Performance Of Photovoltaic System Research Articles

Performance of grid-connected photovoltaic systems in Northern and Southern Hemispheres under equatorial climate

This work studied the actual and simulated technical performance between two grid-connected photovoltaic (GCPV) systems representing opposite latitudes. The system with a capacity of 5.4 kWp installed in Kelantan, Malaysia represents the northern equator, and the 183.6 kWp system installed in Cikarang, Indonesia, denotes the southern equator. The performance was simulated using PVsyst software, which included the energy output (E_outt), reference yield (Y_r), final yield 〖(Y〗_f), performance ratio (PR), and capacity factor (CF). The mean bias error (MBE) between the actual and simulated technical performance were as follows; for system A, the yearly MBE for the E_out, Y_r, Y_f, PR, and CF were -0.4%, 17.1%, -1.4%, -15.8%, and 1.4%, respectively, and for system B, the E_out, Y_r, 〖 Y〗_f, PR, and CF values were 9.80%, 18.3%, 10.0%, -7.2%, and 10.0% respectively. The results have proven that PVsyst has successfully simulated the yearly E_out, 〖 Y〗_f and CF for both systems including PR, for system B, with MBE less than 10%. However, it is noteworthy to highlight that PVsyst significantly overestimated the Y_r of both systems up to 18.3% and conversely underestimated the PR for system A by 15.8%, which highly likely caused by the Meteonorm imported weather data.

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.

Experimental investigation of photoelectrical performance and thermal characteristics of ventilated building-integrated photovoltaic system utilizing lightweight and flexible crystalline silicon module

The existing large-scale of industrial buildings with lightweight insulated roofing structures presents a challenge for traditional glass crystalline silicon photovoltaic (PV) systems due to insufficient load-bearing capacity. Meanwhile, traditional PV rooftop applications also face challenges due to limited rooftop resources. To address these issues, this study proposes a ventilated building-integrated lightweight photovoltaic (VL-BIPV) system. The VL-BIPV system incorporates lightweight and flexible crystalline silicon modules, which increase rooftop load by about 6 kg/m2. Additionally, the system features a ventilation channel design to enhance thermal management performance. To evaluate the PV performance and thermal characteristics of the proposed system, an experimental setup was implemented to compare the performances of the VL-BIPV system with a building-attached lightweight photovoltaic (L-BAPV) system that utilizes color steel sheet base plates. The results demonstrate the exceptional performance of VL-BIPV system, with a 100.56% higher ratio of the product of short-circuit current and open-circuit voltage compared to L-BAPV. Moreover, the VL-BIPV system achieved a 1.77% increase in PV efficiency and a 2.35% enhancement in daily electricity generation. In hot weather, the adoption of VL-BIPV reduced the extreme temperature of PV cells by 9.23 °C below 85 °C, surpassing the 6.29 °C reduction achieved by L-BAPV system. Furthermore, the ventilation channel exhibited a gradual temperature increase with slower changes in the flow direction, while the base plate temperature decreased by 13.41 °C, which indicates that VL-BIPV can effectively reduce solar heat gain in the building envelope and improve the indoor thermal environment. The research findings provide important guidance for promoting and applying VL-BIPV technology in large-scale industrial buildings with low rooftop load-bearing capacity, thereby promoting the production and utilization of clean electricity in industrial parks.

Improved Mathematical Modelling and Statistical Assessment of Performance of Photovoltaic System under Non-Linear Operational Condition

It is study presents an advanced mathematical model that captures the non-linear operational characteristics of photovoltaic (PV) systems, enhancing the understanding and optimization of their performance under varying environmental conditions. By integrating principles of non-linear dynamics and statistical analysis, the model precisely simulates the performance responses of PV systems to non-linear inputs such as irradiance fluctuations, temperature variations, and load changes. We utilized a comprehensive dataset collected from multiple PV installations to validate our model, ensuring robustness and applicability. The results demonstrate a significant improvement in predicting system behaviors, which facilitates more effective management and optimization strategies. Statistical tools were employed to assess the reliability and efficiency of PV systems, revealing key insights into their operational dynamics. Our findings contribute to the development of more resilient and efficient solar energy systems, offering a valuable resource for researchers and practitioners in the field of renewable energy technologies.

Comparative Analysis of Hybrid Maximum Power Point Tracking Algorithms Using Voltage Scanning and Perturb and Observe Methods for Photovoltaic Systems under Partial Shading Conditions

Partial shading significantly affects the performance of photovoltaic (PV) power systems, rendering traditional maximum power point tracking (MPPT) methods ineffective. This study proposes a novel hybrid MPPT algorithm integrating voltage scanning and modified Perturb and Observe (P&O) techniques to overcome the limitations posed by partial shading. This algorithm has a simple structure and does not require panel information such as the number of panels or voltage due to its voltage scanning feature. To test the proposed algorithm, a grid-connected PV power system with a power of 252.6 kW was created in the MATLAB/Simulink environment. In this power system, six different PS conditions, containing quite challenging situations, were listed in three different scenarios and simulated. The proposed algorithm was compared with the voltage scanning and P&O and voltage scanning and variable-step P&O methods. It was observed that the proposed algorithm has lower power fluctuations compared to the other two traditional methods. Additionally, this algorithm managed to achieve higher efficiency than the other methods in some cases.

Influence on solar PV performance integrated with heat sinks and nano-enhanced phase change material

The inevitable advancement of solar photovoltaic (PV) system performance highly relies on temperature control, which enhances electrical efficiency. The objective of this study is to enhance electrical efficiency by incorporating phase change material of HS36 (PCM) and nano enhanced PCM (NePM). The thermal properties of PCM were improved by adding graphene flakes (GF) into PCM to enhance the thermal transfer rate between the PV panel and PCM. The phase change properties and thermal conductivity of PCM with different concentrations of GF were assessed. The results indicated that the 0.9 wt.% NePCM exhibited the highest thermal conductivity enhancement of 47% in solid states and a significant reduction in latent heat by 9.4% during freezing compared to pure PCM. The effect of cooling on PV performance was studied using a reference panel, integrated with a heat sink containing PCM (PV/PCM) and NePCM (PV/NePCM). Outdoor experiments were conducted using a 10 W panel, and the results for the use of PCM showed a reduction in temperature and an improvement in efficiency. The findings revealed that attaching a heat sink and integrating the PV panel with pure PCM and NePCM reduced the temperature by 8.65°C and 10.04°C, respectively, and improved efficiency by 11.65% and 12.15%, respectively. It can be concluded that the proposed thermal management method for PV systems offers a viable solution for increasing daily average electrical generation with maximum efficiency.

Experimental design and analysis of advanced three phase converter for PV application with WCO-P&O MPPT controller

Photovoltaic (PV)-based power generation systems are becoming increasingly popular as a due to its high performance and cleanliness. Several factors influence the performance of a PV system, including shadowing effects. PV systems employ MPPT methodologies to obtain the power from PV array. Conventional MPPTs works well under normal conditions when there is no shadow effects or partial shading. The presence of partial shading affects the system performance and generates several power peaks. This complicates the process of finding out of the global peak (GMPP) with improved tracking efficiency and reduced settling time including conversion efficiency. This work proposes three hybrid MPPT techniques: Water Cycle Optimisation-Perturb and Observe (WCO-PO), Artificial Neural Network Supported Adaptable Stepped-Scaled Perturb and Observe (ANN-ASSPO), Grey Wolf Optimisation-Modified Fast Terminal Sliding Mode Controller (GWO-MFTSMC), and two conventional MPPT techniques WCO and P&O have been implemented. The proposed system utilizes interleaved boost converter with three phase. The performances of proposed hybrid MPPTs strategies were compared in terms of output voltage, output current and extracted power. The comparison also includes conversion efficiency and average settling time. To analyse the performances, four different cases have been used to test the efficacy of hybrid MPPTs under changing climatic conditions. The MATLAB/Simulink tool has been used to analyze the PV system performances. In the three hybrid MPPT techniques, WCO-PO has performed better when compared to other two hybrid MPPTs in terms of conversion efficiency (99.56%) and settling time (1.4 m).

Side‐Chain Engineering of Non‐Fullerene Acceptors with Trialkylsilyloxy Groups for Enhanced Photovoltaic Performance†

Comprehensive SummarySide‐chain engineering has emerged as a highly effective strategy for tailoring the aggregation behavior and charge transport properties of non‐fullerene small molecule acceptors (SMAs). In this study, we designed and synthesized two SMAs, namely BTPSi‐Bu and BTPSi‐Pr, respectively incorporating tributylsilyloxy and triisopropylsilyloxy groups in their outer positions. Notably, BTPSi‐Bu exhibited better planarity, crystallization, and favorable phase separation when paired with PM6 donor polymer compared to its counterpart, BTPSi‐Pr. The resulting organic solar cells, utilizing the PM6:BTPSi‐Bu blend, demonstrated a remarkable power conversion efficiency of 17.41% and a high open‐circuit voltage of 0.859 V. These findings underscore the significance of integrating trialkylsilyloxy side chains into SMAs as a rational design approach for enhancing the performance of photovoltaic systems.

Integrated assessment of green hydrogen production in California: Life cycle Greenhouse gas Emissions, Techno-Economic Feasibility, and resource variability

This study explores green hydrogen production, focusing on life cycle assessment (LCA) and techno-economic feasibility; specifically, life cycle greenhouse gas emissions and hydrogen production cost. Existing literature lacks a comprehensive exploration of the impact of solar and wind resource variations, ambient conditions, and proton exchange membrane (PEM) electrolyzer sizing on the carbon intensity (CI) and hydrogen production cost. This work explores the relationship between the performance of photovoltaic (PV) and wind systems and the CI of renewable electricity in the U.S. Secondly, this study incorporates the hourly variations in solar and wind resources to assess the variation in hydrogen CI and production costs across California. The study examines how reductions in PEM and Renewable Energy Systems (RES) costs, technological advancements, and the inclusion of co-products’ carbon dioxide equivalent (CO2eq) credits and revenues impact hydrogen CI and production costs. Wind-based systems consistently demonstrate lower CI (0.35 − 1.9 kg CO2eq/kg H2) except for the central regions (CI can reach up to 4.34 kg CO2eq/kg H2), with geographical variations larger than solar-based systems (1.58 − 2.95 kg CO2eq/kg H2). Similar trends are observed for the hydrogen production cost which varies between 1.5 and 15 USD/kg H2 for wind-based systems and between 3.0 and 5.2 USD/kg H2 for the PV-based systems. This study highlights the importance of optimal sizing of PEM electrolyzer to maximize its utilization for hydrogen production and the use of hourly-based models to assess the CI and production costs of hydrogen. Additionally, the geographical variation in the renewable energy resources and the ambient conditions are important factors that affect the hydrogen cost and the CI of both renewable electricity and green hydrogen.

Energy yield database management system based on solar photovoltaic cell using internet of things technology

This study investigates the performance of solar cell electric power generation, focusing on data collected from Prince of Songkla University, Surat Thani Campus, analyzing the Mean Squared Error (MSE) for each phase consisting of Phase A: 0.00133, Phase B: 0.00137, and Phase C: 0.00216. Through linear regression analysis, we establish the correlation between current and electrical energy in each phase, facilitating the prediction of photovoltaic power generation system performance and timely maintenance alerts. This predictive analysis aids in mitigating greenhouse gas emissions, preventing potential damages from short circuits, and ensuring system safety during installation. Our findings, which are accessible through a user-friendly dashboard interface, address a gap in previous studies by providing empirical data specifically from Prince of Songkla University, Surat Thani Campus, and by integrating IoT technology for real-time monitoring and analysis, underscoring the novelty of our approach.

Experimental and numerical approach for the evaluation of PV-system performance on energy and environmental behavior of nearly zero energy buildings: Case study in Mediterranean climate

Nowadays, the performance of photovoltaic (PV) systems has strategic role for satisfying the standard of net or nearly zero energy building with in-situ production. In this frame, the novelty of the paper is the proposal of a combined experimental and numerical approach for evaluating the mismatch between PV production and consumptions during design, operational and future performance under expected emissions scenarios. First of all, it proposes a comparison of production estimation by means of several tools for the evaluation of the energy balance in the design phase; then the expected and real behavior is compared with also the evaluation of the performance ratio (PR) evolution as function of cell temperature. Finally, a sensitivity analysis is proposed in the short and medium scenarios by varying the size of installed system and considering the degradation rate under future weather conditions. The approach is applied to a case study in a typical Mediterranean climate, starting from the monitoring data available for the building energy request and the renewable production (2016–2022). The results of the case study indicate that the PR greatly influences the performance, mainly under expected climate changes, since the operational emissions could increase of more than 15 % compared to actual performance also if the zero energy balance is satisfied. Furthermore, through a sensitivity analysis on the PV-system size, the study demonstrates that with a maximum linear degradation rate of 1.51 %/year, the building could be configured as nearly zero energy in the medium term (20 years) also with lower peak power. The analysis also suggests that the maximization of installed power is a prerequisite to follow the implementation of positive energy goal because, under all considered climatic evolutions it can balance the penalties both due to technical aspects that to modification of consumption and production profiles.

Comparative Analysis of Reverse Truncated Pyramid and Other Nonimaging Concentrators as the Receiver in Laser Wireless Power Transmission System

The global energy landscape faces significant challenges in meeting the demands of modern industries for stable and efficient energy supply. Laser wireless power transmission (LWPT) systems, which utilize the photovoltaic effect to convert laser beam energy, hold great promise due to their long-range transmission capability and high precision. However, the current energy conversion efficiency of these systems requires further improvement to achieve optimal performance. To enhance concentrated photovoltaic (CPV) system performance, the study examines different nonimaging concentrators such as reverse truncated pyramid, cross-compound parabolic concentrator, and square elliptical hyperboloid. Numerical simulations using the finite element method analyze the multifield coupling mechanism of PV modules with various concentration lenses. Three CPV systems with RTP concentrators of different heights were studied to understand the impact of geometry on CPV performance. And the main impact of rotation angle was discussed. The research findings provide essential insights into CPV system performance and the influence of different concentration lenses, contributing valuable knowledge towards improving LWPT technologies.

Enhanced EV Battery Monitoring Using IoT with Improved SEPIC - ZETA Converter and Modified Lion Optimization for Photovoltaic Systems

The rising popularity of electric vehicles (EVs) and the increasing emphasis on sustainable transportation have highlighted the importance of advanced monitoring systems. These systems play a crucial role in providing real-time information about battery parameters to ensure optimal performance and longevity. Moreover, the integration of renewable energy sources, specifically photovoltaic (PV) systems, with EV charging infrastructure presents an exciting prospect to enhance energy efficiency and minimize environmental harm. As a consequence the proposed work develops an Internet of Things (IoT) based PV fed EV charging system. The system incorporates an improved SEPIC-Zeta converter together with Modified Lion Optimization algorithm (LOA) assisted Proportional Integral (PI) controller for optimizing PV system for charging EV battery. IoT connectivity monitors parameter such as PV voltage, PV current, and State of Charge (SOC) of battery. Real-time monitoring of these parameters is achieved by leveraging sensors. The collected data is transmitted through IoT networks to a central monitoring system, enabling operators to track the performance of PV system and EV battery. This facilitates optimized energy generation, efficient battery charging and discharging, and overall system reliability. IoT-enabled monitoring system provides remote accessibility, data analytics, and the generation of alerts and notifications for timely actions. Experimental validation demonstrates that, the proposed concept enhances the monitoring capabilities, improves energy efficiency, and ensures reliable operation of EV charging infrastructure.

Experimental and numerical study on photovoltaic thermoelectric heat storage system based on phase change temperature control

To improve the thermal and electrical performance of photovoltaic (PV) systems, a novel system was proposed, in which the PV panel, phase change material (PCM), thermoelectric (TE), and thermal collection devices (PV-PCM-TEG-T) were combined. The experimental device of the PV-PCM-TEG-T system was put up, and its electrical and thermal characteristic was experimentally studied by comparing it with the standard PV panel on the condition of 3-hour radiation and 3-hour non-radiation. A heat transfer numerical model of the PV-PCM-TEG-T system is established and verified by experiments. The comparison of the PV-PCM-TEG-T system and standard PV panel and the effects of PCM thicknesses, and melting temperatures on the temperature of photovoltaic devices were numerically analyzed in 24-hour operating conditions. The results show that under an experimental condition of 3-hour solar radiance of 800 W/m2 and 3-hour non-radiance, the novel system has better temperature control performance, which could increase the PV panel’s output power and power generation efficiency by 10.4 % and 1.9 % respectively. Under 24-hour simulation conditions, the temperature of the novel system is significantly lower than that of the standard PV panel, with a maximum temperature difference of 10.1 °C. The PV-PCM-TEG-T system with thicker PCM has the same temperature as the system with thinner PCM, but higher TE power generation. And the temperature control is better with the lower PCM melting point. This study has a good promoting effect on the efficient utilization of solar energy.

Modeling, simulation and efficiency assessment of a direct coupled water pumping PV system in semi-arid coastal areas

Photovoltaics (PV) energy is a solution for the electrification of developing countries, especially for remote rural zones. The use of solar energy in water pumping is the most adopted solution for rural and desert regions. The modeling, simulation and analysis of the PV system of water pumping is a vital step before assembling this system on any place, which allows a better understanding of its behavior in real weather conditions on that place. In this paper, we investigate the performance of a water pumping photovoltaic system consisting of a PV generator coupled with a DC-motor which drives a centrifugal pump that draws water from a well and delivers it to a reservoir. The characteristics of the components of this system allow researchers, manufacturers, and social communities to understand better the functioning of these components. Our simulation results were meticulously cross-verified against the module manufacturer’s data sheet, revealing a maximum relative percentage error of 1.12 %. This attests to the coherence between the manufacturer’s stipulations and our simulated values. Furthermore, we ascertain commendable efficiency in the motor-pump system, particularly noteworthy for elevated irradiation levels, while maintaining acceptable performance even under minimal irradiation conditions.

Analysis on Performance of Arched Photovoltaic System

Analysis on Performance of Arched Photovoltaic System

Approaches for Maximizing Maximum Power Point Tracking and Evaluating Operational Constraints in Photovoltaic Systems

Abstract: Optimization techniques have broad utility in multiple engineering fields, including activities such as modeling, system identification, parameter estimation, forecasting, and control of intricate systems. This innovation emphasizes the use of optimization approaches to control the performance of Photo-voltaic (PV) array systems. The main difficulty lies in the nonlinear correlation between current and voltage (I-V) characteristics of PV arrays, resulting in variations in the location of the Maximum Power Point under varied climatic circumstances. It is crucial to track this Maximum electricity Point efficiently in order to collect the highest amount of electricity possible from the photovoltaic devices. Maximum Power Point Tracking is a tracking procedure that optimizes power generation by dynamically altering the operating voltage to coincide with the MPP. In order to tackle this difficulty, the paper suggests a unique two-stage Maximum Power Point Tracking technique. The initial phase applies the Weightless Swarm Algorithm to evaluate the Maximum Power Point in an offline manner. The subsequent phase employs an online Adaptive Perturb & Observe technique to continuously track the MPP in real-time. In addition, an Approximate Single Diode Model is created to quickly assess the output power. In order to verify the suggested method, computer simulations are performed utilizing a Maximum Power Point Tracking system that is combined with a Single-Ended PrimaryInductor Converter

Solar Panel Cleaning System with Voltage Drop Detection

bstract: This research suggests a unique voltage drop sensor and LDR (light-dependent resistor) based solar panel dust removal detecting system. Whereas the voltage drop sensor gauges the voltage differential between the solar panel's input and output, the LDR sensor counts the amount of light reflected from the panel's surface. The system is able to precisely identify the existence of dust and assess its level of intensity by evaluating the aggregated data from these sensors. Afterwards, an automatic dust removal device, like a water spray system or robotic brush, can be started using this information. The suggested method improves the overall performance and lifespan of solar photovoltaic systems by providing an automated, economical, and efficient alternative for the removal of dust from solar panel

A Comparative Analysis of Various Simulation Software for grid-connected Residential Building: A Case Study at Jeddah, Saudi Arabia

Saudi Arabia receives significant energy daily from solar radiation, making it one of the best places to use solar energy to meet its energy needs. Grid connected Photovoltaic (PV) systems provide the electrical energy available from the solar radiation into the grid. Different simulation tools are currently available used to assess the performance of solar PV systems. The present study was conducted to design and evaluate the performance of 15 kW grid-connected solar PV system under climatic conditions of in Jeddah, Saudi Arabia. Two simulation models, Helioscope and PVsyst were used in the analysis and the results were then compared. The annual energy production, specific production, energy injected into grid, and annual performance ratio (PR) are evaluated by the software’s around a whole year at the same climatic conditions. Results showed that the maximum annual solar irradiation in May was 2212 kWh/m2. The PR based on PVsyst simulation (78.04 %) was higher than that of the Helioscope simulation (74.8%) by about 4.15%. The maximum energy production in May was about 6.1 kWh. The energy production from the PVsyst and Helioscope is 28.98 and 25.9 MWh/year with 289.8 and 259.13 MWh/year energy injected into the grid, respectively.

Improve The Conversion Efficiency and Electrical Output of The Solar PV System by Developing and Implementing a Cooling System

The performance of the grid-connected solar photovoltaic (PV) system in the present study is improved using cooling technology. This technology reduces the temperature of solar PV modules and thus increases their efficiency and lifespan. The current solar PV system has been installed in northern Baghdad in the city of Taji. This study included improving electrical power, conversion efficiency, and performance ratio. All of these improvements are achieved by cooling using water. The performance ratio (PR) and efficiency maximum values of the reference (unimproved) and improved solar PV modules are at 10:10 am at 88.30% & 96.30% and 13.4% & 14.6%, respectively. Improved and reference PV modules maximum solar radiation values occur at 12:00 pm at 1.91 W and 1.566 W, respectively. The maximum solar radiation values of the reference and improved PV modules are at 12:00 pm at 922.9 W/m2 and 1012.22 W/m2, respectively. The maximum daily gain of the power and solar irradiance are 22% and 10%, respectively. The significant innovation in the study is the successful performance optimization of the grid-connected solar PV system. Using different equations to study performance by following different behaviors. Along with improving and studying CIGS PV module performance.