Photovoltaic Panel System Research Articles

Fault Detection and Classification for Photovoltaic Panel System Using Machine Learning Techniques

ABSTRACTThe deployment of solar photovoltaic (PV) panel systems, as renewable energy sources, has seen a rise recently. Consequently, it is imperative to implement efficient methods for the accurate detection and diagnosis of PV system faults to prevent unexpected power disruptions. This paper introduces a potential strategy for fault identification and classification through the utilization of machine learning (ML) techniques. The study aimed to use ML algorithms to identify and classify normal operations, seven different types of faults, in two operational modes (maximum power point tracking and intermediate power point tracking). Four machine learning algorithms and ensemble methods (decision trees, k‐nearest neighbors, random forest, and extreme gradient boosting) were employed, followed by hyperparameter tuning and cross‐validation to determine the best configuration. The results indicated that ensemble methods, particularly XGBoost, excelled in detecting and classifying faults in PV systems, achieving a 99% accuracy rate after hyperparameter adjustments. The TPR values show a high sensitivity of 0.999, with some achieving a perfect score of 1.000. The FPR shows very low values, with the majority of metrics indicating FPRs at or close to 0%. This performance is crucial in the solar energy context, as failing to detect faults can result in significant energy loss and increased maintenance costs.

Analyses of PO-Based Fuzzy Logic-Controlled MPPT and Incremental Conductance MPPT Algorithms in PV Systems

This manuscript aims to increase the utilization of solar energy, which is both environmentally friendly and easily accessible, to satisfy the energy needs of developing countries. In order to achieve this goal, maximum power generation should be provided from photovoltaic panels. Several maximum power point tracking (MPPT) methods are utilized for maximum power generation in photovoltaic panel systems under different weather conditions. In this paper, a novel intelligent hybrid fuzzy logic-controlled maximum power point tracking algorithm founded on the perturb and observe (PO) algorithm is presented. The proposed fuzzy logic controller algorithm and the incremental conductivity maximum power point tracking algorithm were simulated in a MATLAB(2018b version)/Simulink environment and evaluated by comparing the results. Four Sharp ND-F4Q295 solar panels, two in series and two in parallel, were used for the simulation. In this study, the voltage ripple of the proposed hybrid method was measured at 1% compared to the classical incremental conductivity method, while it was 8.6% in the IncCon method. Similarly, the current ripple was 1.08% in the proposed hybrid FLC method, while the current ripple was 9.27% in the IncCon method. It is observed that the proposed smart method stabilizes the system voltage faster, at 25 ms, in the event of sudden weather changes.

Thermal management enhancement of building-integrated photovoltaic systems using coupled heat pipe and evaporative porous clay cooler

Thermal management enhancement of building-integrated photovoltaic systems using coupled heat pipe and evaporative porous clay cooler

Smart PV Monitoring and Maintenance: A Vision Transformer Approach within Urban 4.0

The advancement to Urban 4.0 requires urban digitization and predictive maintenance of infrastructure to improve efficiency, durability, and quality of life. This study aims to integrate intelligent technologies for the predictive maintenance of photovoltaic panel systems, which serve as essential smart city renewable energy sources. In addition, we employ vision transformers (ViT), a deep learning architecture devoted to evolving image analysis, to detect anomalies in PV systems. The ViT model is pre-trained on ImageNet to exploit a comprehensive set of relevant visual features from the PV images and classify the input PV panel. Furthermore, the developed system was integrated into a web application that allows users to upload PV images, automatically detect anomalies, and provide detailed panel information, such as PV panel type, defect probability, and anomaly status. A comparative study using several convolutional neural network architectures (VGG, ResNet, and AlexNet) and the ViT transformer was conducted. Therefore, the adopted ViT model performs excellently in anomaly detection, where the ViT achieves an AUC of 0.96. Finally, the proposed approach excels at the prompt identification of potential defects detection, reducing maintenance costs, advancing equipment lifetime, and optimizing PV system implementation.

Analysis and performance prediction of a building integrated photovoltaic thermal system with and without phase change material

Analysis and performance prediction of a building integrated photovoltaic thermal system with and without phase change material

Hygroscopic hydrogel-based cooling system for photovoltaic panels: An experimental and numerical study

Hygroscopic hydrogel-based cooling system for photovoltaic panels: An experimental and numerical study

ANALYSIS OF AUTOMATION STRATEGY FOR INTEGRATED CUSTOMER-ORIENTED SYSTEM VIA SMART DIGITAL NODES IN DISTRIBUTION TRANSFORMERS

There are many compelling justifications for the significance of MV/LV distribution transformers in facilitating customer-centric services in the next years. The integration of transformer-level intelligence has the potential to strengthen the characteristics of the low voltage (LV) grid management system, which is often lacking in automation. The transformer enables the use of advanced technologies such as local private networks and EDGE computing. The transformer plays a vital role in connecting the appliances of end consumers with the medium voltage grid. Typically, the location of the facility is in close proximity to the client inside a neighboring energy village. Transformer stations are thus ideal locations for the placement of batteries that facilitate the sustenance of the local energy community, bigger photovoltaic panel systems, and expedited charging apparatus. This article presents, use of Smart Digital Nodes (SDNs) as central nodes within the energy community, replacing the conventional MV/LV distribution transformers. This research is intended to provide a new digital service model at the distribution transformer level. A real-life scenarios are presented. Hence, the transformer station presents a very advantageous site for the integration of batteries, substantial photovoltaic (PV) panel sets, or rapid charging devices within the local energy community.

Tube cross-section flatness optimization to enhance the cooling performance of nanofluid-based photovoltaic thermal systems combined with nano-enhanced phase change material

Tube cross-section flatness optimization to enhance the cooling performance of nanofluid-based photovoltaic thermal systems combined with nano-enhanced phase change material

Technical and Economica Feasibility of Photovoltaic Tiles Applies to a Single-Family Residence in Belo Horizonte-MG

Objective: The objective of this study is to verify whether photovoltaic tile technology presents technical and economic feasibility to be implemented in a single-family residence located in Belo Horizonte-MG. Theoretical framework: Through the photoelectric effect, photovoltaic tiles directly convert solar energy into electrical energy in a static, silent, non-polluting and renewable way. In this system, photons, energy-carrying particles present in sunlight, fall on a surface composed of photovoltaic cells (made of semiconductor material). At the ends of the semiconductor material, an electrical potential difference appears, responsible for setting the electrons in the structure in motion, producing electric current. Methodology: The methodology adopted for this research consists of simulating the energy consumption of a 77m2 residential building, consisting of 3 members. The tile and photovoltaic panel systems were designed to meet the energy demands of this building. Results and discussion: The results indicated that both systems present technical feasibility for their implementation, since the technologies demonstrated that they are capable of satisfying 100% of energy needs. However, from an economic point of view, only photovoltaic modules were viable. Originality/value: This work makes a contribution to the literature by analyzing a technology that is still little known in the energy market. Implications of the research: The relevance and value of this research are evidenced by the fact that photovoltaic tiles are a sustainable alternative to generate clean energy and reduce greenhouse gas emissions, which can contribute to the diversification of the Brazilian energy matrix and mitigation of impacts. of civil construction.

Real-Time Monitoring of Photovoltaic Panel Using Node-RED

This research aims to design and implement an Internet of Things (IoT)-based monitoring system for Photovoltaic (PV) panels using Node-RED. The system can monitor critical parameters such as voltage, current, power, and the electrical energy produced by the PV panels in real-time. The data obtained from the PV panels is sent to a Node-RED server and visualized in the form of indicators and graphs on a dashboard. Statistical analysis calculates the daily average power and total energy produced. The results show that the proposed system can enhance monitoring efficiency and significantly benefit PV system maintenance and management. Users can quickly identify and address issues that may arise, such as panel performance degradation or system disruptions. Energy analysis and maintenance planning can be carried out by collecting historical data. This research supports the broader renewable energy development and provides an effective real-time PV system monitoring solution.

Numerical study of the thermal performance of a single-channel cooling PV system using baffles and different nanofluids

Numerical study of the thermal performance of a single-channel cooling PV system using baffles and different nanofluids

Novel cooling system for free-standing photovoltaic panels

ABSTRACT Although photovoltaic (PV) technologies enjoy tremendous benefits and hold the huge potential to lower building overall energy consumption, there is a major drawback. PV efficiency is extremely sensitive to heat and significantly reduced by increasing setting temperature and solar irradiance; thereby, thermal management in PV collectors plays a significant role in generating electrical energy. Using oscillating heat pipes attached to the rear side of PV panels is considered a novel and useful approach to dissipating heat. In this study, a novel cooling system that consists of a newly designed spiral oscillating heat pipe is introduced, while DI water and 0.2 g/l graphene are used as working fluid and PV panels are located at tilt angles of 30° and 60°. The OHP efficiency is higher at 60°; however, the efficiency of PV is maximized at 30° since the panel is exposed to maximum solar irradiance. The research demonstrates that the cooling method proves highly effective, especially in the hottest time of the day and the power output improves considerably from 38 W to more than 42 W at 30°, while the value is about 39.7 W when water is used as a coolant.

Comprehensive review and analysis of photovoltaic energy conversion topologies

Energy conversion is a pivotal process with widespread applications, spanning renewable energy systems, electric vehicles, and industrial power grids. Selecting the right energy conversion topology is critical for optimizing system performance, efficiency, and reliability. This comprehensive review paper provides a thorough overview of energy conversion topologies used in photovoltaic (PV) panel systems, as well as their applicability in diverse domains. Furthermore, the paper conducts a detailed analysis of commonly employed energy conversion topologies. Each topology is meticulously examined based on its operating principles, advantages, drawbacks, and typical use cases. This comprehensive review serves as an invaluable resource for researchers, engineers, and practitioners engaged in the dynamic field of energy conversion, offering insights into both wind energy and photovoltaic panel systems.

Hybrid Solar PV and WECS Power Quality Improvement by STATCOM

The increasing integration of off-grid energy sources in the utility load has ended up resulting in elevated standards regarding power quality, voltage stabilisation purposes, and efficient energy use. The electrical network Wind and solar energy have been considered to be among the most reliable renewable energy sources. However, the self-sufficient operation of either photovoltaic or wind energy systems does not offer a highly consistent source of electricity production owing to the unpredictability of the wind and solar irradiance availability. As a result of this, a variety of solar and wind power generation systems have the ability to produce a very reliable and promising electrical supply. In the present study, a hybrid wind and photovoltaic panels system model has been provided. This specific type of technology possesses plenty of possibilities for its users from afar. This particular kind of technology is highly beneficial in inaccessible or offshore locations where integrating with the grid is not very cost-effective. Nevertheless, integrating power electronics to dissipated generation (DG) systems brings substantial issues with power quality, which include reactive power adjustment and harmonic development, which throws off the system for power distribution. The present study proposes a simulation framework for a hybrid wind-photovoltaic generation system. The system's efficiency in gridconnected mode is assessed. Calculations of total harmonic distortion (THD) at various speeds of wind were used for assessing the wind-SPV hybrid system's power quality. This hybrid system's power quality has been enhanced owing to its employing of STATCOM.

Novel curled cooler to enhance the efficiency of a photovoltaic panel system

Novel curled cooler to enhance the efficiency of a photovoltaic panel system

Wind-Induced Cooling Effects on Photovoltaic Panel Performance

This investigation evaluated the performance of a photovoltaic (PV) panel system under varied cooling speeds of a calibrated wind generator. The objectives encompassed the calibration of wind speed, integration of the wind generator with the PV panel system, monitoring the performance of the PV panel with wind-induced cooling, and analyzing overall performance under different wind generator settings. Parameters assessed included open circuit voltage, short circuit current, PV panel surface temperature, and power output. The tests were carried out both with and without wind cooling and under artificial and natural lighting conditions. Under artificial lighting conditions, the solar PV panel demonstrated suboptimal short circuit current compared to natural lighting conditions, leading to an overall decrease in power output. Moreover, the findings revealed a significant relationship between simulated wind speed and the overall performance of the PV panel, with notable variations in surface temperature, voltage level, current level, and power output. The statistical analysis supported these findings, with all dependent variables exhibiting statistically significant differences. The practical implications of these observations are pertinent to the design of more efficient and sustainable PV and PV-wind cooling systems. By comprehending the influence of wind on PV panel performance, system designers and operators can make informed decisions to maximize energy production and enhance the overall efficiency of the PV system.

Techno-economic analysis of commercial-scale 15 MW on-grid ground solar PV systems in Bakalia: A feasibility study proposed for BPDB

Techno-economic analysis of commercial-scale 15 MW on-grid ground solar PV systems in Bakalia: A feasibility study proposed for BPDB

A case study of techno-economic and environmental analysis of college rooftop for grid-connected PV power generation: Net zero 2050 pathway

A case study of techno-economic and environmental analysis of college rooftop for grid-connected PV power generation: Net zero 2050 pathway

A Feature Extraction of Photovoltaic Solar Panel monitoring system based on Internet of Things (IoT)

INTRODUCTION: The Internet of Things (IoT) is an modern technology that improves user experience and gives items more intelligence. A large number of applications have already embraced the IoT. Our lives were made significantly easier and more accessible by the development of the IoT. In this research a photovoltaic solar panel system has been monitored using IoT.
 OBJECTIVES: The feature extraction of a photovoltaic solar panel monitoring system based on the IoT working process is provided in this work. The implementation of maximum power point tracking (MPPT) algorithm also covered, along with a brief description of the pre-processing method, datasets and the PV system features are extracted.
 METHODS: The model develops a thorough grasp to increase the voltage and current efficiency, a maximum power point tracking technique (MPPT) is implemented in this research study.
 RESULTS: A safer solar panel monitoring system displays the result in LCD display screen it shows various readings, including the IP address, voltage and current rating, light intensity, temperature, and fault occur on the system receive warning message.
 CONCLUSION: The proposed solar panel monitoring system demonstrates high level voltage and current accuracy when compared to the existing method.

Prediction of the optimum photovoltaic output based on cell temperature and solar irradiance

Energy-harvesting photovoltaic (PV) systems are common, but due to the challenges in managing the output, they raise serious difficulties. Climate variables have an impact on the uneven output performance of PV panels. The sunlight and the surrounding environment are unlimited making it challenging to estimate a PV panel system's output of electricity. Not only that, The PV panel will only provide power in parallel with its rated capacity under the Standard Test Condition (STC). STC requires 1000 Watts of sun energy per meter square of solar irradiance and cell temperature of 25 degrees Celsius. Therefore, the changing weather, which will impact the output power, requires prediction. Since the PV panel output will not generate according to its rating, PV power generation predictions requiring calculations of elements such as weather, sun hours, and temperature play a significant role. Hence, this research is related to the prediction of the optimum photovoltaic output based on cell temperature and local solar irradiation. The novelty of this research is all of the surrounding parameters used to predict the PV output are focused on the local area in Batu Pahat, Johor where the UTHM campus is located.