Solar Panels Research Articles

Comparative analysis of single-axis solar tracker performance with and without reflector under various weather conditions

This research explores a sun tracking system for solar panels that affects the power output of the panels. To address this, a unidirectional sun tracking system is implemented to ensure the solar panels are perpendicular to the sun, thus optimizing solar radiation. Additionally, reflectors are integrated to capture more sunlight. This research aims to design the system of unidirectional sun tracking to enhance the power output generated by solar panels and compare its performance with stationary (static) solar panels. The results demonstrate that the system of sun tracking improves the power output of solar panels. However, when reflectors are used in conjunction with the sun tracking system, no significant increase in power output is observed. Moreover, solar panels equipped with the unidirectional sun tracking system exhibit a power increase of 52.06 Watts compared to stationary solar panels. This research indicates that employing a unidirectional sun tracking system with the addition of reflectors does not enhance power output but instead reduces it due to the increased temperature effect caused by the sunlight reflection from the added reflectors.

Do laundry when the sun shines: Factors that promote loadshifting in Dutch households with solar panels

The installation of solar panels by residential households is vital for the energy transition. However, the rapid uptake of solar panels by households leads to congestion in the electricity grid. Specifically, when the sun shines, these solar panels simultaneously produce a lot of electricity that is fed into the grid, which is inefficient and can destabilize the grid. Consequently, it is better if self-produced solar energy is directly consumed when the sun is shining. Loadshifting involves shifting energy use (e.g., doing laundry) to periods in which energy is produced. This necessitates behavior change within the household, and it is not yet well understood why people struggle to loadshift. To assess the individualistic and contextual factors influencing laundry loadshifting behavior in the Netherlands, we conducted a survey among 283 Dutch households with solar panels. The survey builds on a framework that integrates aspects of the theory of planned behavior and social practice theory. The framework comprises eight factors (sufficiency attitude, user beliefs, know-how, monitoring skills, habits, hassle, practical knowledge provided, and feedback provision by system design), which are quantitatively measured and analyzed. We used multiple regression analysis to explore the collected responses. Results show the relevance of monitoring skills, strong habits, passive user beliefs and practical knowledge for laundry loadshifting behavior. Findings highlight that instead of asking people to adjust to technologies, technologies should support behavior change and understand its intricacies and connections to its broader context. Additionally, it is important to strengthen households' beliefs regarding their active role in the energy system.

Performance analysis of different control models for smart demand–supply energy management system

Several features of innovative grid technologies can be deployed to improve the overall performance of the power system environment. This can be seen from the generation to the consumption of energy. The two-way communication of smart metering introduces the novel functionalities of the energy management system. This paper presents a practical implementation of using the intelligent metering system. It consists of implementing a nanogrid that optimally coordinates the energy from the solar panel, battery storage and utility grid to supply the end user. The developed model is validated with an optimal value of the state of charge of the distributed energy storage to maximise energy from the solar panel and battery storage while minimising the power received from the utility grid. A demand response scheme is employed to formulate the performance index of the energy management system using three optimal control models: adaptive open-loop control, adaptive closed-loop control and model predictive control schemes. The formulation of the performance index of each approach is a function of the energy flow from different resources depending on the power consumption. The three models have given different insights into the performance of the smart nanogrid, which may be used to the advantage of the grid owner or end user. Through the performance of the optimal strategies, it can be observed that energy management is ensured, and real-time monitoring of the entire system is guaranteed. The performance models facilitate the minimisation of the power from the utility, resulting in savings between 23.7% and 39.240% of the total energy demand from the end user. Besides, the system design is validated by an electrical system to form a real-world innovative nanogrid application in residential environments.

High transmittance BiVO4 thin-film photoanodes by reactive magnetron sputtering for a photovoltaic-photoelectrocatalysis water splitting system

As the system with the highest solar hydrogen conversion efficiency, the further improvement of photovoltaic-photoelectrocatalysis (PV-PEC) efficiency is dependent on the light transmittance, activity and stability of the photoanode. Here, a highly permeable BiVO4 thin film was fabricated through controlled magnetron sputtering. The thickness of the thin film was merely 345 nm, while its transmittance in the visible light range reached as high as 70%. Moreover, large-scale production of such films could be achieved. By incorporating NiFeOx oxygen extraction cocatalyst, under AM 1.5G illumination, the photocurrent density at 1.23 V on reversible hydrogen electrode (RHE) increased to 4.2 mA cm–2 and the incident photon-current conversion efficiency reached 70%. A PV-PEC system was designed to efficiently harness sunlight by integrating the photoanode with a solar photovoltaic panel. Upon connection with the solar photovoltaic panel (with an efficiency of only 7%), spontaneous water decomposition could be achieved, resulting in a solar-to-hydrogen conversion efficiency (ηSTH) of 4.2% for the series system. This study contributes to the realization of cost-effective and highly efficient PV-PEC hydrogen production.

Multi-microgrids system’s resilience enhancement

Nowadays, electricity consumption is increasing rapidly which leads to conventional power systems exhaustion. Therefore, micro-grids (MGs) implantation can enhance the resilience of power systems by implication of new resources, such as renewable energy sources (solar panel and wind power systems), electric vehicles (EV), and energy storage systems (ESS). This paper proposes a new strategy for optimal power consumption inside one microgrid; then, the approach will be extended to optimize the power consumption to enhance the resilience in the case of multi-MGs systems. The system controller of each microgrid has been implemented using ESP32 microcontroller and Raspberry IP4. The proposed approach intends to enhance the resilience of the system to react to any contingency in the system such as loss of power linkage between MG and the network in case of any natural disaster, especially in the rural area. Two controllers are implemented; the first one ensures MG autonomy by the efficient use of its own sources. The second one handles the system resilience cases by demanding/delivering power from/into neighbor microgrids. Hence, this work enhances the system resilience with an optimal cost. Thus, the MG can offer ancillary services for the neighboring MGs.

Optimizing photovoltaic systems performance under partial shading using an advanced cuckoo search algorithm

Partial shading negatively impacts power output in photovoltaic systems (PVs), causing multiple local maximum power points (LMPP) instead of a single global maximum power point (GMPP). The cuckoo search (CS) technique utilizes the maximum power point tracking (MPPT) technique to extract the global maximum power (GMP) from shaded PVs. CS is a metaheuristic technique that has gained widespread recognition. Moreover, the CS algorithm is associated with several challenges, including a failure rate, long response time, and noticeable oscillations during steady-state operation. To address these limitations, our proposed advanced cuckoo search (ACS) algorithm is designed to overcome the shortcomings of the standard CS algorithm. The algorithm iteratively evaluates individual solar panels and collectively explores the solution space using levy flight operations. Persistent variables are used to store and track the current state and previous iterations. Where the duty cycles of the solar panels are optimally set to enhance the overall power generation efficiency. We also evaluate and analyze the results obtained from the performance of our proposed technique and compare them to the performance of the four most recent CS optimization techniques. for all test cases, the tracking efficiency was improved to 99.98% with a fast-settling time of <44 ms.

Design of actuator motor acceleration model in dual axis tracker movement for stand-alone PV system

Stand-alone photovoltaic system or PV is a power generation technology with potential that is environmentally friendly and also one of the solutions for saving high electricity rates today. However, problems that often occur due to weather fluctuations that are always changing, especially North Sumatra, Indonesia result in the conversion produced by solar cells not being optimal. Therefore, it is necessary to do a new model with a dual tracker system and the development of accelerator motor actuators so that the resulting energy conversion is more optimal. The result of optimizing the reliability of the polycrystalline type solar panel which is designed with an additional photovoltaic tracker system to maximize the conversion of solar energy to solar panels is to obtain an output power of 303.72 volts DC and 267.52 volts DC in the position where the tracker is not used. Then the percentage increase in energy reached 29.80%. Dual axis tracker technology is able to maximize energy conversion in improving PV usage performance. The implementation of a stand-alone PV system will be beneficial if the installation is in Indonesian territory, especially in disadvantaged, frontier and outermost areas.

Combining solar panels with plants for sustainable energy and food production: state of the art

The need for alternative energy sources becomes extensive because of the escalating cost of fossil fuels. The goal of this paper is to examine the effectiveness of combining photovoltaics and agriculture for better yield. Photovoltaic (PV) solar plants will compete with farms for available land. In this study, the methodologies are discussed how it is possible to maximize land utilization by placing solar arrays and food crops on the same plot of land. The term is proposed "agrivoltaic system" to describe this setup. Conventional solutions (discrimination of agricultural and energy extracting) were compared to two agrivoltaic schemes with varying density of PV arrays using land equivalent ratios. We utilized a crop model to simulate the amount of sunlight reaching the crop from an array of solar panels and to speculate on the yield reduction that would result from the partial shading. These early findings suggest that agrivoltaic systems may be highly effective; the two densities of PV panels were anticipated to boost worldwide land production by 73%. One possible explanation for the success of these hybrid systems is the presence of facilitation mechanisms analogous to those seen in agroforestry. At the end it is suggested that in places where arable land is rare, new solar plants may find it beneficial to produce both power and food.

Investigation on implementing the swarm nano grid system for effective utilization of solar-powered agro-industries

The agro-industry is the backbone of the global economy, even in the twenty-first century. The agro-industry would not be what it is now without irrigation. The production and use of renewable energy in this sector of the agricultural economy have also expanded rapidly in recent years. Base-load power production and conversions dominate the literature. This research examines user concerns. The swarm nano grid system fixes this. The pulse width modulation (PWM) sinusoidal inverter converted stable DC power from the bidirectional DC-DC converter into sinusoidal AC voltage for the irrigation pump induction motor. Solar panels, batteries, and converters are costly, but they pay off. The nano grid distributes excess power generated during low demand to local loads. This technique works well when the load can be disconnected from the power grid. MATLAB is used to keep an eye on the reliability and efficiency of the induction motor. In the first simulation, solar power generation is modeled using the MATLAB Simulink software in two distinct modes. A PWM sinusoidal inverter that is driven by solar energy is what provides power to the 5.67 kW induction submersible motor. The simulation result provides a conceptual model of how induction motors powered by renewable energy sources function in practice.

Particle swarm optimization based sliding mode control for maximum power point tracking in solar PV systems

One of the most significant renewable energies is photovoltaic (PV) energy, however it has a low efficiency due to its variable maximum power point that depends on weather conditions. In order to guarantee the system's best performance, intelligent algorithms can effectively track this point in real-time utilizing the maximum power point tracking (MPPT) method. Consequently, it is crucial to maximize the use of the solar energy that has been captured as well as the PV system's generated electricity. Variations in solar irradiance affects the amount of electric energy obtained from solar arrays. For efficient extraction of electricity from solar PV systems, MPPT algorithms are required. Sliding mode control (SMC) can be used in the control of nonlinear systems. However, the effectiveness of SMC can be improved by the choice of the sliding coefficients. In this paper, optimal search using particle swarm optimization (PSO) is used in the design of the sliding manifold. Results obtained via simulations showed that MPPT tracking efficiencies obtained for the PSO based SMC and the conventional SMC are 99.65% and 96.79% respectively. That means, PSO based SMC is 2.86% better than conventional SMC.

Design and Performance Analysis of Photovoltaic Power Generation Light Emitting Diode Device

This research focuses on an independent photovoltaic power generation system with supercapacitor energy storage as the study subject. The model is simplified, and the photovoltaic power generation light emitting diode (LED) device is designed based on the given parameters. This system selects a Boost-type step-up converter for the supercapacitor charging circuit, capable of achieving Maximum Power Point Tracking (MPPT). The supercapacitor discharge circuit employs an LM2596 series regulator to power the rated load LED (12 V, 1 W), providing good linear regulation capability. In designing other hardware components of the device, the characteristics of a photoresistor are utilized to implement an automatic load switch circuit. An efficient single-chip integrated circuit LM2575 series is used as a regulator to convert the voltage across the supercapacitor terminals to +15 V and +5 V. Considering the need to collect the output voltage of the photovoltaic cell array and the voltage across the supercapacitor terminals, a resistor divider method is used to sample these two voltages. The sampling circuit includes a resistor divider circuit and a linear optocoupler isolation circuit. An HNC-25LTS series Hall current sensor is used for current sampling to measure AC, DC, and pulse signals under electrical isolation conditions. The supercapacitor, solar photovoltaic panel, control unit, and the main circuit for supercapacitor charging and discharging have been assembled in the experiment. Connecting the charging and discharging circuit with the photovoltaic panel and LED, the system provides power to the LED during the night. Under varying light intensity and temperature conditions, the photovoltaic output voltage waveform, PWM waveform, and Boost circuit output voltage waveform remain stable when reaching the MPPT point. The output power with added MPPT control at different times is compared. The results indicate that the designed system has effectively achieved the functionality of MPPT for solar energy.

Solar Tracking and Monitoring System

Abstract: We will eventually have to deal with the depletion of fossil fuels and other non-renewable energy sources as they are running out rapidly. Having a large number of renewable alternative energy sources is crucial. The sun's radiation properties meet both requirements. As a result, new technologies focused on solar energy harvesting are starting to appear. Concentrated or photovoltaic panels may yield the highest efficiency. Due to the planet's rotation, which causes humans to view the sun at different times of the day the efficiency may reduce. Devices that direct a solar panel or concentrating panel during the day are incorporated in the design, along with light-trackers to boost the system's effectiveness. A solar tracker can monitor the sun's radiation in single direction. The device monitors daily tilt of the sun for optimal performance. The work focuses on the fundamentals of solar panel parameters and their application, as well as the design and construction of an automatic solar tracker prototype utilizing Arduino code based on microcontroller. By simulating the sun's 12-month tracking in a matter of minutes, the device incorporates automation mechanisms into the tracking system.

Evaluation of Optimum MPPT Controllers for PV Cells using Matlab Simulink Platform

Abstract: Nowadays, the Photovoltaic cell is one of the most essential parts in the electrical field to convert photo light to voltage and current, at the desired output voltage and frequency by using various control techniques The Solar panel can produce maximum power at a particular operating point called Maximum Power Point (MPP).To produce maximum power and to get maximum efficiency, the entire photovoltaic panel must operate at this particular point. Maximum power point of PV panel keeps on changing with changing environmental conditions such as solar irradiance and cell temperature. Thus to extract maximum available power from a PV module, MPPT algorithms are implemented. The output power of a photovoltaic (PV) module depends on the solar irradiance and the operating temperature; therefore, it is necessary to implement MPPT controllers to obtain the maximum power of a PV system regardless of variations in climatic conditions. This project reviews the most used MPPT algorithms, which are Perturb and observe (P&O), Incremental conductance method (ICM), and Fuzzy logic control (FLC).

All in One Robot for Military Purpose

Abstract: The "All in One Robot for Military Purpose" project is an innovative and comprehensive robotic system designed to fulfil a range of critical functions for military operations. This multifunctional robot integrates various advanced features including line following, obstacle avoidance, IR remote control, voice control, and mobile application-based control, ensuring versatile and adaptable operation in diverse environments. Additionally, the robot incorporates specialized systems such as landmine detection, RADAR technology, unwanted activities detection, fire detection, GPS navigation, and solar panel power supply.

Carbon Footprint of a Nearly Zero Energy Building in Accra (Ghana): an LCA-based Model

This study presents a comprehensive Life Cycle Assessment (LCA) of a Nearly Zero Energy Building (NZEB) in Accra, Ghana, comparing its environmental impact with a conventional Business-As-Usual (BAU) building over a 50-year lifespan. Adhering to ISO 14040 and ISO 14044 standards, the research evaluates the carbon footprint and operational efficiencies essential to sustainable building designs. Utilizing SimaPro 9.5 software and the IPCC 2021 GWP100 method, the total carbon footprint was quantified at 1727 tons of CO2-equivalent for the NZEB, significantly lower than the BAU comparison. The analysis highlights the operational phase, including waste generation as the most substantial contributor to the NZEB's environmental impact, accounting for 725 tons of CO2-equivalent emissions. Conversely, the strategic inclusion of solar panels and enhanced material selection for the NZEB markedly reduced energy demands, contributing to a net positive environmental outcome with an avoided carbon footprint of approximately -859.72 tons CO2-eq. This reduction underpins the NZEB's effectiveness in leveraging eco-friendly materials and renewable technologies, setting a benchmark for future sustainable construction practices. The study ultimately advocates for an integrated approach, harmonizing technological innovation with environmental stewardship, to mitigate the carbon footprint of the built environment, steering the construction industry towards sustainability.

Selection of optimal strategy for managing decentralized solar PV systems considering uncertain weather conditions

Solar power is a promising source of energy that is environmentally friendly, sustainable, and renewable. Solar photovoltaic (PV) panels are the most common and mature technology used to harness solar energy. Unfortunately, these panels are prone to dust accumulation, which can have a significant impact on their efficiency. To maintain their effectiveness, solar photovoltaics s must be cleaned regularly. Eight main techniques are used to clean solar panels: natural, manual, mechanical, robotic, drone, coating, electrical, and acoustic. This study aims to identify the best cleaning method using multiple criteria decision-making (MCDM) techniques. Using the Analytical Hierarchy Process (AHP), Quality Function Deployment (QFD), Fuzzy Technique for Order of Preference by Similarities to Ideal Solution (FTOPSIS), and Preference Selection Index (PSI), this research evaluates all eight cleaning methods based on several criteria that are categorized under cost, performance, resource requirement, and safety in Abu Dhabi. The data are collected from surveys completed by experts in solar and sustainable energy. The AHP, QFD, and PSI results identified natural, manual, and surface coating as the best and most effective cleaning methods. Natural cleaning involves using rainwater primarily to remove dirt and dust; manual cleaning requires cleaning agents and wiping clothes; and surface coatings involve applying a layer of hydrophobic material to the panels to repel dust. Identifying the most effective cleaning method for dust removal from solar panels can ensure optimal efficiency recovery at minimal costs and resources.

Modeling, simulation, and experiments of a flexible track robot over rigid horizontal and inclined surfaces

This paper studies the locomotion of a robot fitted with flexible rubber tracks while driving and climbing over rigid horizontal and inclined surfaces. We developed a model that accounts for sliding during rotation and the distribution of the normal forces along the track. On horizontal surfaces, we found that the size of the robot (width and length) and the normal force distribution along the track had a substantial influence on its turning speed and radius, whereas the coefficient of friction (COF), the robot's mass and inertia had a much lesser influence. The model shows that on inclined surfaces, even on relatively small slopes, the robot substantially slides downwards as it tries to rotate. The results of the model and the simulations were validated using a tracked vehicle that was built and tested on a solar panel. The experimental results of the turning radius and rotational speed were within 2% of the model (see video).

Assessment of reliability measures and cost optimization of a solar seed sowing machine

PurposeIn this research work, the general form of reliability measures, which include availability, mean time to failure (MTTF), and sensitivity analysis, are investigated with their graphical representation, which would help designers and engineers improve the reliability of the system. Along with reliability assessment, a mathematical model is developed and solved to achieve the minimum cost of the system as well as maximum reliability.Design/methodology/approachIn the proposed work, a general model of a solar seed sowing machine is considered for reliability evaluation using the Markov model process. The proposed system is a series-parallel arrangement of components where three components, namely the solar panel, batteries and direct current (DC) motor, are connected in series while all the operators are connected in parallel. The implemented Markov model approach assesses several parameters of reliability, which opens the scope for improvement in reliability and other measures like mean time to failure (MTTF) and sensitivity of the proposed system. So that the machine can deliver the desired output on the field. Also, the particle swarm optimization (PSO) algorithm is applied to optimize the cost of the system with the desired level of reliability.FindingsImplementation of PSO provides the optimal cost for the proposed system with a predetermined level of reliability, which shows the relationship between reliability and cost of the system. Also, the Markov process approach provides the availability function, reliability function, reliability at different time values, MTTF and sensitivity of the proposed system.Originality/valueThis work evaluates the crucial characteristics of reliability for the proposed solar seed sowing machine using the Markov model which is a stochastic model. The assessment of reliability measures such as MTTF, availability and sensitivity plays a vital role in measuring and improving the performance of the machine in the actual environment. Examining the data obtained in this research is of great importance for the manufactures and system designers. Also, the powerful optimization technique PSO is implemented to solve a non-linear mixed-integer programming problem that provides the optimal cost for the system with desired reliability.

Impact of string connection and contact defects on electrical current distribution in solar cells and modules: A model validated by magnetic field imaging

AbstractModeling of solar modules and their components is essential to quantify geometrical, optical, and electrical losses and to improve the designs and technologies in terms of performance. In most loss analysis models, the current share among the busbars of the solar cell is assumed to be equal since a symmetrical distribution of the metallization is given. The impact of string terminal connection on the current distribution among the ribbons and the resulting changes in ohmic losses has not been studied yet. In this study, a MATLAB model is developed to consider the impact of the string connector terminal position on the current distribution and the ohmic losses in the ribbons and in string connector. The model allows for the analysis of the impact of contact defects scenarios in ribbons and string connectors on the current distribution. Results show that the highest current flows at the closest busbar to the string connector terminal while the current decreases at the busbars farther away from the terminal due to higher ohmic resistance of the current path. The higher the ohmic resistance of the string connector, the more inhomogeneous the current share at busbars. Simulating a 9 busbar M6 half‐cell with 1 × 0.08 mm2 string connector, positioning the string connector terminal at the leftmost or rightmost ribbon results in 0.4 W less power compared to center connection configuration, where the string connector terminal is positioned at the center ribbon. Furthermore, simulation results show that inhomogeneity of current causes about 2.1% reduction in module power compared to the case of evenly distributed cell current, considering a 120‐haf‐cell module with the same string connector. Regarding contact defect analysis, exemplary simulations show the impact of the position of detached ribbons on the power or efficiency loss. Considering left or right connection configuration, detaching the leftmost or rightmost ribbon results in higher power loss compared to other ribbons. Detaching one cell ribbon completely from the string connector results in about 0.2%abs decrease in cell efficiency, while detaching the outer ribbon along all strings of a 120‐half‐cell module results in power loss of about 0.8%. The developed model is validated by performing magnetic field imaging (MFI) measurements, in which the magnetic flux density induced by the current carried by the ribbons is measured.

Maximum power point tracking using unsupervised learning for photovoltaic power systems

ABSTRACT The Maximum Power Point Tracking (MPPT) technique in the solar energy field optimises the performance of solar panels in different atmospheric conditions and variable loads. In this study, we present a new method that uses unsupervised learning (K-means clustering) to identify the atmospheric clusters of solar irradiance and cell temperature (G, T) and delimit homogeneous atmospheric zones or clusters to reduce the search space of the optimal parameters ( V mp , I mp , and P mp ). The data collected for one year is segregated into 12 clusters; in every cluster, 04 regions are defined based on every cluster’s centroid ( G c , T c ). A local search of the reference voltage/Duty cycle per cluster region is initiated for every sensed (G, T). Variable atmospheric conditions and resistive loads are tested. The results show that the efficiency of the DC/DC converter is 97.5% with a settling time (4.013 ms/5.577 ms) compared to the Perturb and Observe (P&O) the conventional tracking method and the Particle Swarm Optimisation (PSO), both applied locally inside a cluster and a deviation of 2% from the global maximum.