Performance Of PV System Research Articles

Performance characterization of a PV system using wavelet transform and genetic algorithm

This paper presents a study of PV system performance in terms of power quality. Wavelet transform has been applied as a tool for signal characterization and future extraction. A Gaussian curve has been proposed as an approximation of daily production. The parameters of the curve were computed using genetic algorithm.

Water-Cooling-Based Approach for PV System Performance Enhancement towards UAE Future Energy Efficiency Policies

United Arab Emirates (UAE) has implemented the UAE Energy Strategy 2050, targeting a 50% increase in renewable energy's contribution by 2050. Steps to achieve this strategy include accelerating efficient consumption of energy and focusing on research and development for sustainable energy solutions. This research aims to investigate the potential improvement in the performance of PV systems as a result of panel’s water-cooling under the UAE climatic conditions. In this work, a PV system consists of two identical 100-W PV panels and an automated water cooling arrangement was built. To assess the effectiveness of the cooling method used, one PV panel was subjected to water cooling, while the other remained uncooled in order to be taken as a benchmark. The experiments took place over a typical summer day during the period between 8:00 am and 5:00 pm. The proposed cooling strategy was repeatedly applied every half an hour to investigate the temperature reduction behavior at different times of the day. The experimental results demonstrated that the adopted water approach was able to achieve a temperature drop of up to 14.6 K. The corresponding power output was improved by up to 12% as a result of the PV panel cooling.

An statistical model for the short-term albedo estimation applied to PV bifacial modules

Albedo estimation is an essential input parameter for bifacial PV modules. However, there was no clear agreement on which albedo values should be used and how they should be measured, either with satellite measurements or using onsite measurements which can be obtained from nearby meteorological stations. Since long-term measurements are not always available for new PV system locations, short-term albedo measurements are also used as input parameters in PV system performance estimation models. Short-term albedo presents high variability due to factors such as weather, seasonality or changes in the surrounding surface among others. In addition, apparently random albedo variations of 60% can be observed, even during consecutive days or within the same day. Therefore, this study presents a two-parameter exponential model that modelates the albedo data statistical distribution with an error of less than 5% in all cases and from which it is possible to determine the reliability of the obtained data. This model has been evaluated at a set of locations, with different surface types and climates, and assessed using onsite and satellite data. The impact of the methodology used to estimate the albedo data uncertainty and its reliability has also been studied as a function of several parameters such as the global horizontal irradiance and measurement time, allowing the process optimization and enhancing its reliability.

Performance Evaluation of Photovoltaic Thermal using MgO Nanofluid

This study investigated the performance and efficiency of a photovoltaic thermal (PV/T) system utilizing a metal-based nanofluid, specifically MgO nanofluid. This research proposes MgO as nanoparticle to mix with base fluid because it demonstrated to have superior features with the highest thermal conductivity and lowest viscosity among the metal oxide. The nanofluid offered improved thermophysical properties that enhanced the PV/T system performance. The study focused on formulating a stable nanofluid, determining its thermophysical properties, and analysing the overall system performance. 0.2wt% MgO nanofluid were successfully developed and demonstrated excellent stability over a 14-day period by using a two-step method which 20 minutes of homogenization at 1000rpm and 30 minutes of ultrasonication. Tests were conducted to determine the thermal conductivity and viscosity of the nanofluid at various concentrations and temperatures. Results showed that increasing the concentration and temperature enhanced thermal conductivity, while viscosity increased with concentration but decreased with temperature. The thermal and electrical efficiencies of the PV/T system at various irradiances (200W/m2, 500W/m2 and 800W/m2), and flow rates (10L/h, 20L/h, 30L/h) were examined, calculated and compared between water and the MgO nanofluid as working fluids. At 10L/h, it was observed that nanofluid had the highest 74% of thermal efficiency increment compared to the water at 500W/m2 followed by 71% at 200w/m2 and 55% at 800W/m2. Also, Nanofluid demonstrated a 5% increase in electrical efficiency at 200W/m2, 2.1% increase at 500W/m2, and 1.9% increase at 800W/m2 compared to water. The nanofluid exhibited superior thermal and electrical efficiency compared to water, indicating its potential for improving system performance hence, surpassing the performance of a standalone PV system.

Sizing a grid-connected photovoltaic system under economic and environmental uncertainties

Several looming challenges confront the implementation of PV systems. The decision-maker must consider technical, economic, and environmental uncertainties to maximize the PV systems' efficiency under specific operating constraints. In this research, we have developed a two-stage stochastic programming model using a multiobjective optimization technique, extending the approach originally introduced by Attia et al. (2021), to optimize the performance of a grid-coupled PV system considering economic and environmental uncertainties. The capacity of a PV system is determined by deciding the number of PV arrays, the amount of energy imported from the grid, and the amount exported to external utilities. The inflation rate, hourly irradiation, ambient temperature, and energy demand are considered uncertain parameters associated with economic and environmental factors. Uncertain parameters are characterized by possible scenarios associated with the corresponding probability of occurrence. A case study of sizing a grid-connected PV system to provide power to the housing area is presented to demonstrate the usefulness of the proposed technique. A sensitivity analysis is conducted by changing the levels of the primary parameters to grasp the tradeoffs that govern the research framework. It is found that the system can meet the entire demand using 1,566 PV arrays at an annual cost of M$1.47 and a reduction of CO2 emissions by 96.32%.

Bifacial and Monofacial PV Systems Performance Assessment Based on IEC 61724-1 Standard

Bifacial and Monofacial PV Systems Performance Assessment Based on IEC 61724-1 Standard

Parameter Estimation Techniques for Photovoltaic System Modeling

In improving PV system performance, the parameters associated with electrical photovoltaic equivalent models play a pivotal role. However, due to the increased mathematical complexities and non-linear traits of PV cells, the precise prediction of these parameters is a challenging task. To estimate the parameters associated with PV models, a reliable, robust, and accurate optimization technique is needed. This paper introduces a new algorithm, Rat Swarm Optimizer (RSO), for obtaining the optimum PV cell and module parameters. The proposed method maintains an adequate balance between the exploration and exploitation phases to overcome premature particle issues. The results obtained using RSO are compared with those of other algorithms, i.e., Particle Swarm Optimization (PSO), Ant Lion Optimizer (ALO), Salp Swarm Algorithm (SSA), Harris Hawks Optimization (HHO), and Grasshopper Optimization (GOA), in this work. The modified one-diode model (MODM) and modified two-diode model (MTDM) are used to analyze the parameters of the mono-crystalline PV cell using the suggested RSO. The obtained findings imply that the parameters estimated by the suggested RSO are more accurate than those calculated by the other algorithms taken into consideration in the paper. The statistical results are compared, and it is clear that RSO is a very accurate, fast, and dependable approach for the parameter estimation of PV cells.

Development of a novel solar PV module model for reliable power prediction under real outdoor conditions

Accurately predicting and validating the power output of commercial solar PV power plants, remains an important research topic despite numerous studies already conducted. The precision and reliability of power prediction depends on the accuracy of the solar cell parameter values used in the model. A novel analytical technique has been developed in this study for PV power prediction, which employs one and two diode models with 3, 5, and 7 parameters. This new model only requires the manufacturer sheet data and has been validated through indoor and outdoor experiments. The performance of an experimental PV system is evaluated using the proposed solar cell models under varying irradiance and temperature levels. Additionally, the predicted output solar power was experimentally validated under real outdoor conditions in India with higher accuracy. The 7-parameter solar cell model is found to be the most accurate with the least RMSE of 0.02, followed by the 5 and 3-parameter models with RMSEs of 0.04 and 0.07, respectively. Compared to previous methods, the present new model predicts PV power with higher accuracy and lower percentage error. Finally, the study also identifies follow-up photovoltaic research areas.

Dynamic global power extraction of partially shaded PV system using a hybrid MPSO-PID with anti-windup strategy

Particle Swarm Optimizer (PSO) has three main drawbacks in case of partially shaded photovoltaic systems. First, it converges slowly to the global peak (GP). Second, because PSO is a time invariant, it cannot adhere to a dynamic GP in the presence of various temporal shading patterns and instead, sticks to the first GP. Third, it exhibits high oscillations around GP. To overcome these shortcomings, this paper proposes a novel hybrid modified PSO-PID (MPSO-PID) with anti-windup strategy based maximum power point tracking. The anti-windup strategy aims to guarantee the robustness of the PID controller and eliminate the PID windup outcome. Two anti-windup structures were applied to PID namely: anti-windup using back calculation and anti-windup using conditional integration. For validation purpose, the hybrid MPSO-PID with anti-windup has been compared with conventional PSO and three modified PSO versions namely: PSO with random numbers eliminated (PSO-RNE), PSO with linearly varying parameters (PSO-LVP), and PSO with fixed maximum iterations (PSO-FMI). The obtained simulation and experimental results revealed that the proposed MPSO-PID with anti-windup overcome the previous shortcomings providing outperformance to track dynamic GP with a less convergence time and small oscillations around GP compared to other algorithms. The proposed MPSO-PID technique has a minimum average response time; 0.026 s; to catch the GP under various shading patterns compared to the other PSO versions; CPSO, PSO-LVP, PSO-RNE, and PSO-FMI; where the average response time are 0.026 s, 0.531s, 0.446 s, 0.763 s, and 0.494 s respectively. Finally, the results proved the robustness and effectiveness of PID design for enhancing both the PSO and PV system performance.

General layout design of mountain PV plant based on array spacing planning

Abstract Reasonable determination of the installation inclination and array spacing of PV power plant modules is essential to improve the power generation efficiency of PV power plants. This paper firstly derives the formula for calculating the north-south spacing of PV arrays with arbitrary slope inclination and visualizes the north-south spacing of complex mountain PV arrays using ArcGIS. Secondly, a mountain PV array system is proposed to ensure that the system can still operate at the maximum power point in real-time when the solar radiation intensity changes drastically due to unpredictable environmental variables. Finally, to verify the feasibility of the active PV array system in real-life production, an experimental platform is built, and an operational test experiment of the active PV array system under partial shading conditions is conducted, as well as a long-term power boost comparison test. The experimental results show that the mountain PV array system has a 95.7% matching degree in the operation test experiment, which can be perfectly adapted to most PV plants; in the power boost comparison test, the power generation of the traditional PV system is 254Wh, and the power generation of the mountain PV array system is 483Wh, which is about 1.9 times higher than the performance of the traditional PV system. The mountain PV array system has good adaptability to various harsh and unexpected conditions and solves the problem of improving the power output of PV systems in the shadow-shaded environment of mountainous areas, which improves the general usability of PV.

Centralized MPPT based on Sliding Mode Control and XBee 900 MHz for PV systems

Maximum Power Point Tracking (MPPT) algorithms are essential to achieve the best overall performance of PV systems. Typically, MPPT techniques are implemented over wired communications, which connect sensors, computing nodes and DC–DC converters. However, the introduction of wireless communication systems can offer more flexibility for information collection, dissemination, and processing when compared with wired communication infrastructures. This article proposes a wireless control architecture that allows the execution of the MPPT algorithms for several PV subsystems on a central node with limited computing power. This approach introduces flexibility and optimizes energy production at PV systems. The presented approach uses Current and Voltage measures, as well as the Irradiance and Cell Temperature values obtained at the PV panel, to calculate the optimal PWM duty cycle for the DC–DC converter which extracts the maximum power from the PV modules. Wireless communications are implemented by means of XBee 900 MHz RF modules. These modules provide a low cost solution with a relatively long range communication, avoiding the overpopulated 2.4 GHz band, in which other common technologies may cause interferences. Although the proposed approach allows the use of different control algorithms, Sliding Mode Control (SMC) techniques were selected, since this control technique ensures robustness and low computational complexity. The proposed SMC was simulated and compared with other conventional techniques with low computational cost, namely PID and P&O. Simulation results proved that SMC provides better performance and higher robustness when sudden changes in irradiance occur. The presented approach was experimentally tested in a PV rooftop installation at the Faculty of Engineering of Vitoria-Gasteiz. The obtained results suggest that it may be a valid way of maximizing energy production in PV systems while avoiding the constraints of wired communications.

Influence of photovoltaic cell technologies and elevated temperature on photovoltaic system performance

This work deploys a configured hypothetical 6-kWp capacity PV system, with mounted rooftop panels, to examine the performance of a PV system, corresponding to different (a) PV cell technologies; (b) ambient temperatures. The first (crystalline silicon (c-Si)) and second (copper indium gallium selenide (CIGS)) generations of PV cells have been chosen for this study. A range of ambient temperatures, −10 °C to 50 °C, at an interval of 5 °C, will be used to investigate the influence of temperature on PV system performance, using the chosen PV cells. A PV design and simulation software, PVsyst, was deployed based on optimisation considerations. It was observed from the report that: the CIGS PV cell produced the highest energy at standard tests and conditions (STC) and elevated temperature; the Si mono and polycrystalline yielded the same amount of energy; the CIGS and Si monocrystalline cells PV have the highest and lowest PR, respectively.

DESIGNING TECHNO-ECONOMIC OFF-GRID PHOTOVOLTAIC SYSTEM USING AN IMPROVED DIFFERENTIAL EVOLUTION ALGORITHM

Conventional power generation is one of the main contributors to the phenomenon of the greenhouse effect. This has led to a diversification of electricity sources including environmentally friendly energy sources such as solar energy. Off-grid PV systems have gained some traction due to their cost-effectiveness for rural communities. However, the intermittent nature of solar is the main challenge to developing the off-grid PV system. Moreover, the high capital cost of PV systems as well as the storage batteries becomes the main concern for all PV users. Thus, this study aims to optimize the size of the PV system and battery simultaneously and design a cost-effective off-grid photovoltaic system considering various aspects such as battery power, solar irradiance, and PV panel selection while ensuring system reliability. The proposed system was optimized using improved Differential Evolution (DE) and its effectiveness was tested by comparing the results with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The Improved DE algorithm provides the highest average cost savings compared to other algorithms, which is $500 per year. It is recommended that this method is very useful in the optimization of off-grid PV systems, considering other uncertainties that affect PV system performance.

ANN based performance forecasting for dusty solar panel

This paper proposes computational models to research the impacts of residue and encompassing temperature on the presentation of a photovoltaic framework. The models have been created utilising enhanced structures of counterfeit brain organisation (ANN) models (multi input multi output) to gauge change productivity in view of exploratory information. The strategy of building the models is shown and approved for its exactness, utilising various measurements. On a daily basis, cleaning will improve the solar PV system's performance ratio, and by using an artificial neural network, the accuracy of the solar PV system is about 99.8%.

Smart energy monitoring and power quality performance based evaluation of 100-kW grid tied PV system

Globally, the demand for energy from renewable sources is growing due to the increasing electricity consumption and the pollution of fossil fuels. The government has framed various policies to facilitate green energy generation, encouraging renewable energy source usage through PV installations in multiple sectors, including educational institutions. The primary objective of this paper is to propose a methodological approach for analysing the performance of the installed PV system on the rooftop of a university building in Tamil Nadu, India. The site selected is favourable for electricity generation from PV systems with an average global solar radiation of 5.82 kWh/m2day. Solar energy changes periodically with annual and daily variations and is not steady due to seasonal changes. The step-by-step performance assessment and the annual performance of the 100-kW solar PV system, which was instituted in 2019, with the forecasted parameters, are presented in this paper. Therefore, the assessment analysis is carried out in four phases: feasibility assessment, Energy yield assessment, Life cycle assessment, and Power quality assessment. To improve the solar PV output and efficiency, considering the solar irradiation, temperature, wind velocity, etc., PV yield is measured to evaluate the PV system's energy metrics. This paper also considers the carbon credits earned, solar power generated in the location, and the payback period. The power quality assessment is carried out in this paper to test the PV plant's compliance with effective grid integration.

A Statistical Analysis of Long-Term Grid-Connected PV System Operation in Niš (Serbia) under Temperate Continental Climatic Conditions

This study analyzes the grid-connected PV system performances over a 10-year period under temperate continental conditions in Niš. Based on the experimental results, we found the following: the 10-year yearly average values of PV system efficiency, Yf, CF, and PR are 10.49%, 1178.51 kWh/kWp, 13.45%, and 0.87, respectively. The yearly average value of PV performances for a 10-year measurement indicates that the behavior of the given PV system over 10 years does not change significantly. Besides, a mathematical prediction model was obtained through regression analysis, and ANOVA was applied for testing the model’s validity. It is shown that the obtained model is statistically significant and enables prediction better than a simple average, the mean values of PV electricity are not changed statistically significantly over the 10 observed years, and there is a statistically significant difference in POA mean radiation during the months over 10 years. Based on the obtained model and POA radiation values, a prediction of the PV system output can be made for similar PV installations. The analysis presented in this study significantly impacts energy prediction, PV energy modeling, and the economics and profitability of the grid-connected PV system utilization, as well as the PV systems’ operation planning and maintenance.

Experimental investigation of a PV/T system containing a TEG section between water-based heat exchanger and air-based heat sink

The negative impact of temperature on PV power generation has led to the implementation of new cooling techniques globally to enhance the annual performance of PV systems. This study proposes a novel arrangement of Photovoltaic/Thermal-Thermoelectric generator PV/T-TEG integrated system that uses water and air cooling to enhance the performance of PV modules in warm regions. The system applies TEGs between the water heat exchanger and the air heatsink, instead of between the PV module and the cooling fluid. This avoids the non-uniform cooling associated with direct TEG connection to the PV backside. The proposed system was tested in four different climates in Iran and compared with PV-TEG and alone-PV systems. The results showed that the proposed system reduced the PV surface temperature by 23%, increased the electrical output power by more than 15%, and improved the PV electrical efficiency by about 3%. The average total energy efficiency was 55.6% and the maximum thermal efficiency was about 20%. These values were satisfactory for the non-concentrated TEG-based PV/T system in all analyzed climates.

Effect of Temperature and Solar Panel Position on Solar PV System Performance: A Review

Most people think that the sun's energy is the most valuable and plentiful of all the energy sources in the world. Getting electricity from the sun's energy can be done in many ways that have been tried and tested. Solar PV systems that use sunlight to generate electricity are well-known and widely used technology. The performance of PV technology depends on the solar panel's temperature, how much dust it is exposed to, and how the panel is tilted. Changing the panel's materials may alter its performance but the effects of other parameters are still questionable. Few research works have examined individually how the temperature of the panel, as well as the panel angle, affect the performance of the solar PV system but still, the impact of the integration of both systems needs to be better studied. Therefore, this review aims to investigate how the temperature of the solar panels and the angle of the automated control panels affect solar PV performance.

Technical modelling of solar photovoltaic water pumping system and evaluation of system performance and their socio-economic impact

Water is a precious resource for agriculture and most of the land is irrigated by tube wells. Diesel engines and electricity-operated pumps are widely used to fulfill irrigation water requirements; such conventional systems are inefficient and costly. With rising concerns about global warming, it is important to choose renewable energy source. In this study, SPVWPS has been optimally designed considering the water requirement, solar resources, tilt angle and orientation, losses in both systems and performance ratio. A PVSyst and SoSiT simulation tools were used to perform simulation analysis of the designed solar photovoltaic WPS. After designing and performance analysis, farmers were interviewed during fieldwork to assess socioeconomic impacts. In the result section, performance of PV system is analyzed at various tilt angles and it is established that system installed at a 15° tilt angle is more efficient. The annual PV array virtual energy at MPP of designed photovoltaic system is 33342 kWh and the annual energy available to operate the WPS is 23502 kWh. Module array mismatch and ohmic wiring losses are 374.16 kWh and 298.83 kWh, respectively. The total annual water demand of the selected site is 80769 m³ and designed SPWPS pumped 75054 m³ of water, supplying 92.93% of the irrigation demand. The normalized values of the effective energy, system losses, collection losses and unused energy in the SPVWP system are 2.6 kW/kWp/day, 0.69 kW/kWp/day, 0.72 kW/kWp/day and 0.48 kW/kWp/day, respectively. The annual average performance ratio of the proposed system is 74.62%. The results of the interviews showed that 70% of farmers are extremely satisfied with the performance of SPVWPS and 84% of farmers indicated that they did not incur any operating costs. The unit cost of the SPWPS is 0.17 €/kWh, which is 56.41% and 19.04% less expensive than the cost of diesel and grid electricity.

Assessment the technical and economic performance of a window-integrated PV system using third-generation PV panels

Assessment the technical and economic performance of a window-integrated PV system using third-generation PV panels