Production Of Photovoltaic Modules Research Articles

Parameters Estimation of Photovoltaic Modules Using Differential Evolution Metaheuristic Method

This paper presents the analysis of the differential evolution (DE) metaheuristic method, which is used to estimate some parameters employed in the equivalent electrical circuit that represents the photovoltaic (PV) cell model. The DE algorithm is an evolutionary algorithm that can be designed to search global optimal points with fast convergence time and present accurate results, requiring few control variables to be set. The accuracy of reproducing the characteristics of the PV module depends on the knowledge of some PV cell model parameters, such as series and shunt resistances, diode ideality factor, and diode reverse saturation current. Once the referred parameters are not usually given in the manufacturers' datasheet, their determination can be achieved by the DE algorithm, employing data and the current-voltage (I-V) characteristic curve provided by the PV module manufacturers. The technique is designed to minimize the error between the reference I-V curve and the I-V curve reproduced by the DE algorithm. Through simulation results, the feasibility of the DE algorithm to estimate the desired parameters of a PV cell is validated, and the algorithm's performance to reach the best solution with fast convergence and a small iteration number is evaluated.

Environmental impact assessment of the manufacture and use of N- type and P-type photovoltaic modules in China

For a long time, solar power has been considered a clean and non-polluting energy source because it absorbs sunlight without consuming other energy or materials and does not emit pollutants. Nevertheless, the manufacturing and end-of-life stages of solar power systems leave an environmental footprint and produce pollutants. Hence, a global perspective on photovoltaic (PV) systems using life cycle assessment methodology is necessary. Here, we investigated the life cycle impacts of P- and N-type PV modules in terms of their energy consumption, carbon emissions, and human toxicity potential. In addition, the energy payback durations of P- and N-type PV modules were computed. In this study, we used the Life Cycle Assessment Basic Database from the National Engineering Laboratory of Industrial Big Data Application Technology at Beijing University of Technology to create a life cycle assessment model for N-type PV modules. Subsequently, we performed a life cycle assessment of Chinese silicon N-type- and P-type PV modules. The research system encompassed the production processes for metallic silicon materials, solar-grade silicon materials, silicon wafers, cells and modules, utilization, recycling, and other interrelated processes. We found that the production and processing of silicon-to-solar-grade polysilicon feedstock were crucial stages that significantly affected the energy consumption and environment of P- and N-type PV modules in China. The high electricity consumption of this process, combined with the dominance of coal power in China's electricity structure, contributed to the substantial energy consumption and environmental impacts of the PV modules. Therefore, this stage is critical for the low-carbon and environmentally sustainable manufacturing of N-type PV modules in China. Carbon emissions for both the P-type and N-type PV modules were lower only during the cell production phase but higher during the other stages when compared to the P-type and N-type PV modules. The n-type bifacial PV modules yielded the highest return on investment in terms of energy. Different regions and installation types have a substantial impact on the carbon emissions of P-type and N-type PV modules. Projections indicate that the potential to lower carbon emissions from n-type PV modules will increase by 2060.

Photovoltaic Manufacturing Factories and Industrial Site Environmental Impact Assessment

Life cycle inventories (LCIs) and life cycle assessments (LCAs) of photovoltaic (PV) modules and their components focus on the operations of PV factories, but the factories and industrial site product and construction stages are either not or only partially tackled. This work contributes through the bottom-up, model-based generation of LCIs and LCAs for setting up a vertically integrated 5 GWp/a PV industrial site, including the manufacturing of silicon ingots, wafers, solar cells, and PV modules, on a 50 ha greenfield location. Two comparative LCAs are performed. The first compares the annualized environmental impacts of the developed LCI sets with four existing inventories in the Ecoinvent v3.8 database. The second comparative LCA explores the environmental impact differences concerning the industrial site when using different building systems for the factories. Here, the reference system with a steel structure is compared with two alternative building systems: precast concrete and structural timber. The results show that the wafer, cell, and module factories’ annualized environmental impacts with the Ecoinvent LCIs are strongly overestimated. For the ingot factory, the opposite result is identified. The impacts of all four factories show reductions of between 11.7% and 94.3% for 14 of the 15 impact categories. High mean environmental impact shares of 79.0%, 78.2% and 79.2% for the steel, precast concrete and timber structural building systems, respectively, are generated at the product stage. The process and facilities equipment generates 54.2%, 54.4% and 58.2% of the total product and construction stages’ mean environmental impact shares. The proposed alternative timber building system reduces the environmental impacts in 14 of the 15 evaluated categories, with reductions ranging from 1.1% to 12.4%.

An improved hybrid solar cell defect detection approach using Generative Adversarial Networks and weighted classification

Quality control has a vital role in manufacturing processes. Electroluminescence (EL) imaging is one of the main non-destructive inspection methods for quality assessment in the Photovoltaic (PV) module production industry. EL test reveals PV cell defects such as micro cracks, broken cells, finger interruptions and provides detailed information about production quality. In recent years, automated detection and classification systems using deep neural networks for PV module inspection have gained increasing attention. However, deep learning-based systems usually require large amount of labeled data and high computational power. In this work, we proposed a compact classification framework based on hybrid data augmentation and deep learning models for detection of the defective solar cells. In the proposed method, the limited and imbalanced EL datasets were augmented through various Generative Adversarial Networks (GAN), and defect detection was achieved by customized pre-trained Convolutional Neural Networks (CNN). A novel hybrid EL dataset for training was formed by combining public ELPV dataset, our custom real-world dataset and synthetic images created with different GAN architectures such as GAN, cGAN and WGAN-GP. The datasets were classified through proposed customized VGG-16 and other state-of-the-art CNN models. The best results obtained by the proposed CNN model with WGAN-GP augmented dataset are 94.11% mean accuracy in the ELPV test dataset and 93.08% mean accuracy in the custom real-world test dataset. Therefore, the proposed detection system achieved superior performance with lesser resource usage and limited data.

The European Union's Ecodesign Directive – Analysis of Carbon Footprint Assessment Methodology and Implications for Photovoltaic Module Manufacturers

With an increasing shift away from fossil fuels toward renewable energy sources within the European Union (EU), photovoltaics (PV) are projected to see substantial growth with estimates of nearly 600 GWp of capacity by 2030. As the use of PV technology continues to expand, the European Commission has introduced various policy instruments, enabling consumers to make informed choices. Among those, the Ecodesign directive 2009/125/EC sets a carbon footprint threshold as a minimum qualification for the European market to cut out the least sustainable PV modules. For this directive, the methodological guidelines for the complex carbon footprint calculation of PV modules are under development. To this end, this analysis compares the two methodologies, namely Electronic Product Environmental Assessment Tool (EPEAT) and the Ecodesign adaptation of Product Environmental Footprint Category Rules (PEFCR), emphasizing the implications of choosing one over the other for the PV industry. This study illustrates how varying parameters, like module lifetime, degradation rate, and purchased renewable electricity certificate allowance limit, stemming from the differing methodological approaches can influence the carbon footprint calculation. Apart from the strengths and weaknesses of each methodology, this article emphasizes the need for globally harmonized standards to ensure consistency in evaluating the carbon footprint of PV modules. The observations made in this study should be considered not just for Ecodesign directive but for any such market regulation policy like the recently passed EU Net Zero Industry Act or the EU Ecolabel for PV modules. It underlines the significance of choosing a transparent and fair approach to ensure the credibility of carbon footprint labels and meet the EU's decarbonization objectives successfully, propelling the transition toward a more sustainable energy landscape.

Fraction order particle swarm optimization for parameter extraction of triple-diode photovoltaic models

This work proposes an application of Fractional Order Particle Swarm Optimization (FO-PSO), a meta-heuristic method for parameters estimation of photo-voltaic (PV) module as a non-linear, transcendental, multi-modal and implicit optimization problem. The uses single diode model (SDM), double diode model (DDM) and three-diode model (TDM) of PV modules with the constraint that only data-sheet information may be utilized. A fitness function based on the error amongst the computed values of current and voltage and the ones given in characteristic I-V curves of data-sheet, is minimized using the FO-PSO to get the required parameters. The comparative study between the estimated and data-sheet values provided by PV module manufacturers will determine the effectiveness of this research. The effectiveness of the FO-PSO is demonstrated by comparing the fitness values with that of other techniques. The FO-PSO technique makes a novel contribution to the PV power systems industry by making it possible to obtain a nearly realistic model of any commercial PV module. The effectiveness of the FO-PSO is determined by comparing the results for all the three models with the state of the art optimization techniques. The Root Mean Square error values calculated for the TDM is less than 10e–16, producing very consistent FO-PSO results. Therefore, FO-PSO is anticipated to be a competitive method for obtaining PV module specifications.

Efficacy of Enterprise Risk Management in Enhancing Sustainability and Financial Performance in the Solar PV Industry: A Conceptual Framework

As an alternative to fossil fuels, solar PV electricity can help mitigate global warming and improve the environment by lowering greenhouse gas emissions (GHG). More nations have developed programs to encourage the production and use of PV electricity, considering the potential of renewable energy for sustainable development. The government of Malaysia wants solar PV to be the primary source of renewable energy by 2030. To reduce global warming, renewable energy technology must be implemented more widely. However, the production of solar photovoltaic modules raises serious sustainability concerns. These concerns include using conflict minerals, toxicity, and limited supply or supply chain governance risks of rare materials. Even though solar energy projects are technically feasible, stakeholders still view the region’s initiatives as risky due to ongoing governance problems. Domains related to solar project deployment that involve installation, operation, and management are particularly susceptible to governance issues, such as a lack of accountability and transparency. Renewable energy investments upfront are risky and expensive. Risks in the solar PV value chain include subpar design and manufacturing decisions, inventory losses, quality problems during the execution process, and cultural and societal problems brought on by the absence of an effective risk management system. This study thus investigates how the implementation of ERM influences the company’s financial performance. Enterprise Risk Management (ERM) is a technique that regulates, and coordinates offset risks all over the firm to manage and integrate all risks holistically. As a result, this paper provides a conceptual and theoretical framework for how corporations use risk management to lower the cost of capital and improve sustainable development in the solar PV industry. The suggested theoretical and conceptual framework, supported by stakeholder and legitimacy theory, provides a foundation for empirically validating the entangled interaction between the relevant variables. It is advocated that measuring variables such as enterprise risk management, financial performance, and sustainability performance be based on previous research and frameworks and recommendations produced by major organizations. The purpose of this paper is to guide Malaysian solar PV companies in the implementation of sustainability and risk management.
 Keywords: enterprise risk management, sustainability, solar PV, financial performance

Estimation of Solar Cell Equivalent Circuit Parameters for Photovoltaic Module Using Differential Evolution Algorithm

The accurate estimation of solar module parameters is crucial for predicting the energy production of photovoltaic modules under different environmental conditions. In this paper, we present an approach for estimating the optimum parameters of a one-diode model using the Differential Evolution (DE) algorithm implemented in MATLAB. Our system enables the determination of these parameters at any solar irradiance and module temperature conditions, making it easy to apply the model for predicting the energy production of a photovoltaic module. The results demonstrate that the DE algorithm can estimate the parameters accurately. The numerical estimation technique based on a mathematical algorithm approximately fits all the points on the I-V curve at various environmental conditions. This work is a valuable tool for improving solar cells’ performance and efficiency and applies to many photovoltaic applications.

A Comprehensive and Sustainable Recycling Process for Different Types of Blended End-of-Life Solar Panels: Leaching and Recovery of Valuable Base and Precious Metals and/or Elements

The production of photovoltaic modules is increasing to reduce greenhouse gas emissions. However, this results in a significant amount of waste at the end of their lifespan. Therefore, recycling these solar panels is important for environmental and economic reasons. However, collecting and separating crystalline silicon, cadmium telluride, and copper–indium–gallium–selenide panels can be challenging, especially in underdeveloped countries. The innovation in this work is the development of a process to recycle all solar panel waste. The dissolution of all metals through the leaching process is studied as the main step of the flowchart. In the first step of leaching, 98% of silver can be recovered by 0.5 M nitric acid. Then, the second and third step involves the use of glycine for base metal dissolution, followed by the leaching of valuable metals with hydrochloric acid. The effect of parameters such as the initial pH, acid concentration, solid/liquid ratio, and hydrogen peroxide concentration is studied. The results show that up to 100% of Cu, Pb, Sn, Zn, Cd, In, Ga, and Se can be recovered under optimal conditions. The optimal conditions for the dissolution of Cu, Zn, and Cd were a glycine concentration of 0.5 M, a temperature of 25 °C, a solid/liquid ratio of 10 gr/L, and 1% of hydrogen peroxide. The optimized glycine concentration for the leaching of lead and tin was 1.5 M. Indium and gallium were recovered at 100% by the use of 5 M hydrochloric acid, S/L ratio = 10 gr/L, and T = 45 °C. Separation of selenium and tellurium occurred using 0.5 M HCl at a temperature of 60 °C. Additionally, for the first time, a general outlook for the recycling of various end-of-life solar panels is suggested.

The effect of storage conditions on the long-term stability of ethylene-vinyl-acetate (EVA) copolymer used in glass/glass modules

We evaluate the effect of storage conditions of uncured encapsulant rolls and the potential consequences on photovoltaic (PV) module performance. We show the impact of residual water trapped inside laminated double glass PV modules after lamination and during UV exposure. We focus on ethylene vinyl acetate (EVA) copolymer and its stability over 630 kWh/m2 UV exposure (equivalent to 10 years of outdoor exposure in a Central European country). Three storage conditions were tested by simulating different moisture contents to mimic relative humidity variations that can occur when polymeric foils are exposed to an uncontrolled environment, such as the PV module production line, next to the laminator machine. The presence of water during lamination had no apparent impact on module quality and performance after the fabrication but only became apparent during the aging test. The module power loss was directly related to the EVA chemical and physical degradation and varied depending on the storage history. Results indicate that when the storage is not too harsh, its effect can be somehow mitigated. Based on our observations, we leave a door open to the adoption of high-quality EVA polymers in the manufacturing of glass-glass modules. However, the storage and handling conditions prescribed by the supplier should be carefully respected.

PERFORMANCE EVALUATION OF THE IMPACTS OF METROLOGICAL PARAMETERS ON CRYSTALLINE AND AMORPHOUS MODULES AT MINNA, NIGERIA

Photovoltaic (PV) module performance is rated under standard test conditions (STC) i.e. irradiance of 1000 W/m², solar spectrum of Air Mass 1.5 and module temperature at 25°C. Manufacturers of photovoltaic modules typically provide the ratings at only one operating condition i.e. STC. However, PV module operates over a large range of environmental conditions at the field. So the manufacturer’s information is not sufficient to determine the actual performance of the module at field. Optimization of solar energy is affected by so many factors ranging from conversion efficiency of PV module to local metrological conditions. The research work therefore, evaluates the performance of three PV technologies using performance ratio. Metrological parameters such as solar radiation intensity, wind speed, relative humidity, and air temperature were measured simultaneously with the output electrical parameters from the three modules exposed to field test using metrological sensors and a CR1000 software-based data logging system with computer interface attached to the modules. Four years consecutives metrological and modules output data’s were collected from the modules and analyzed. The findings indicates that metrological parameters fluctuate non-linear with the modules output, under this conditions the trends as measured by the output power revealed that polycrystalline module has a better performance than amorphous module followed by mono-crystalline module in this experiment. The paper recommends the need to mitigate substandard modules entering our market through appropriate monitoring agencies and the setting of solar module laboratory for locally production of solar modules that would captures our local metrological parameters towards greater efficiency.

Effect of Solder Flux on Resistive Solder Bond Hotspot Generation in Photovoltaic Module Circuit Process and Restoration of Hotspot Module

In photovoltaic (PV) modules, resistive solder bond (RSB) hotspots are the primary cause for a reduction in output power of over 25%. They may be the result of inadequate soldering between the busbars and/or between the busbars and the interconnector ribbon during the circuit assembly procedure for the PV module. This study proposes a straightforward, dependable, and rapid method for reducing RSB hotspots in PV modules using additional solder flux during the circuit soldering process. The soldering of PV modules is examined in accordance with actual conditions present in PV module manufacturers during the manufacture of circuits. Using the tab pull test and the damp heat test, respectively, the bonding strength and dependability of the soldered connectors are evaluated. Connectors soldered with flux have a void ratio of 10% that is five times lower than connectors soldered without flux. In addition, connectors with flux decrease soldering strength by a range of −1.54% to −7.69%, whereas connectors without flux decrease soldering strength by a range of −17.39% to −29.31%. During long‐term reliability evaluations on repaired 370A and 370B samples, the RSB hotspots are substantially reduced by incorporating additional flux into the circuit process. In addition, the application of additional solder at the busbar to interconnetor ribbon soldering site prevents RSB hotspots effectively. The results are anticipated to provide comprehensive and straightforward solutions for significantly reducing RSB hotspot failures in commercial PV modules.

Encapsulant Materials and Their Adoption in Photovoltaic Modules: A Brief Review

In the last two decades, the continuous, ever-growing demand for energy has driven significant development in the production of photovoltaic (PV) modules. A critical issue in the module design process is the adoption of suitable encapsulant materials and technologies for cell embedding. Adopted encapsulants have a significant impact on module efficiency, stability, and reliability. In addition, to ensure the unchanged performance of PV modules in time, the encapsulant materials must be selected properly. The selection of encapsulant materials must maintain a good balance between the encapsulant performance in time and costs, related to materials production and technologies for cells embedding. However, the encapsulants must ensure excellent isolation of active photovoltaic elements from the environment, preserving the PV cells against humidity, oxygen, and accidental damage that may compromise the PV module’s function. This review provides an overview of different encapsulant materials, their main advantages and disadvantages in adoption for PV production, and, in relation to encapsulant technologies used for cell embedding, additives and the interaction of these materials with other PV components.

Modeling of the effectiveness of novel edge seal designs for fast, low‐Cap‐Ex manufacturing

AbstractIn the manufacturing of photovoltaic (PV) modules, the lamination process can take up to 20 min to complete. In this work, new lamination processes are being developed, and have been prototyped, which hope to be able to cut this time down to as little as 30 s. This could provide significant savings in the cost of lamination equipment, floor space, and energy. PV modules are expected to have a lifespan exceeding 20 to 30 years. For moisture‐sensitive PV technologies, the edge seal between the two layers of glass can be the weakest point of its reliability. There is an inherent challenge when evaluating edge seal materials due to their low permeation rates. As part of Colorado State University's Photovoltaic Research and Development 2, work at the National Renewable Energy Laboratory has developed models to evaluate edge seal configurations in glass‐glass PV modules. Here, this new manufacturing process is evaluated for long‐term moisture durability. Different edge seal design options within glass–glass PV modules are explored. Most of these designs are targeting a superstrate on glass configuration, e.g CdTe, but some designs could be used on conventional crystalline Si cells. Using COMSOL finite element simulation software, we investigated the edge seal and interlayer design configurations containing silicone perimeter edge adhesive, desiccated polyisobutylene‐based edge seal, air, and polyolefin while integrating climate conditions equivalent to a hot and humid environment such as Miami, Florida. We found optimized configurations that will allow the module to prevent moisture ingress over 50 years minimizing the amount of time and material used while utilizing polymers that are easily dispensed.

Microwave annealing of silicon solar cells

The microwave annealing of semiconductor devices has not been extensively researched and is rarely utilized in industry, yet it has the potential to significantly reduce the time and cost associated with large-volume semiconductor processing, such as the various heating and annealing processes required in the manufacture of photovoltaic modules. In this paper, we describe microwave annealing of silicon solar cells, the effective passivation of light-induced defects, and a reduction in light-induced degradation. We find that silicon solar cells are heated rapidly in a microwave field and that effective B–O defect passivation can be achieved by microwave processing in less than 2 s. Microwave annealing yields similar results as compared to rapid thermal annealing.

Environmental Assessment of Solar Cell Materials

Abstract In today’s world, fossil fuels, including coal, oil, and gas, are the primary energy sources from which electricity is obtained. As they are exhaustible and their exploitation has a negative impact on the natural environment, they should be, at least partially, replaced by renewable energy sources. The implementation of this goal depends on a number of factors, including social and political, the existence of investment support programmes, and the need to lower electricity prices and ensuring energy security. One of these sources is solar energy. Each year, the Earth receives around 1 · 1018 kWh of solar energy, which is more than 1000 times the current global energy demand. This is therefore a vast source of energy that can be tapped to satisfy human energy requirements. The use of solar energy releases no CO2, SO2, or NO2 gases, and does not contribute to global warming. Photovoltaics is one of the technologies that makes it possible to generate electricity in an environmentally friendly manner. By using the energy of solar radiation, a photovoltaic cell converts energy without emitting harmful substances to the atmosphere, noise, and waste. Photovoltaics is the cleanest technology among all the technologies that use renewable energy. Considering the shorter and shorter times needed to generate energy equal to that required by the module production process, during its lifetime it will produce much more electricity than was used to produce it. This results in a reduction in greenhouse gas emissions. For example, during its lifetime, a 200 Wp module prevents the emission of over four tonnes (Mg = 106 g) of carbon dioxide. Although the technologies for the production of photovoltaic cells and modules entail a lower environmental burden compared to other sources of electricity, it is necessary to remember about the risks associated with the use of chemicals at the stage of module production, which threatens their release to groundwater or air, and the need to recycle modules after their disassembly. Also, the energy consumption in the production phase of PV systems significantly worsens the ecological balance. This article presents an analysis of the impact of the materials and technologies used on the result of the environmental analysis of PV installations. In the article a detailed energy balance analysis of the EPBT value has been carried out. The values of greenhouse gas emissions throughout the life cycle of the solar module were determined. Methods of limiting the impact of photovoltaic technologies on the natural environment were indicated.

Using On-Site Measurements to Identify and Adjust PV Single-Diode Model Parameters for Real Operating Conditions

Photovoltaic (PV) module manufacturers specify their products’ performance under the standard test condition. However, such a condition is hardly found outdoors, that is, during actual operation of photovoltaic systems. Despite that, many modeling methods proposed in the literature rely on standard test condition data for parametric identification. This paper presents an experimental study concerning different modeling approaches for photovoltaic modules, focusing on assessing model performance in different scenarios. The goal is to assess the influence of the data used for the model parametric adjustment when predicting the maximum power point of two photovoltaic modules, allowing the most advantageous methods to be identified. By using an experimental outdoor photovoltaic platform, over 30,000 I-V curves referring to two photovoltaic modules were measured for 16 months. Different models were applied for cases where their parameters were identified using field measurements. It was found that using measurements obtained under real operating conditions to adjust the model parameters provides significantly better prediction of the maximum power in comparison to cases employing data sheet-extracted information. For the all methods and cases studied, using in-field measurements to adjust the model parameters provided average root-mean-square error of 3.4% for power predictions, whereas the average error level found when using data sheet information was 8.8%. An error level as low as 2.83% was reached by adopting the most complex model, although using a significantly simpler modeling approach provided error of 3.25%. Therefore, using field-measured data to adjust model parameters produced the best results, but increasing method complexity did not increase performance in the same scale.

Availability of Raw Materials for Indigenous Manufacturing of Solar Photovoltaic Modules in Nigeria

Nigeria is well positioned as one of the nations of the world with abundance resources in the areas of oil, gas, petrochemical and solid minerals. Despite this feat, the nation is still struggling to meet up with the local production of raw materials for its industry. With its recent interest in the transitioning to clean, affordable and sustainable electricity, Nigeria is in dire need to meet up with the continuous energy demand. This calls for urgent need for local production of raw materials for it to be self-reliant in the local production of solar PV modules. This research therefore provides insight on the availability of required critical materials deposit in the country which has been serving as one of the major barriers of indigenous solar PV manufacturers such as NASENI Solar Energy Limited in the country. Related literatures were reviewed to adequately formulate the research problem statement. This work will serve as a policy redirection to interested stakeholders in the industry.

Combining circularity and environmental metrics to assess material flows of PV silicon

A product made from virgin raw materials that ends up in a landfill presents a linear supply chain model. Today's photovoltaic (PV) industry is still largely based on this model. With the increasing volume of production, the raw materials required for it, and consequently the volume of waste, the application of circular economy principles in the PV sector can significantly increase its environmental efficiency. This study analyzes the impact of circularity on the supply chain of PV silicon used for PV module production. Four scenarios based on the combination of technological pathways and circularity options are created. Their evaluation is carried out by the methodologies of Material Circularity Indicator (MCI) and Life Cycle Assessment (LCA). The State-of-art case of the PV polysilicon supply chain corresponds to the MCI score of 0.54. Closed-loop circularity solutions provide the MCI score of 0.80 presenting the potential for a circular economy approach in the industry. LCA results show the reduction of environmental impact by 12% with improved circularity. The study presents the benefits of potential circularity options within the supply chain as well as the impact of technological development on the polysilicon demand.

Sistem Pengendali Mesin Solar Cells Automatic Tabber Stringer pada Penyolderan String di PT. Indonesia Solar Global

In the production of photovoltaic modules, solar cells are an input that is processed to produce a photovoltaic module output. The core process of making photovoltaic modules is at the soldering stage of solar cells until the solar cells are assembled in series and become a string. The soldering process at PT. Indonesia Solar Global is done automatically using a machine called Solar Cells Automatic Tabber Stringer. This soldering machine uses the infrared soldering method in which the light produced from infrared produces heat energy so that it can solder the solar cells. So that in the soldering process using this machine an analysis is carried out to be able to classify what type of control system is on the Solar Cells Automatic Tabber Stringer machine. This research was conducted using data collection by means of interviews and direct observation in the field. This research produces new knowledge related to the type of control system that exists in the Solar Cells Automatic Tabber Stringer machine which is capable of soldering solar cells to produce a string output.