Solar Panels Research Articles

Experimental test of optimizing maximum power point tracking performance in solar photovoltaic arrays based on backstepping control and optimized by genetic algorithm

Maximum Power Point Tracking (MPPT) is a key component of modern solar photovoltaic (PV) systems. It improves the efficiency of PV power generation systems by inevitably reducing power losses. The most developed MPPT methods adopted like hybrid approaches combine algorithms with nonlinear controllers, such as backstepping controller (BSC). Despite their prevalence, there is still a lack of standardized procedures for tuning the parameters of these nonlinear controllers. In response to this challenge, a proposed method is adopted to identify the optimal gains using Genetic Algorithm (GA) for an efficient power tracking. The advantage of this strategy is established by real-time testing with the GA-BSC technique, which validates its capacity to generate appropriate controller gains for improved tracking performance. Experimental comparisons reveal that the modified GA-BSC approach significantly outperforms the conventional GA-BSC strategy. The conventional GA-BSC method falls short due to its use of non-optimal gains, leading to less effective reference voltage tracking and lower overall performance. In contrast, the proposed method benefits from optimal gains, resulting in enhanced stability and faster response times—achieving maximum power point tracking in 0.2 s compared to 0.6 s for the P&O-BSC method. Another experiment was conducted to test the robustness of the proposed method under variable irradiation profile. The results demonstrated the efficiency of the improved GA-BSC approach compared to other methods, which was more stable and faster. These improvements highlight the capability of the proposed method to enhance hybrid method efficiency, thereby leading to increased efficiency and reliability in photovoltaic systems.

Experimental Study and Performance Analysis of Thermoelectric Cooler Using Solar Photovoltaic Energy

Thermoelectric coolers need electrical energy to create temperature differences between the hot and cold sides; however, photovoltaic systems immediately convert solar radiation into electrical energy. The study is a combined (PV-TEC)—experimental study on a thermoelectric cooler operating by the Peltier effect to analyze and develop the TEC. One TEC was used, and its dimensions were (40*40*3.4) mm. The current required by the TEC is 6A and 12V DC. The thermoelectric cooler is electrically powered by a solar system consisting of two 660W solar panels, a solar charger and two 12V batteries. The results revealed a relationship between the coefficient of performance and the input energy, as the COP showed an increase as the input energy decreased, which is an essential factor for the cooling process. The temperature difference, which was the difference between ambient and cold temperatures, is related to the COP. The COP rises as the temperature difference decreases until it becomes stable. Moreover, the consumption current is an important factor in electronic devices, so the study focused on demonstrating the effect of the cold side temperature on the current, and an empirical equation was found between them. It has been found that a decrease in the temperature of the cold side leads to a sharp reduction in the consumption current until it stabilizes. The maximum coefficient of performance was 3.7436, obtained at the current 1.4 and cold side temperature of zero degrees centigrade. This high value of the coefficient of performance resulted from using curved fins to improve heat dissipation from the hot side.

PV integrated multi-leg powered constant quasi-dynamic charging system for low-speed vehicles

The global adoption of electric vehicles (EVs) is gaining momentum as countries strive to achieve sustainable development goals. Establishing charging infrastructure is of paramount importance to promote increased EV usage. The cost and weight of the batteries are factors that reduce the sales volume and popularity of EVs. A dynamic charging system has also been developed to enhance the driving range of EVs and mitigate the need for heavy storage requirements. The energy demand of charging infrastructure is increasing day by day. Many countries are installing solar arrays along the roadside to meet the power demand of highway lighting applications and achieve sustainable development goal (SDG) 7. To further enhance this system, this manuscript proposes integrating PV technology with the dynamic charging system. The PV arrays and energy storage system (ESS) collaborate to power the dynamic charging system. A multi-leg inverter is employed to energize the charging couplers, while a resonant network improves the power transfer capability of the couplers. On the receiver side, a resonant network ensures the delivery of constant voltage and constant current by tuning the network topology. The 3.3 kW five-legged inverter is developed to energize the four double-D-shaped charging couplers. The common DC bus delivers 350 V to the inverter, and the charging system delivers 350 V, 8.85 A to the EV batteries.

Experimental Comparison of Glazed and Unglazed Hybrid Solar Modules Considering Power Productivity and Cell Temperature

AbstractThis study presents the effect of cell temperature on the hybrid solar collectors PV/T for modules with and without using a front glass cover. A numerical model of thermal behaviour was carried out for glazed (PV/Tg ) and unglazed (PV/Tun) modules. As a result of this experimental investigation conducted for presented PV/T modules, a sufficient decrease in the cell temperature of PV/Tun compared to the PV/Tg, PV/Tun module exceeded the PV/Tg by 19%. Thus, the electrical productivity of the PV/Tun module was higher; it was 3.44% higher than the PV/Tg value. The outlet liquid temperature of the un-covered module was 6.34% higher than the outlet liquid temperature of the glass-covered module. Besides, the total efficiency of the PV/Tg was higher during the periods of study. In this sense, the glass-covered module is preferable for applications that deal with overall efficiency as a desirable factor. The un-covered module is much beneficial for applications that need high electrical productivity.

Modeling and manufacturing of solar modules of different designs for energy supply of biogas plant

The article presents a description of the modeling and manufacturing of solar modules of photovoltaic, thermal and photovoltaic thermal designs intended to supply energy to a biogas plant intended for the production of biohydrogen and biomethane. Mathematical modeling of the photovoltaic module was carried out and the calculated temperature of the photovoltaic converters was determined, and also the photovoltaic module was manufactured using the process of sealing the photovoltaic converters with a two-component polysiloxane compound. Mathematical modeling of a solar thermal collector with water radiators in the form of a round copper tube, an oval copper tube, as well as a rectangular water cooling channel (“water jacket”) was also carried out, in which pressure losses and the amount of water heating were assessed. The distances between the rectangular channels of the water-cooling radiator for uniform heat removal were determined, and mathematical modeling of the thermal state of a solar thermal collector with a semicircular cross-section of the water-cooling radiator channel was carried out, after which the solar thermal collector was manufactured. Mathematical modeling of the total displacements of the components of a photovoltaic thermal module, the values of which do not exceed acceptable limits, was carried out, after which a photovoltaic thermal module was manufactured using the process of sealing photovoltaic converters with a two-component polysiloxane compound.

Monitoring solar irradiance and PV module performance in mobile applications

The paper presents a comprehensive evaluation of a PV module attached to an electric vehicle using a custom developed PV monitoring system to estimate the effect of PV energy production on the driving range.A rigid crystalline silicon photovoltaic (PV) module with a nominal peak power of 192.4 W accompanied with four irradiance sensors (positioned horizontally and vertically to the left, right and back) was mounted on an electric car, and various driving scenarios were executed, with data recorded for analysis. The results of a two-month continuous monitoring of the car's usage mainly in the Central Slovenia region in late winter and early springtime, show that the daily energy generation by the installed PV module contributed an additional driving range of up to 5 km per day, totalling 93 km of additional range in the entire monitoring period. Based on irradiance monitoring results applied to a hypothetical case where all sides would be covered with a state-of-the-art PV, the driving range would extent to 471 km in total for the same period. When compared to a fixed, ideally installed PV module at our outdoor PV monitoring site in Ljubljana, the average performance ratio (PR) of the mobile PV module in the two-month period was 87 %, whereas the PR of the fixed installed PV module was 83 %. The energy yield varied significantly under the varying conditions resulting from different car usage scenarios and on average it reached 41 % of the fixed PV module's energy yield. Through real-world experiments and data collection, different car use cases under various driving and parking conditions are presented and evaluated in detail. From these, the base specifications of a dedicated mobile VIPV monitoring system are identified.

Integrating Bayesian inference and neural ODEs for microgrids dynamics parameters estimation

The integration of solar and wind energy sources in microgrids has witnessed significant growth, giving rise to distinct challenges due to their intermittent nature when it comes to achieving efficient microgrid control. However, estimating the parameters of the dynamic microgrid components facilitates capturing the complex and time-varying characteristics of renewable energy generation. This requires an accurate estimation of the parameters from the dynamic differential equations for effective modeling and control. In this research paper, we presented a novel methodology based on the integration of Bayesian inference and Neural ODEs. The Bayesian inference quantifies the uncertainty, and the Neural ODEs model the dynamic systems. By combining the strengths of both methods, we aimed to achieve a precise and robust parameter estimation of the dynamic microgrid components. The methodology is validated on a simulated microgrid that consists of a diesel generator, Solar PV array, double-fed induction generator, and a battery energy storage system. The results showed promised inferences estimation obtained from the parameter posterior distribution even in the presence of uncertainty. This can enhance our understanding of the dynamics of renewable energy systems and can contribute to the advancement of decision-making microgrid control strategies.

Design and implementation of a dual-axis sun tracker for an Arduino-based micro-controller photovoltaic system

This research investigates the optimization of solar panel performance by designing and implementing a low-cost Dual-Axis Sun Tracker (DAST) for an Arduino-based Microcontroller Photovoltaic System. The primary aim is to enhance solar energy extraction by precisely aligning the panel perpendicular to the sun's position, maximizing output voltage and current efficiency compared to fixed systems. The DAST employs two micro servo motors, SG90, controlled by a specialized chronological algorithm in offline mode, ensuring strategic alignment and scheduled adjustments. A comprehensive evaluation of the DAST's performance is conducted, contrasting it with a Fixed System to underscore the advantages of solar tracking. As a result, a DAST produces higher output than a fixed system by 0.896W during sunny days and 0.206W during cloudy days. Besides, the efficiency of PV panels in the DAST is 71.65%, and fixed is 49.66% during sunny days, while DAST is 22.96% and fixed is 17.91% during cloudy days.

Teaching and Learning with Technology: Effectiveness of usage of Information and Communication Technology (ICT) Facilities in Public Primary Schools in Ondo State, Nigeria

The use of Information and Communication Technology (ICT) in schools is a worldwide requirements meant to replace traditional teaching methods with a technology- based teaching and learning tools and facilities which will assist teachers in their day to day activities of teaching, keeping of records among others. This study aims to analyze the importance of ICT usage to support teaching and learning process in the classroom and also to ascertain the Effectiveness of ICT usage for pupils learning. It also finds out the challenges of usage of ICT facilities in public primary Schools. The findings from the study revealed that computer and internet facilities affected the Educational system better than before. Usage of ICT facilities in public primary Schools will improve the teaching and learning process. The following challenges were revealed from the study: lack of technical support/ Skills, problem of electricity, network issues inadequate ICT facilities in schools among others. It was therefore recommended that the government should give utmost priority to training of teachers in ICT usage. ICT specialist should be recruited and posted to each public primary School to provide technical support to other members of staff, Electricity should be improved upon or solar panels to be provided to schools. Teachers and pupils should be provided with ICT facilities such as educational tablet to improve their ICT usage for teaching and learning.

Hybrid energy-based electric vehicles charging station integrated with INVELOX wind turbine: A case study of Kermanshah

Global warming from fossil fuels is a growing concern for governments. A potential solution is using renewable energy microgrids, which reduce dependence on the power grid. On the other hand, Electric vehicles are a solution to combat environmental pollution as they emit no harmful pollutants compared to conventional vehicles. However, charging these vehicles can lead to congestion, reliability, and resiliency issues for power systems. To address this issue, renewable energy sources are being utilized to ease the burden of electric vehicles on power grids. Therefore, this paper assumes a proposed microgrid's planning and management in Kermanshah city and uses unique renewable energy sources such as the INVELOX wind turbine and common photovoltaic panels by utilizing Homer software. Results show that for the first scenario, excluding PV panels, the NPC is $432,173. Adding PV panels reduces the optimized NPC by 53 % to $282,523. Sensitivity analysis highlights the impact of inflation, fuel prices, and PV longevity. In the second scenario with the INVELOX wind turbine, the NPC without PV is $373,199, with $26,070 in annual repairs. Adding PV panels decreases the NPC to $253,405 and maintenance to $14,288, showing significant cost reductions. Novel technologies like INVELOX and PV panels enhance microgrid cost efficiency and environmental impact.

Research on probabilistic analysis of trapezoidal triangle truss

As a region affected by the Mongolian Siberian high-pressure system, the Northeast area of China faces extreme low temperatures and snowy weather in winter, which poses a high demand for local energy. As a relatively mature sustainable energy source, laying solar photovoltaic panels on the roofs of residential buildings relied on sufficient local sunlight resources has become a feasible measure. From the perspective of engineering safety, this paper studies the stability of a single span double slope roof steel truss with added solar photovoltaic panels under snow loads. First, the types of loads on the truss are analyzed, assuming the distribution of the load and capacity of any member in the truss structure. Then, Monte Carlo algorithm is used to simulate the failure probability, and finally the failure probability of the member as well as the overall structure is obtained. As a conclusion, this paper finds that the stability of this structure is basically not affected by the above factors, and this provides certain reference significance for balancing safety and economic benefits in practical engineering design.

Space solar power project and a theoretically performable solar energy policy with some proposed improvement measures for energy transition in the future

ABSTRACT For the renewable energies (REs), solar power generation is currently the most common. Some countries are currently competing to develop Space Solar Power (SSP) projects, hoping to take the lead in this race to obtain energy from space with high conversion efficiency. In Taiwan, the SSP generation project is expected to cost US$4 billion in research and development in the next five years, and subsequent costs will be astronomical. From an energy management perspective, these proposed improvement measures will be powerful to improve the effectiveness of generating electricity for the SSP system and the solar panels on the ground, so that obtained energy from them can be integrated into an integrated energy (IE), as well as corresponding recycling measures and a reliable energy storage system (ESS) are used. This ESS can store much solar energy to avoid the phenomenon of duck curve and negative electricity prices. Therefore, combing with the concept of the IE, there is a theoretically performable solar energy policy for energy transition in the future. However, in Taiwan, such energy transition using the REs concerns must be considered not only in terms of energy availability at an affordable price, but also from a political and social perspective.

Hybrid offshore wind–solar energy farms: A novel approach through retrofitting

Due to the inherent variability of the power output of offshore wind farms, their integration into electrical grids poses a challenge to their stability and leads to significant balancing costs. Combining wind and solar power may be expected to mitigate the power output variability. In addition, a number of synergies can be realised—shared infrastructure, shared crews and vessels for operations and maintenance, and last but not least, optimum use of scarce marine space. The objective of this work is to investigate this hybrid approach and, in particular, to determine the optimum capacity of the solar energy subsystem given a certain installed capacity of the wind energy subsystem. Three case studies are considered in Europe and China. Each of them is an existing wind farm that could be retrofitted with floating solar PV. After assessing the local wind and solar energy resources, the optimal size of the floating solar array is calculated with a view to smooth the aggregated power output of each farm. Subsequently, the benefits of this hybrid approach are demonstrated from various perspectives. It is found that a much larger solar array is required for a wind farm with a large installed capacity, but the specific optimal size depends more on the local wind and solar resources. The novelty of this paper lies in its exploration of retrofitting existing offshore wind turbines with floating solar PV systems from the perspective of addressing the variability challenge for the currently operating wind farms. This study could serve as a guideline for project designs aiming to retrofit existing offshore wind farms with solar PV technology, thus reducing balancing costs and facilitating the penetration of offshore renewable energy into national power grids.

A quick comparison model on optimizing the efficiency of photovoltaic panels in collecting solar radiation

Few scholars study light efficiency of solar-cell arrays in theory, while it is difficult to experimentally determine the maximum capacity of a photovoltaic panel to collect solar radiation. This paper proposes a solar energy comparison model (SECM), considering the sunshine duration changes every day to optimize the solar radiation collection model in an ideal state for a whole year, which is easy to use, and can quickly obtain the optimal tilt angle of photovoltaic panels and the solar radiation collecting efficiency enhancement of intelligent light tracking photovoltaic panels. The results show that the sunshine duration is an important factor affecting the solar radiation received by photovoltaic panels. In regions from 66°34′N to 66°34′S, intelligent light tracking photovoltaic panels can increase the collected solar radiation by at least 63.55%, up to 122.51% compared to stationary photovoltaic panels during the effective light time, which is much higher than what most people generally thought. And the advantage of intelligent light tracking photovoltaic panels is more obvious in high latitudes, with a longer and more variable sunshine duration. These findings provide a theoretical basis for the solar radiation collection and photovoltaic panels.

Experimental Study on the Influence of External Heat Flux and Air Pressure on the Combustion Characteristics of Solar Panels

Experimental Study on the Influence of External Heat Flux and Air Pressure on the Combustion Characteristics of Solar Panels

UV LED ageing of polymers for PV cell encapsulation

Encapsulation polymers in terrestrial solar modules degrade due to ultraviolet radiation from the sun. To assess a polymer’s durability under UV light, accelerated aging tests can be conducted. A new LEDs device allows us to investigate the effects of temperature, irradiation, and UV source spectrum on the photooxidation mechanism and kinetics of two polyethylene-based commercial encapsulants, differentiated by the presence or absence of UV absorbers. The photooxidation rate of the polymer matrix increases as the temperature and irradiance increase between 62 and 82 °C, and 12 and 28 W.m−2, respectively. In the last case, the photooxidation rate is not proportional to the number of photons. Finally, we observed different distributions of degradation products under UVB radiation at 305 nm compared to those under UVA radiation at 365 nm. UVB photons enable Norrish reactions that are not possible with UVA alone. Special care is needed to maintain a balance between UVA and UVB photons to ensure representative durability tests. With a few adjustments to their emission spectrum, UV LED devices appear to be good candidates for accelerated aging of encapsulation polymers.

Investigation on the operation performance of solar panels cooled by a natural draft cooling system

This paper is to investigate the feasibility of a natural draft cooling system for PV panel cooling in a typical hot and dry region (Hami, Xinjiang, China). A 3-D model of PV panels cooled by a natural draft cooling system is established using Fluent 2020R2 software, and the cooling effect of the natural draft cooling system on PV panels is simulated and analyzed based on the meteorological data of Hami, China. Simulation finds that the natural draft cooling system can reduce the average temperature of the PV panels. The minimum temperature drops of the PV panels in January (represents winter season), April (represents spring season), July (represents summer season) and October (represents autumn season) of the year 2020 are 1.7 °C, 3.1 °C, 6.1 °C and 2.5 °C, respectively; while the maximum temperature drops of the PV panels are 7.0 °C, 11.2 °C, 15.5 °C and 6.3 °C, respectively. Besides, the natural draft cooling system is also compared with the PV panels without cooling system in six typical days, and finds that the PV panel with a natural draft cooling system increases the photoelectric conversion efficiency by up to 1.41 % (i.e., from 13.71 % to 15.12 %) when compared with the PV panel without cooling. Therefore, the proposed natural draft cooling system can effectively reduce the temperature of PV panels in Hami, Xinjiang.

ANALISIS PERBANDINGAN KINERJA SISTEM PENDINGIN PV DENGAN CAIRAN AQUADES, AIR SUMUR, DAN TANPA PENDINGIN DENGAN MONITORING IOT

Solar Power Plants are an environmentally friendly energy source that utilizes sunlight energy which is converted into electricity. However, solar panels must maintain their performance. One of the impacts is that solar panels cannot work optimally if the temperature of the solar panels exceeds the safe temperature. This research examines the factors that cause the performance of solar panels to not work optimally, when the surface temperature of the solar panels is too hot and exceeds the safe temperature limit, then tools are needed to help the solar panels so that the working temperature is not too high. The technology used to control the temperature of solar panels is by utilizing IoT by maximizing the DS18B20 sensor and voltage sensor, to read the surface temperature of the panel, which will then wet the surface of the solar panel with distilled water and well water automatically if the surface temperature of the panel exceeds the safe temperature on the solar panel. And later you can monitor the temperature of the panel with a smartphone and also observe whether distilled water and well water can reduce the temperature on the surface of the panel. When collecting data, it can be compared to when without using cooling, the temperature on the panel is above 33 degrees. Meanwhile, when using a cooler the temperature obtained decreases. The well water cooler produces a temperature of 32 degrees, while the distilled water cooler produces a temperature of 30.5 degrees. It can be concluded that distilled water can reduce the temperature of the panel, so it can make the panel work optimally. So, in order to maximize the performance of the panels to utilize solar power, in this research, distilled water is very good for lowering the temperature on the surface of the panels.

Analyzing the impact of temperature on PV module surface during electricity generation using machine learning models

Use of fossil fuel in industries causes Carbon emission, which is mostly responsible for global warming. Another aspect is that environment friendly energy production and sustainable development goal is highly dependent on the production of clean energy. According to the IEA solar energy has a huge potential and will contribute up to 16 % of the global electricity by 2050. Hence, prediction of solar energy production has a great deal of demand in renewable energy sector. This paper compares machine-learning algorithms to evaluate the impact of PV module back surface temperature (degC) on the generated power. Support Vector Machine for Regression (SMOreg), Multilayer Perceptron (ANN), Linear Regression, M5 Rules, k-Nearest-Neighbor (Ibk) and Random Forest methods are employed to test their performance in different ratio of training and testing data. The dataset comprises five independent parameters such as PV module back surface temperature (degC), Dry bulb temperature (degC), Relative humidity (%RH), Atmospheric pressure (mb), and Precipitation (mm). The dependent parameter is Maximum power of PV module (W). The correlation coefficient was determined by varying the percentage of training data from 60 % to 85 %. The numerical tests were done for two data sets, one dataset includes all the independent variables and another one excluded the PV module back surface temperature. Except for M5 Rules, other models exhibit consistent correlation coefficients with several of training data. All models demonstrate a dependency on the PV module back surface temperature, with Random Forest surpassing others in overall performance with a correlation coefficient of 0.9713 at 75 % of training set.

Differentiable programming for gradient-based control and optimization in physical systems

This paper presents an exploration of the application of control theory, particularly utilizing a gradient-based algorithm, to automate and optimize the operation of photovoltaic panels and refrigeration systems in warehouse environments. The study emphasizes achieving coordination between energy generation and consumption, specifically harnessing surplus solar energy for efficient refrigeration. The complex interplay between fluctuating solar irradiance, thermal dynamics of the warehouse, and refrigeration needs underscores the significance of control theory in designing algorithms to dynamically adjust PV panel output and refrigeration system operation. The paper discusses foundational control theory principles, proposes a tailored framework for warehouse operations, and highlights the potential for sustainable energy practices. This paper explores the use of data-driven approaches based on NeuralODEs vs classical ones using physics equations.