PV Installations Research Articles

Organizational and Economic Mechanisms for Promoting Residential Battery Energy Storage Systems in Ukraine

Energy storage technologies are one of the ways to decrease the intermittency of renewable energy such as sun or wind. The article aims to consider the organizational and economic mechanisms of promoting residential battery energy storage systems (R-BESS) in Ukraine, as households have ensured the significant growth of installed capacities of residential PV installations, reaching 1.4 GW by 2024. The energy system of Ukraine faces balancing challenges, and partial covering of the demand for energy by households with the help of R-BESS should be beneficial for the energy system. Using methods of levelized cost of electricity and cost of storing electricity, and based on the projected electricity demand and the number of R-BESS, measures were suggested to stimulate the R-BESS installation. Significant investments are required to employ R-BESS, reaching EUR2024 2.9-3.6 billion by 2050. If the interest rates for loans are subsidized, the expenditures on subsidies will reach only EUR2024 35-44 million, and the households themselves must allocate the remainder of the funds.

Cost-Effective Dust Detection on Solar PV Panels through Deep Learning: A Step towards Automated Maintenance Systems

Abstract: Accumulation of dust on solar panels impacts the overall efficiency and the amount of energy it produces. Detecting and mitigating dust accumulation is therefore crucial for optimizing solar energy production. While various techniques exist for detecting dust to schedule cleaning, many of these methods uses licensed software like MATLAB, which can be financially burdensome. This study proposes the use of modified pre-trained ResNet-50 model architecture with an adjusted fully connected layer for binary classification. An experimental setup was installed utilizing a single 75 Wp panel with an inclination maintained at 30-degree angle. The fine dirt particles were artificially introduced and datasets of images of clean and dusty panels were collected from five different sides were taken, to compensate for the surface reflectance from the PV panel due to camera angles. Those datasets were used to train and test the model and the accuracy achieved was 90%. The model's ability to detect dust with minimal false positives ensures more efficient maintenance scheduling. This research demonstrates the potential of AI-driven dust detection systems to enhance the operational efficiency of solar PV installations.

Secure low-cost photovoltaic monitoring system based on LoRaWAN network and artificial intelligence

The advanced study will focus on developing a secure and cost-effective photovoltaic monitoring system using Long Range Wide Area Network (LoRaWAN) and Artificial Intelligence technologies for highly risky missions. With the world shifting to using renewable energy, the development of secure and efficient cost-effective monitoring systems for photovoltaic installations becomes very important. However, most of the solutions in use for PV installation monitoring are characterized by high costs, hence their limited use, especially in developing regions. In this regard, the present work presents country-specific protocols designed for the country of Turkey. The proposed system in this study is expected to offer real-time monitoring and data collection at a very meager cost by utilizing inexpensive microcontrollers and sensors. The accuracy rate demonstrated by the research is highly above board: 97.65%. It costs $210, with a very low power consumption of 0.5W and a range of 10 km. The major features underpin real-time monitoring with wide area coverage for effectiveness and efficiency in PVs monitoring. Test results in many places around Turkey have turned out reliable and accurate to justify a possible reduction in operational costs without compromising the quality of data received. This design is reinforced by a detailed mathematical model that assures one of its thorough analysis in performance. There is custom-built firmware that enhances communication efficiency and ensures data integrity in implementation. Comparative studies carried out with existing technologies indicate that the proposed system is cost-effective and operationally sound. This work gives a scalable, low-cost solution that probably might raise the uptake of PV systems in economically constrained areas.

Modelling and experimental investigation of cooling of field-operating PV panels using thermoelectric devices for enhanced power generation by industrial solar plants

The performance of commercial solar power plants degrades due to an increase in module temperatures for which standard PV-T air or water-cooling techniques are mostly used. In this study, a thermoelectric cooling system is studied for improving photovoltaic cell power efficiency and hence solar power generation. The cooling optimization requires solar cell temperature prediction of field operating PV modules, for which analysis of six models, is presented. The experimentation results show that TEC cooling maintains PV cell at 25 °C whereas PV cell without TEC operates at 55–63 °C, a higher temperature range, showing the effectiveness of the thermoelectric cooling system in precisely controlling PV cell temperature to operate at or near STC conditions in the field creating a temperature difference of 30–38 °C. The NOCT and Faiman model results are found close to the experimental values in comparison to other models. The potential for cooling and a corresponding increase in solar plant energy production is assessed using PV Syst modeling and simulation for three practical PV installation scenarios for 31 different climatic zone locations worldwide showing 6–27 % power loss due to elevated temperatures, which is not studied in previous studies adding novelty to the analysis. The results show that PV-TECS is an effective system to control the temperature of field operating PV modules, which can be used in future photovoltaic power plants. Field results and analysis of PV temperature models is crucial for the optimization and future development of PV-thermoelectric systems deployed under actual outdoor conditions as well as the expected cooling gains in different climatic locations. These aspects are collectively studied in the current work adding to the novelty of the study.

Assessment of the Profitability of a Photovoltaic Installation Cooperating with Energy Storage Using an Example of a Medium-Sized Production Company

This work aims to comprehensively analyze the cooperation of an electricity storage facility with an operating photovoltaic installation in a manufacturing company regarding the efficiency and effectiveness of the device and the economic profitability of the investment. This work aims to check the benefits that can be brought by expanding the PV system with an electricity storage facility. Based on the real energy balance and the characteristics of electricity distribution in the company, profitability calculations were carried out reflecting the expected savings generated by using individual solutions. These methods allowed the authors to calculate the market value of the investment with the assumed boundary criteria and to determine the economic effectiveness of the investment. Additionally, the practical process of selecting an electricity storage facility was presented and key moments in the company’s energy report were analyzed, in which the use of a battery could bring results. Calculations showed that supplementing the described PV installation with an energy storage facility will increase the current level of self-consumption of PV energy by over 14%. The benefits translate into the final effect of energy storage operation, which brings additional annual savings for the company of approximately EUR 23,000 in the case of a weaker device and roughly EUR 40,000 in the case of a more powerful energy storage device. The proposed research could improve the planning of new industrial plants for photovoltaic installations, as well as the redesign of existing ones.

A genetic algorithm approach for flexible power point tracking in partial shading conditions

A novel Flexible Power Point Tracking (FPPT) algorithm based on Genetic Algorithms (GAs) is presented in this study. The algorithm is designed to effectively handle fluctuating solar irradiation levels and partial shading scenarios. The main objective is to enhance power output and tracking accuracy under dynamic environmental conditions, based on extensive simulations. The results showed superior performance for power output, tracking accuracy, and convergence speed than traditional techniques. Its adaptability to changing environmental conditions renders it suitable for real-time implementation, thereby contributing to efficient power generation in PV systems. Simulations demonstrate the efficacy of the algorithm in maximizing power extraction and meeting grid-code requirements under dynamic conditions. The comparative analyses underscore the superiority of the GA-based FPPT algorithm, highlighting its potential to significantly improve power point tracking in photovoltaic systems. This shows significance of adaptive algorithms in modern PV systems, particularly for reducing the effects of partial shading on energy yield. More research is required on the refinement of the algorithm's performance for long-term reliability and scalability in larger PV installations fostering advancements in photovoltaic power point tracking toward sustainable energy systems.

Comparison of the Energy Efficiency of Fixed and Tracking Home Photovoltaic Systems in Northern Poland

The relevance of the article’s results lies in presenting the actual energy yields of PV panels of various generations and types of installations. The aim of the article is to provide answers about the effective operation of three different photovoltaic systems: a stationary off-grid system operated for several years, a stationary on-grid system, and a system mounted on trackers. A stationary on-grid system was used as the reference system, taking its area and energy yield as the reference point. The assessment was made on the basis of energy and cost efficiency analysis using the comparative method. The obtained results were compared to the results of other PV systems whose parameters were obtained from literature analysis. The analysis showed significant differences in adapting them to different sunlight conditions. The results confirmed the validity of using fixed PV panels (Installation II) in the short term and the advantage of the PV panel tracking system (Installation III) in the long term. The results also confirm that Installation I, despite its eight years of operation time, shows a relatively small decrease in efficiency, which confirms the validity of the long-term operation of the PV installation.

Assessing the Features of PV System’s Data and the Soiling Effects on PV System’s Performance Based on the Field Data

This paper assesses the features/characteristics of a photovoltaic system’s data, investigates the relationship between the soiling and solar panel performance, and leverages real-world data obtained from a solar site in Shams Solar Facility located at the German University of Technology in Oman. Through an experimental approach, different parameters were scrutinized to unravel the dynamics at play. Due to the lack of studies on how to assess the features of a PV System’s data, and in order to model the PV System’s data, extensive analyses were conducted based on a big dataset containing 36,851 observations of each parameter (environmental factors) of the study. In addition, diverse environmental factors, operational conditions, and the collected data were analyzed by various mathematical/statistical measures, and inferential statistical measures were applied to obtain accurate and significant results that explain the level of each parameter (environmental factors), and are developed to examine the features/characteristics and performance of PV Systems and reveal the influence of soiling accumulation on the energy output. The research findings do not only deepen the understanding of the features of PV Systems data and the impact of soiling on solar panels, but also underscore the significance of considering geographical and climatic variations. This research contributes significantly to advancing knowledge within the realm of solar energy systems and provides actionable insights for optimizing the performance and reliability of PV installations in real-world settings. The discussion, conclusions, limitations, and future directions have been discussed.

Simulation of Rooftop Solar Photovoltaic for Tourist Accommodation Villa as a Mean to Promote Green Tourism in Bali – Indonesia

Abstract Indonesian government renewable energy mix can be accelerated if tourism industry also contributes to the generation of green electricity such as rooftop solar PV, especially for Bali Province as the world tourist destination with thousands of accommodations spread across the Bali island. In this research, the feasibility analysis to implement rooftop solar PV in Sanctoo Suite and Villa located in Gianyar Regency, Bali Province was carried out using Helioscope software simulation. The design was aimed to maximizing the benefit of free rooftop space with financial investment cost of installation. It was determined to reduce electricity bill of 345 kVA load capacity of the villa operation. Based on the simulation, the rooftop solar capacity of 69.3 kWp was available. Furthermore, the energy output generated by the rooftop solar PV annually was around 106.4 MWh. From financial analysis, the monthly electricity bill saving achieved was on average around 12 %. Further calculation on NPV and IRR shows positive value for feasible investment. It was estimated that the payback period for the investment will be around 18 years. These results showed that installation of rooftop solar PV for tourist accommodation is feasible and will promote green tourism for the industry in Bali.

LCZ-based city-wide solar radiation potential analysis by coupling physical modeling, machine learning, and 3D buildings

Addressing climate change and urban energy problems is a great challenge. Building Integrated Photovoltaics (BIPV) plays a pivotal role in energy conservation and carbon emission reduction. However, traditional approaches to assessing solar radiation on buildings with physical models are computing-intensive and time-consuming. This study presents a hybrid approach by integrating physical model-based solar radiation calculation and machine learning (ML) for city-wide building solar radiation potential (SRP) analysis. By considering urban morphology, land cover, and meteorological characteristics, local climate zones (LCZs) are classified. The SRP of representative LCZs is precisely evaluated using computing-intensive physical models integrated with 3D building models. A ML model is then developed to effectively predict the SRP of building roofs and facades throughout the city. An experiment was conducted in Shenzhen, China to validate the presented approach. The results demonstrate that Shenzhen has a total annual building solar radiation of 3.28∗1011kwh. Luohu District exhibits the highest SRP density. The LCZ-based analysis highlights that compact low-rise LCZs offer greater SRP for roofs, while compact high-rise LCZs do so for facades. Moreover, BIPV could cut CO2 emission by up to 41.85 million tons annually. Notably, solar PV installation only on rooftops in Shenzhen could meet 87.81% of the city's electricity department's carbon reduction goal. This study provides an alternative for city-wide SRP estimation by combining physical modeling and ML and offers valuable insights for data-driven and model-driven urban planning and management in low-carbon cities.

Integration of Crops, Livestock, and Solar Panels: A Review of Agrivoltaic Systems

This review article focuses on agrivoltaic production systems (AV). The transition towards renewable energy sources, driven by the need to respond to climate change, competition for land use, and the scarcity of fossil fuels, has led to the consideration of new ways to optimise land use while producing clean energy. AV systems not only generate energy but also allow agricultural and livestock yields to be maintained or even increased under PV structures, offering a sustainable production strategy that may be more acceptable to local communities than traditional PV installations. This review assesses the technical feasibility of AV systems, the environmental, economic and social benefits, as well as the challenges faced and the legal framework regulating their implementation. It is highlighted that despite the advantages in land use efficiency and dual food and energy production, there are important challenges related to the initial investment required, the need for technological adaptation, social and regulatory obstacles, or the effects of shading on production. This paper underlines the importance of further research and development of these systems to overcome technical and economic constraints and maximise their potential benefits. It is concluded that although they present significant challenges, AV management offers promising opportunities to improve land efficiency and contribute to several sustainable development goals.

A Model Validatory Approach in Determining Solar Panel Tilting Angles and Orientations at the Brikama Environment of The Gambia

Solar energy demand in The Gambia has got a boost in recent times owning to it cleaner nature and affordability compared to other renewables and by this many people are shifting towards solar PV installation. To optimize the design of any PV system for maximum performance, adequate knowledge of the orientation and tilt angles of the solar panel against the sun radiation received by the solar panel is vital. This paper determines the solar optimal tilt angle and orientation of solar panels in the Brikama environment of The Gambia. This was achieved by comparing a mathematical model results with experimental data collected using a PV module (Model AP-120) manufactured by AstroPower, Inc., Deleware, USA, and single axis tracker technology at the same location and months of the year 2022. The experimental tilt angles obtained range from 29.85-30.14 with an average angle of 29.99 while the mathematical model approach obtained the tilt angle to be 30. By comparing all the values recorded during the experiment, the peak value of power generated by the solar panel was recorded at an angle of 30due South and this proves our techniques in determining the tilted angles with our applied model. The monthly tilt angles of the solar panel, which were averaged from the total months of the year and the average tilt angle in the Brikama environment is 15.5and the solar module should face south during installation for optimization. These results are vital in maximizing solar energy collection from photovoltaic systems.

Are alpine floatovoltaics the way forward? Life-cycle environmental impacts and energy payback time of the worlds’ first high-altitude floating solar power plant

Floating photovoltaics (FPV) and high-altitude PV installations are increasingly gaining importance in the sustainable energy sector, each technology holding its own potential. A pioneering high-altitude FPV installation in Switzerland represents the first implementation of combining the two technologies. In order to determine the environmental performance of such an installation, the present study examines the life-cycle environmental impact of the world’s first high-altitude FPV system, using Life Cycle Assessment (LCA). Our results record life-cycle greenhouse gas emissions of 94 g of CO2–eq per kWh of electricity produced by the high-altitude FPV system. The non-renewable primary energy demand amounts to 10′810kWh oil-eq/kWp, which equals an energy payback time of 2.8 years. Environmental hotspots in the life cycle of the installation were found to be the production of the PV panels, due to the wafer production, and the mounting system, dominated by the production processes of the aluminium. Comparison to other PV installations identifies the mounting system as the main point of issue in the high-altitude FPV installation, due to a more intensive aluminium use. It was found that the high-altitude FPV installation can generally compete with alternative PV systems in the lowland, with its environmental impacts lying in the range of −45 % and + 15 %, while being largely outperformed by ground-mounted PV installations at high altitude. By implementing measures such as transitioning to renewable energies in the PV panel and mounting system supply chains, as well as reducing aluminium use for the mounting system, FPV systems hold great potential to help meet the increasingly growing demand of renewable energy sources.

Decarbonisation at least cost: an analysis of the optimal portfolio of instruments

Purpose This paper aims to propose a methodology for assessing an optimal portfolio of investment instruments that minimise the social costs of decarbonising economic activity while improving the environmental objectives proposed in EU legislation. Design/methodology/approach The methodology defines the net social cost of decarbonisation related to a portfolio of four instruments: installation of solar PV and wind generation, thermal insulation of households and deployment of heat pumps. The social cost is minimised by restricting it to the minimum level of the targets proposed in the Spanish National Energy and Climate Plan to reduce greenhouse gas emissions, increase generation from renewable sources and reduce energy consumption. The empirical approach also includes differences between regions according to the expected effect for instruments. Findings The application of this methodology to the environmental objectives defined in the current Spanish National Energy and Climate Plan for 2030 concludes that it is clearly possible to reduce the social cost of decarbonisation while improving environmental performance through a reorientation of investment instruments. In this case, such a reorientation would be based on a minimisation of efforts in thermal insulation of households and a maximisation of measures aimed at the installation of heat pumps. Originality/value The paper proposes a novel methodology for a social cost assessment that improves the allocation of a portfolio of environmental instruments. This portfolio could be extended in further work to include instruments related to transport or support for industrial decarbonisation, such as the deployment of renewable hydrogen, among others.

Optimal sizing of a fixed-tilt ground-mounted grid-connected photovoltaic system with bifacial modules using Harris Hawks Optimization

This paper presents an optimal design for ground-mounted grid-connected bifacial PV power plants using a Computational Intelligence (CI)- based Harris Hawks Optimization (HHO) algorithm. This HHO algorithm identifies the best configuration of components and installation parameters for the bifacial PV power plant, aiming to maximize the final yield, minimize the Levelized Cost of Electricity, and boost the Net Present Value. Four variables were optimized: the bifacial PV module model, inverter model, tilt angle, and module elevation. Furthermore, the paper introduces a Harris Hawks Optimization Sizing Algorithm (HHOSA) to address the sizing challenges. The presented HHOSA was purely developed in Matlab R2017b. The usage of PVsyst was only limited to the derivation of irradiation data at different tilt angle of PV array. These data were later used in HHOSA. To verify its effectiveness, HHOSA was benchmarked against other CI algorithms, including the Slime Mould Algorithm (SMA), Firefly Algorithm (FA), Manta Ray Foraging Optimization (MRFO), and Cuckoo Search Algorithm (COA). The evaluation considered the algorithm’s stability, local search capability, convergence rate, computation time, and required population size. Findings suggest that the HHOSA outperforms its peers, marking it as a potential leader for designing bifacial PV power plants. The results indicate that the HHOSA algorithm exhibits superior performance in these aspects, making it a promising approach for optimizing the design of bifacial PV power plants. Moreover, this study provides insights into the economic and technical viability of bifacial PV systems under various environmental and system conditions. A sensitivity analysis, focusing on the interplay of three decision variables − albedo values (25 %, 50 %, and 75 %), tilt angles (10°, 25°, and 35°), and module elevations (0.5 m, 1.5 m, and 2 m) − was conducted. It assessed their influence on final yield, additional bifacial PV module yield, Levelized Cost of Electricity, and the system’s Net Present Value. The results emphasize the importance of carefully considering the impacts of albedo, module elevation, and tilt angle on the financial performance of bifacial PV installations.

Suns-Vmp method for health monitoring of 110 PV modules

One can monitor the health of the PV modules by analyzing their current-voltage (I–V) curves, which rarely are measured in commercial settings. Fortunately, nearly all PV installations measure the maximum power point current (Imp) and voltage (Vmp), along with the ambient weather conditions, which the proposed Suns-Vmp method uses to generate pseudo I–V curves. In this work, the proposed methodology was rigorously tested on 110 PV modules of various technologies installed under harsh desert conditions, for approximately 7 years and 9 months. For these modules, the fitting accuracy between the actual field measured and pseudo I–V curves, did not exceed an RMSE value of 0.35 A. The median power degradation of the mono-crystalline, poly-crystalline, and thin-film technologies were estimated to be around 0.21 %/year, 0.49 %/year, and 1.51 %/year. From the root-cause analysis using the fitted PV parameters, it was found that the dominant degradation contribution in all the modules came from series resistance, followed by shunt resistance. For mono-crystalline, poly-crystalline, and thin-film technologies, the mean yearly rate of change for series resistance was 1.47 %, 4.37 % and 13.37 %, while for shunt resistance these values were 0.68 %, 1.26 % and 3.95 % respectively. As field measured I–V curves are seldom available, techniques like the Suns-Vmp method can offer valuable insights for effective solar farm management and maintenance, without any interruption in the operation.

How will manufacturing capacity additions in China and North America affect the carbon footprint of silicon photovoltaics?

Global annual PV installation is expected to increase from 150 GW in 2021 to 820 GW in 2030 to reach net zero emissions by 2050. Electricity production from PV generates almost zero carbon emissions, but the emissions from the manufacturing phase are nonnegligible. While most installed PV modules in the US are imported from China, manufacturers are expanding the manufacturing capacity in North America to reduce reliance on Chinese PV modules. Although it has been commonly perceived that the North American modules would have a lower environmental footprint than Chinese ones, the effect of capacity expansions and regional impact considering where each component is produced has yet to be fully understood. This study aims to compare the carbon footprint and cumulative energy demand of PERC modules manufactured in China and North America based on the expected 2024 manufacturing capacity additions. We develop PV manufacturing scenarios to perform life cycle assessment (LCA) for the first time considering the regional manufacturing capacity, partnerships between suppliers and manufacturers, and regional electricity grids, while previous PV LCA studies evaluated the national average production. The carbon footprint of China's PERC modules for monofacial and bifacial designs, when using the national average grid, is 517 and 412 kg CO2eq/kWp, respectively. In comparison, the GWP of modules produced in North America is 22.0–22.2 % lower than in China, a difference attributed to the lower carbon footprint of electricity grids. When considering where each component is made, the GWP increases by 1.5 % in China compared to the national average. This difference arises because most of China's solar manufacturing facilities are in regions with higher carbon intensity grids than the national average. Solar manufacturers can reduce the carbon footprint of their products by changing manufacturing locations or increasing the share of renewable sources for manufacturing. We find that both China- and North America-made PERC modules meet the Electronic Product Environmental Assessment Tool (EPEAT) low carbon solar criteria (630 kg CO2eq/kWp). However, to meet the ultra-low carbon solar criteria (400 kg CO2eq/kWp), a significant share, approximately 60 % for China and 15 % for North America, of the total electricity supply must be sourced from renewable energy in addition to the existing grid. This study identifies the significant impact of manufacturing locations on the overall carbon footprint of PV modules. It is important to consider production locations by stage and the regional electricity supply when developing the carbon assessment methodology of PV modules. Otherwise, manufacturers may take advantage of assessing carbon footprint using the country's average grid while producing products in dirty grid regions.

Integrating Renewable Energy Solutions in Small-Scale Industrial Facilities

The purpose of this study was to analyze the economical suitability of numerous on-site renewable electricity generation technologies which were intended to be used in a recently built industrial facility designed and utilized as a warehouse. The facility was located in the vicinity of Riga, Latvia. Data were collected and calculations were performed within the scope of the project “Mitigating Energy Poverty through Innovative Solutions” as part of several planned activities to address the broad spectrum of energy poverty and self-reliance issues in both the residential sector and small-scale industrial facilities. During the project, evaluations of various renewable energy technologies, including PV installations, wind energy installations, battery storage solutions, and hybrid technologies, were carried out. The aim of these evaluations was to develop an electricity production–consumption model for efficient and cost-effective energy use and to reduce greenhouse gas emissions from the test facility. A model was created and subsequent research scenarios were developed based on a payback period instead of the net present value criterion. The project was carried out over several steps to develop a calculation methodology. The open access databases of energy resource providers were used to evaluate statistical data and make forecasts for the analysis of the electricity consumption of companies. MATLAB/Simulink 23/2 was used for the data analysis, and the H-TEC method was employed. This made it possible to modulate the required production capacity as the model allowed for the addition of new modules to modules already installed. The project results proved that despite high initial investment costs, renewable energy sources and efficient storage systems can provide cost-effective solutions and reduce dependence on fossil fuels in the long term.

Analysis of photovoltaic self-consumption as a function of the demand profile in detached houses

Self-consumption PV installations in the residential sector have a great potential to mitigate emissions associated with fossil fuels. However, few studies analyse the influence of the seasonality of the prosumer’s consumption habits on the evaluation of PV self-consumption.Thus, this work develops a detailed analysis of the evaluation of self-consumption and self-sufficiency as a function of different variables, such as the size of the installation, consumption habits, and existing installations in the home, among others. In addition, a sensitivity analysis is carried out, in which it is studied how a change in the hourly and monthly distribution of consumption influences self-consumption.The results show the importance of considering the prosumer’s consumption habits. Dwellings with electric heating have a greater potential to increase self-consumption than other dwellings, while in low-consumption dwellings the hourly or seasonal distribution of consumption does not play as important a role as in high-consumption dwellings. On the other hand, it is shown that the hourly distribution is much more significant than the monthly distribution since improvements in the hourly distribution of consumption can increase self-consumption and self-sufficiency by 21.05 % and 29.6 %, respectively.

Failures and performance of different aged PV modules operated under northern Algerian climate conditions: Analysis, assessment, and recommended solutions

This paper analyzes, assesses, and compares the failures and performance of various PV module types deployed at six PV installations located in different regions of northern Algeria, under Mediterranean climatic conditions. Qualitative data has been considered by selecting the best and worst-performing PV module samples for each of the six PV module types, along with other PV samples exhibiting specific permanent failures. Subsequently, the following IEC 61215 inspections were conducted: visual failures inspection, electrical performance inspection, thermal failures inspection, and insulation failures inspection. The results of these failure inspections indicate that different types of PV modules exhibit varying performance. Interestingly, the disparities are more pronounced between the PV module types than among the PV module samples within the same PV module type. This gap is at least ten times higher in terms of yearly degradation rates. However, some of the PV module types with high failure occurrence, severity, and exposure duration exhibit high performance compared to other types that have low failure occurrence, severity, and exposure duration. Meanwhile, there is no obvious and clear correlation between the different PV inspections, especially for PV module types. Thus, our analysis of the obtained results leads us to conclude that the significant disparity in failures and performance among the tested PV module types is primarily attributable to differences in their quality rather than the influence of local climate conditions or working conditions. Out of the six PV module types, only one will meet the 25-year warranty provided by the manufacturer, providing valuable insights into the prevalence of poor-quality PV modules in PV installations and those available in Algeria. Finally, a list of recommended solutions has been proposed to the Algerian government and other countries facing similar challenges to integrate into their national infrastructures and frameworks (quality, technical, qualification, and policies). These solutions aim to ensure the high quality, performance, and long lifespan of PV modules and PV installations.