Solar PV Performance and Shading Analysis in a Rooftop Agro-Voltaic System

Solar photovoltaic (PV) panels are projected to become the largest contributor of clean electricity generation worldwide. Maintenance and cleaning strategies are crucial for optimizing solar PV operations, ensuring a satisfactory economic return of investment. Nanocoating may have potential for optimizing PV operations; however, there is insufficient scientific evidence that supports this idea. Therefore, this study aims to investigate the effectiveness of nanocoating on the performance of solar photovoltaic (PV) panels installed in Al Seeb, Oman. A further study was also carried out to observe the influence of coating layers on the performance of PV panels. One SiO2 nanocoated solar panel, another regularly cleaned PV panel, and a reference uncleaned panel were used to carry out the study. The site of the study was treeless and sandy, with a hot and dry climate. A data logger was connected to the solar PV panel and glass panel to record the resulting voltage, current, temperature, and solar radiation. It was observed that nanocoated PV panels outperformed both regular PV panels and uncleaned PV panels. Nanocoated PV panels demonstrated an average efficiency of 21.6%, showing a 31.7% improvement over uncleaned panels and a 9.6% improvement over regularly cleaned panels. Although nanocoating displayed high efficiency, regular cleaning also contributes positively. Furthermore, even though nanocoated PV panels outperformed the other two panels, it is important to note that the performance difference between the regular cleaned PV panels and the nanocoated PV panels was small. This indicates that regular cleaning strategies and nanocoating can further contribute to maintaining a more efficient solar PV system. Coating in many layers was also observed to influence the performance of PV panels insignificantly, mainly the fourth layer coating appeared to have formed sufficient mass to retain heat.

The installed capacity of grid-tied photovoltaic (PV) systems around the globe is increasing rapidly due to the need for clean, sustainable and fuel independent energy. The PV technology is already a major part of the energy mix in many developed and developing countries. The electricity generated from these systems heavily depends on the prevailing weather conditions and is directly related to the available solar irradiance. Therefore, the electricity injected into the grid from these systems is intermittent reducing the utility of that generated power. Any sudden irradiance changes, due to passing clouds, rain, dust storms, etc., directly affect the power response of solar systems, compromising the security of electricity supply and resulting in the need for operating reserves to stabilize the supply. The further deployment of grid connected PV systems will benefit greatly by developing the methodology to systematically study and analyse the variability and quantity of the power produced by installed PV...

Recently, real-time simulation of renewable energy sources are indispensible for evaluating the performance of the maximum power point tracking (MPPT) controller, especially in the photovoltaic (PV) system in order to reduce cost in the testing phase. Nowadays, real time PV simulators are obtained by using analog and/or digital components. In this paper, a real-time simulation of a PV system with a boost converter was proposed using only the digital signal processor (DSP) processor with two DC voltage sources to emulate the temperature and irradiation in the PV system. AMATLAB/ Simulink environment was used to develop the real-time PV system with a boost converter into a C-program and build it into a DSP controller TMS320F28335. Besides, the performance of the real-time DSP-based PV was tested in different temperature and irradiation conditions to observe the P-V and V-I characteristics. Further, the performance of the PV with a boost converter was tested at different temperatures and irradiations using MPPT algorithms. This scheme was tested through simulation and the results were validated with that of standard conditions given in the PV data sheets. Implementation of this project helped to attract more researchers to study renewable energy applications without real sources. This might facilitate the study of PV systems in a real-time scenario and the evaluation of what should be expected for PV modules available in the market.

Sunlight is a great source of available energy on the planet. South America is a region near the line of the Equator, and Brazil is a country with a large amount of solar radiation. In this paper, only 4 of the 37 TPPs of the Brazilian coast that transport million tons of cargo per year are considered. The TPPs are distributed around the coast and have many roof warehouses and covered carport areas available or idle. The times of insolation and solar irradiance data were collected and correlated with these PPs to determine a solar energy generation using photovoltaic system modules available on the Brazilian market for each of these ports. Then we estimate the total potential energy lost in selected ports around 96.81 mW per day, due to the lack of SPVm in TPPs installed in the TAs. Thus, we suggest that Brazilian port authorities should develop programs to encourage an application for areas to generate solar energy.

The demand for solar photovoltaic (PV) system is growing rapidly driven by new technology and strong economies of scale. PV systems directly convert solar energy into electricity without release any pollution into the environment and deplete natural resources. PV technology has matured and its reliability keeps improving. However, PV system is more expensive to produce than conventional sources of energy due in part to the cost of manufacturing PV devices and in part to the conversion efficiencies of the equipment. Besides, important attention in designing, developing and installing the PV systems is time-consuming. In this paper, we propose a mathematical model to predict the PV systems behaviour and performance by considering the plausible factors. The factors accept in this model are solar irradiance and manufacturers’ information for the type of PV panel. A case study at the eastern part of Peninsular Malaysia was conducted to examine the effect of factors on the performance of PV. Through the comparative analysis, the results have a good agreement.

In recent years, solar energy has received tremendous attention in accordance with the global efforts in moving towards clean energy generation. A solar tracking system shifts the position of solar panel following the Sun's movement, allowing more energy to be harvested. This paper aims to evaluate the performance of solar tracking system in Malaysia, including the east-west single-axis tracking system, north-south single-axis tracking system, vertical axis tracking system, and dual-axis tracking system. The periodical tilt angle adjustment of fixed-tilt photovoltaic system is also investigated to optimize its performance. A mathematical model is formulated to compute the amount of solar radiation collected in a photovoltaic system and the optimization model is solved using genetic algorithm to determine the optimal tilt and azimuth angles for maximum solar radiation yield. Based on the results, PV system with dual-axis solar tracker has 22.14 % more solar radiation collected compared to the fixed-tilt system, while monthly tilt angle adjustment improves the yield by 2.15 %.

The analysis presented in this paper focuses on the energetic aspects of the use of photovoltaic (PV) systems in office buildings. Energy generation from PV system has been simulated on an hourly time scale and compared with the energy demand of two office buildings located in Krakow (southern Poland). The buildings’ annual load exceeded 1 GWh in both cases. The analysis dealt with estimating how much energy generated by a PV system can be utilized on-site (self-consumption) and how big the energy surpluses will be (energy generation greater than demand). Capacities of PV systems ranging from 0.1 to 1.0 MW have been considered. Also, the impact of PV generation on the residual load parameters and changes in the maximal monthly and hourly energy demand were investigated. The results show that although the building energy demand is similar (in terms of annual volume of energy consumed) the potential of PV systems to cover it is different. The 100-kW PV system can reduce the observed hourly peak energy demand by 1% in December but by over 30% in June (respectively, from 171 kWh to 169 kWh, and from 333 kWh to 255 kWh). Considering the annual patterns of the office buildings’ energy demand and PV generation (both have their respective peaks in summer), the application of a PV system changes the office building energy demand pattern significantly from the perspective of the power system operator. After installing 500 kW PV in an office building consuming 1 GWh annually, the months with highest demand are no longer in summer but in winter.

The performance of grid-connected Photovoltaic (PV) power generation system operating in the field is inevitably affected by environmental parameters (solar irradiance, temperature, humidity, wind speed, spectrum, cloud cover, dust, etc.), of which the main factors are solar irradiance and temperature. Based on the data of 100kW PV system of ShangYi PV Plant captured form June 1, 2012 to May 31, 2013 (1 min resolution) and the data of Qinghai Delingha 20MW PV Plant in China captured in 2012., the influence of solar irradiance and temperature on PV system is analyzed. The results show hourly PV array DC power has highly significant positive correlation with hourly total solar radiation, also PV system AC power output and solar irradiance have good consistency. Both of them show irradiance is the main environment factor to the PV system. Then using the captured data, the relationship between maximum load and PV panels surface temperature is also analyzed, the surface temperature is higher, the maximum load is lower.

Solar photovoltaic (PV) technology has the versatility and flexibility for developing off-grid electricity system for different regions, especially in remote rural areas. While conventionally straight forward designs were used to set up off-grid PV-based system in many areas for wide range of applications, it is now possible to adapt a smart design approach for the off-grid solar PV hybrid system. A range of off-grid system configurations are possible, depending upon load requirements and their electrical properties as well as on site-specific available energy resources. The overall goal of the off-gird system design should be such that it should provide maximum efficiency, reliability and flexibility at an affordable price. In this chapter, three basic PV systems, i.e. stand-alone, grid-connected and hybrid systems, are briefly described. These systems consider different load profiles and available solar radiations. A systematic approach has then been presented regarding sizing and designing of these systems. Guidelines for selection of PV components and system sizing are provided. Battery energy storage is the important component in the off-grid solar PV system. Due to load and PV output variations, battery energy storage is going to have frequent charging and discharging. So the type of battery used in a PV system is not the same as in an automobile application. Detailed guidelines for selection of battery are therefore also provided. At present, most of the world-wide PV systems are operating at maximum power points and not contributing effectively towards the energy management in the network. Unless properly managed and controlled, large-scale deployment of PV generators in off-grid system may create problems such as voltage fluctuations, frequency deviations, power quality problems in the network, changes in fault currents and protections settings, and congestion in the network. A possible solution to these problems is the concept of active generator. The active generator will be very flexible and able to manage the power delivery as in a conventional generator system. This active generator includes the PV array with combination of energy storage technologies with proper power conditioning devices. The PV array output is weather dependent, and therefore the PV power output predictability is important for operational planning of the off-grid system. Many manufacturers of PV system power condition devices are designing and developing new type of inverters, which can work for delivering the power from PV system in coordination with energy storage batteries as conventional power plant.

In the Research Center (CINVESTAV), located north Mexico City was evaluated 60 kWp photovoltaic (PV) system. The PV system energy performance ratio, so called “quality factor” are reported together with the measured solar irradiation, ambient and PV module temperatures. Quality factor defines the overall system performance with respect to the energy production, solar resource, and total effect of system losses. The electric grid-tied PV system consists of 240 PV modules of 250 Wp each, which are connected to 5 inverters to produce three phase AC. We describe the general PV system quality factor in a month basis for 2013. In spite of the different seasonal weather conditions and some inverter trouble, the calculated average quality factor was 91.75%. The averaged daily PV generated energy throughout the year was 258.9 kWh/day. The accumulated total generated energy during the year was 94,427.7 kWh. However, instead of using solar irradiance sensor at the array tilt angle, and taking in consideration the horizontal global irradiation, the quality factor reduces drastically to 83.56%.

A photovoltaic (PV) array performance depends on various operating conditions. Solar irradiation is considered the most important factor. The shading on PV array can result from passing clouds, trees, utility, telephone poles, or neighboring buildings. It causes not only power losses, but also increases non-linearity of V-I characteristics of PV array. This phenomenon has been studied in many research works using different software packages. In this paper, user-friendly LabView tool is proposed to simulate effects of PV shading on its characteristics. Simulation results are verified through different case studies.

Efficient Maximum Power Point Tracking (MPPT) techniques play a vital role in optimizing energy extraction from photovoltaic (PV) systems, primarily due to the high sensitivity of photovoltaic panel (PVP) characteristics to varying environmental parameters, including ambient temperature and solar irradiance. Conventional MPPT methods generally depend on identifying and following reference points, which are extracted from variables closely related to the Maximum Power Point (MPP) on the external current-voltage characteristics of PVP. In response to the limitations inherent to traditional approaches, this study proposes an advanced lookup table strategy to generate highly accurate reference values explicitly as functions of measured ambient temperature and solar irradiance. Initially, this research employs the two-diodes electrical circuit model to rigorously define the foundational relationships between ambient temperature, irradiance, and photovoltaic panel performance. Subsequently, contemporary advanced extraction methods based on recent academic literature were applied, enabling accurate identification of the MPP coordinates. Creating an effective lookup table requires comprehensive and detailed experimental datasets, which are often insufficient or unevenly distributed in practical scenarios. To address this challenge, the Shepard global interpolation method was integrated into the model development process, effectively mitigating datasets limitations through accurate interpolation of missing data points. This approach significantly elevates the precision and robustness of MPPT models. A comprehensive case study, conducted with real-world experimental datasets, rigorously validated the accuracy and reliability of the proposed interpolation-based lookup table. The results confirm substantial enhancements in MPPT accuracy, facilitating greater energy extraction efficiency and improved overall performance in practical photovoltaic applications. DOI: 10.61416/ceai.v27i4.9541

Solar Photovoltaic (PV) Systems are one of the most favorable and advantageous power generation frameworks used worldwide to fulfill the global requirements/needs for Renewable & Clean Energy. The output power characteristics generated by the PV Systems are non-linear and are strongly dependent upon the variable environmental parameters such as the Solar Irradiation (W/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) and Temperature (°C). Each PV System has its own ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$V_{MPP},I_{MPP}$</tex> ) point defined at a specific Irradiation (W/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) and Temperature (°C) value at which the power is optimal. Thus, in order to ensure the continuous operation of the PV System at the Maximum Power-Point (MPP), an intelligently smart Maximum Power-Point Tracking (MPPT) mechanism is mandatorily implemented along with the Photovoltaic (PV) System. This paper exhibits a comparative study on the behaviors of the four MPPT algorithms namely: Cuckoo Search Algorithm (CSA), Flower Pollination Algorithm (FPA), Grey Wolf Optimization Algorithm (GWOA), and the Particle Swarm Optimization Algorithm (PSOA) under Dynamic Weather/Environmental conditions based on fluctuations in Temperature (°C) and Solar Irradiation (W/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) for a DC-DC Step-Up Converter based Photovoltaic (PV) System that is modeled & implemented under Matlab/Simulink Environment.

In this study, based on the slope of power versus voltage, a novel MPPT algorithm using neural network compensator is proposed to avoid the oscillation problem and effect of uncertain parameters in photovoltaic (PV) systems. However, the characteristics of PV output voltage and output current are determined by the solar irradiation conditions, ambient temperature, and the load electrical characteristics, thereby the technologies of changing the location of the maximum power point must be developed in the applications of maximum-power-point-tracking (MPPT) control in order to make the PV arrays get the optimal efficiency from solar energy at different operating conditions. In this study, the uncertainties in PV systems are compensated by a neural network and the duty cycle of dc/dc converter is determined by a PI controller. The control objectives of this study is to achieve MPPT for the PV systems including solar cell arrays, a dc/dc converter, and an output load despite the variation of solar irradiation, ambient temperature, and the load electrical characteristics in PV systems. From experimental results, the validity of the proposed MPPT controller can be verified under a certain solar irradiation and a partially shaded condition, respectively.

Global perspectives on advancing photovoltaic system performance—A state-of-the-art review