect out-of-threshold samples and system degradation trends; these trends are extracted by computing the Triangular Moving Average (TMA) where the window size is automatically determined. The paper also reports experimental data results revealing that the model leads to a good anomaly detection rate, which is measured as a positive predictive detection rate greater than 90%. Moreover, the algorithm is able to recognize trends of system’s deviations from normal operation behavior and generate predictive maintenance alerts as a decision support system for operatives, with the aim of avoiding possible incoming failures.

Solar panel temperature control system using IoT

Solar panel temperature control system using IoT

Environmentally Sustainable Roof Integrated Solar Conservatory System

It is a well-known fact that the efficiency of the photovoltaic decreases with the increase in the operating Solar PV panel temperature. Solar Photovoltaic/Thermal (PV/T) technology is a newer solar conversion technology which would convert the incident solar radiation into usable electrical and thermal energy at the same time. It is observed that solar PV modules have low efficiencies of not more than 20% that means 80% or more of the total incoming solar radiation is not utilized and converted as heat which is utilized in raising the operating temperature of the module. This heat can be removed by passing water from the rear surface of the absorber plate which is the Solar PV panel. The absorbed heat can be used in low temperature application like drying, space heating, etc., Thus it is the aim of the present study to go in for the thermal analysis of building integrated solar PV-T system as a means of energy conservation and environmentally sustainable solution with respect to carbon dioxide emissions.

Prediction of Solar PV Panel Temperature Using Mathematical Models and Artificial Neural Networks

Prediction of Solar PV Panel Temperature Using Mathematical Models and Artificial Neural Networks

Experimental study of efficiency of solar panel by phase change material cooling

The dependence of efficiency of photovoltaic panels on their temperature during operation is a major concern for developers and users. In this paper, a phase change material (PCM) cooling system was designed for a 60W mono-crystalline solar panel. Tealights candle was selected as the cooling medium. The solar irradiance was recorded using Kipp & Zonen CMP3 pyranometer and Meteon data logger. Temperature distribution on the surface of solar panel, output voltage and output current of solar panel were measured. The average irradiance throughout data collection was found to be 705W/m2 and highest irradiance was 1100 W/m2. The average solar panel temperature was 43.6°C and a maximum temperature of 53°C was at the center of solar panel. Results showed that average power output and efficiency of the solar panel were 44.4W and 15%, respectively. It was found that the higher the solar irradiance, the lower the efficiency of solar panel and the higher the temperature and power output of solar panel. This is due to the fact that high irradiance results in high power input and high solar panel temperature. But high PV panel temperature reduces its power output. Therefore, the increase of power input outweighs that of power output, which leads to the decrease of efficiency of solar panel with the increase of solar irradiance. Compared with solar panel without cooling, the power output and efficiency of solar panel did not increase with PCM cooling. It indicates that Tealights candle as PCM cooling is not efficient in improving the efficiency of solar panel in this study.

The mathematical modeling of concentrated photovoltaic module temperature

In this study, we examined the effect of the use of paraffin wax on the panel temperature of concentrated solar panels. Some tests were performed on various days for three months (including spring, summer, and winter months). With the help of the experimental results, new approaches have been made as concentrator ratio, area ratio, concentrator efficiency and power coefficient. As a result of this approaches the concentrator ratio was found to be 3. When the concentrator ratio was 3, the panel temperature of the system with paraffin was found to be between 80 and 100 °C, while that of the other system was found to be above 100 °C. Panel efficiency might be reduced down to 10% at these temperatures. The study also included the development of a mathematical model of the changes in the panel temperature of the concentrated systems in which paraffin was not used. The temperature at the back of the panels could be calculated by this mathematical model, depending on the ambient temperature and the concentrated solar radiation. The correlation coefficient of the mathematical model was found to be 0.929. The test results of two days, which were not included in the model, were used to determine the reliability of the model, and the panel temperatures were calculated using the correlation coefficients of 0.933 and 0.966.

Математическое моделирование динамики температуры солнечных батарей в различных условиях орбитального полета космического аппарата

Математическое моделирование динамики температуры солнечных батарей в различных условиях орбитального полета космического аппарата

One Cycle Control Based Maximum Power Point Tracker Applied in Photovoltaic Systems

The utilization of solar energy has grown in the last decades, and due to the scarcity of fossil fuels and the awareness of the increasing greenhouse gases in the atmosphere, this energy tends to become predominant. For generating photovoltaic energy, photovoltaic modules are connected to converters to define the amount of energy provided to a load. A maximum power point tracking method is used to maximize the photovoltaic module output power considering the solar radiation and panel temperature. This work proposes the implementation of one-cycle control (OCC) to track the maximum power point of a photovoltaic module in direct current converters. This paper contains an analysis of response speed, reference tracking and transient, showing the applicability of the OCC technique.

Artificial neural network modeling of a photovoltaic-thermal evaporator of solar assisted heat pumps

In this work, the artificial neural network model was developed to predict the energy performance of a photovoltaic-thermal evaporator used in solar assisted heat pumps. The experiments were carried out under the meteorological conditions of Coimbatore city (latitude of 10.98°N and longitude of 76.96°E) in India. The energy performance parameters of a photovoltaic-thermal evaporator such as, evaporator heat gain, solar energy input ratio, photovoltaic efficiency and photovoltaic panel temperature were observed with reference to four ambient parameters such as, solar intensity, ambient temperature, ambient wind velocity and ambient relative humidity. The experimental results were used as training data for the network. The multilayer feed forward network is optimized to 4-15-4 configuration for predicting the energy performance of the photovoltaic-thermal evaporator. Analysis of variance was carried out to identify the significant ambient parameter influencing the energy performance of photovoltaic-thermal evaporators. The network predictions are found to be closer to the experimental values with the maximum fraction of absolute variance values, minimum root mean square errors and minimum coefficient of variance values. The analysis of variance results confirmed that solar intensity and ambient temperature are the most influencing parameters affecting the energy performance of photovoltaic-thermal evaporators.

Online Fault Detection in PV Systems

This paper presents the development of a practical fault detection approach in photovoltaic (PV) systems, intended for online implementation. The approach was developed and validated using field measurements from a Canadian PV system. It has a fairly low degree of complexity, but achieves a high fault detection rate and is able to successfully cope with abnormalities present in real-life measurements. The fault detection is based on the comparison between the measured and model prediction results of the ac power production. The model estimates the ac power production using solar irradiance and PV panel temperature measurements. Prior to model development, a data analysis procedure was used to identify values not representative of a normal PV system operation. The original 10-min measurements were averaged over 1h, and both datasets were used for modeling. In order to better represent the PV system performance at different sunlight levels, models for different irradiance ranges were developed. The results reveal that the models based on hourly averages are more accurate than the models using 10-min measurements, and the models for different irradiance intervals lead to a fault detection rate greater than 90%. The PV system performance ratio (PR) was used to keep track of the system's long-term performance.

Seasonal variations in the operating temperature of silicon solar panels in southern Ghana

This work deals with the seasonal daily variation of the operating temperature of silicon solar panels under tropical atmospheric conditions, including high turbidity (Harmattan dust particles). Data was collected from March 2010 to July 2012 at Legon (0°11′08″ W, 5°39'04″ N) using a Davis wireless Vantage Pro2 Plus weather station monitored with the software WeatherLink®. While the ‘common outdoor’ operating temperature is usually set at 45 °C, it has been observed that during the harmattan season, the operating temperature of a solar panel can rise beyond 70°C.

A Hydrogen Management Method in Residential Distributed Generation Systems with Photovoltaic Cells and Hydrogen‐Storage Type Fuel Cells

SUMMARYRecently, renewable energy has been attracting attention as a result of global warming and the depletion of fossil fuels. Photovoltaic (PV) systems have spread rapidly around the world because they generate electric power quietly and can be installed in many places. The output power generated in a PV system fluctuates with changes in solar irradiance and panel temperature. The reverse flow of surplus power in output spikes may have a negative effect on electric power quality, such as on the frequency and voltage in a power system. A residential distributed generation (DG) system composed of a fuel cell (FC) unit, an electrolyzer (EL) unit, and a PV system has been proposed in order to resolve these problems. In order to operate this system without interruption, the hydrogen storage volume must be managed. This paper proposes a novel hydrogen management method for a residential DG system with PV cells and hydrogen‐storage type FCs. The hydrogen storage volume is maintained at the preset frequency by operating the FC unit and the EL unit. Models of the PV, FC, and EL were constructed for a simulation. In the simulation, we showed that the proposed management method is viable for a residential DG system with PV cells and hydrogen‐storage FCs.

In Situ Solar Panel Output Power Measurement Related to Climate Parameters using Digital Recording

Solar energy in tropical area is one of potential renewable energy due to the sun always shines along of a year involving in dry and rainy season. The power output of solar panel is depended on climate parameters including solar radiation, humidity, cloud, rain, and dust decomposition. This paper explores the climate parameters that potentially affect the power output of solar panel and estimate the solar energy in such region based on its climate parameters. To measure the climate and electric data, this work develops in house digital climate and electrical data recording that saves the data of humidity, wind speed, temperature, solar irradiance, current, and voltage sensors. The data are analyzed by equation of correlation between climate parameters, power output and solar panel temperature. The protoype of digital recording is tested at Politeknik Negeri Semarang located on latitude -7.054044 and longitude 110.434695 during dry season. Based on the correlation analysis of several climate parameters to solar panel output power, the correlation value of the humidity is -0.85, ambient temperature=0.87, solar irradiance=0.98, wind speed= -0.34 and cell temperature=0.83. This work can be used to estimate the potency of solar panel output power in specific location using climate data.

Performance Evaluation of Photovoltaic Systems by Use of RBF Network Models

This paper deals with the problem of modeling and performance evaluation of the solar photovoltaic systems, based on the available operation data measurements. The main goal is to find out the most significant cause-effect relationships between the available measured inputs and the output power of the system. The problem is not easy one, because quite often the available measurements are correlated and in addition they have an indirect influence on the final output of the system - the output power. The use of the Radial Basis Function (RBF) network models is proposed in this paper. Two different models have been created. One of them needs direct available measurements for the solar radiation and the solar panel temperature to predict the output power. The other is indirect model, which first predicts the solar panel temperature, based on other measurements and then is used in another model for predicting the output power. It is shown in the paper that the indirect model is suitable for performance evaluation and simulation of a solar photovoltaic system under different climate conditions, in different parts of the country. This helps to optimize the most suitable location of the solar system, in order to produce a larger amount of renewable energy.

Numerical Analysis of Heat Transfer for Cooling of Photovoltaic Cells

AbstractPhotovoltaic cells are devices which convert solar radiation directly into electricity. However, solar radiation increases the photovoltaic cells temperature [1] [2]. The temperature has an influence on the degradation of the cell efficiency and the lifetime of a PV cell. This work reports on a cooling water technique for cells, whereby the cooling system was placed at the front surface of the cells to dissipate away excess heat and to block unwanted radiation. Using water as a cooling medium for the cells, the overheating of closed panel is greatly reduced without prejudicing luminosity and water acts as a filter to remove a portion of solar spectrum in the infrared band but allows transmission of the visible spectrum most useful for the PV operation. The aims of this study are to develop a 3D thermal model to simulate the cooling and heat transfer in Photovoltaic panel and recommend a cooling technique for the PV panel. In order to have a good estimation for the temperature distribution, the three‐dimensional flow and heat transfer across the cooling block is investigated numerically by solving the continuity, momentum and energy equations using FLUENT. The second objective of this work is to study the influence of the geometrical dimensions of the panel, water mass flow rate and water inlet temperature on the flow distribution and the solar panel temperature. The results obtained by the model are compared with experimental results from testing the prototype of the cooling device. (© 2014 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

10309 ソーラーパネルを裏面から冷却による温度低下の数値解析

The solar panel is heated by energy of radiation from the sun. The efficiency of electric transduction of solar panel is decreased with increasing temperature. Therefore, this paper described that the effect of cooling by natural re-circulation flow of solar panel temperature using two-dimensional numerical analysis. This numerical analysis was used OpenFOAM code based on PMPLE method. The solar panel was assumed the heating plate with the heat source. The inclination angle of the heating plate was 30 degrees, and the analyses were carried out by changing the ambient air temperature, the cooling water temperature and the amount of heat generation at heating plate. Results show that the temperature of the heating plate is decreased by cooling water and ambient air temperatures. This mechanism and relations are also discussed.