Photovoltaic System Research Articles

Design and analysis of power decoupling based microinverter considering parasitic parameters

With fossil energy reducing year by year, more and more attention to the new energy sources greatly promotes the development of the distributed power generation system, especially the low-power photovoltaic system. However, the power injected into the single-phase grid is time-varying, an electrolytic capacitor with large bulk should be paralleled with PV to balance the input and output power ripple. But the electrolytic capacitor has a very short lifetime, which could shorten the whole inverter’s lifetime. In this paper, the operational principle of the power decoupling based microinverter considering parasitic parameters is proposed, in which a film capacitor with small capacitance value replaces the electrolytic capacitor to improve the lifetime of the inverter. Further, the operating mode of the transformer and the decoupling capability is analyzed, and obtains the reasons affecting the inverter steady-state performance. Finally, the simulation and experiment validation of the proposed microinverter have been accomplished. Base on the analysis method proposed in this paper, a more accurate device selection can be provided for industrial design.

Photovoltaic Maximum Power Point Tracking Technology Based on Power Prediction Algorithm Combined with Variable Step Length Disturbance Observation Method

Under partial shading conditions, the system operating sequence of photovoltaic cells does not fall on a single characteristic curve, and the traditional maximum power point tracking (MPPT) control algorithm is prone to causing the system output power to oscillate around the maximum power point. In the case of multiple peaks, the traditional MPPT algorithm is prone to being trapped in a local optimum solution. This paper proposes an MPPT control algorithm based on the WOA-RF prediction algorithm combined with a variable step disturbance observation method. By establishing a photovoltaic system simulation model, the improved algorithm is verified through simulation. The improved MPPT control algorithm can adaptively adjust the step size under different conditions to ensure that the system can quickly and accurately track the maximum power point. At the same time, by optimizing the algorithm logic and parameter settings, it can effectively avoid problems such as local optimum solutions and instability in the system, and improve the system convergence speed and tracking accuracy.

Photovoltaic Modules’ Cleaning Method Selection for the MENA Region

Photovoltaic (PV) systems are important components of the global shift towards sustainable energy resources, utilizing solar energy to generate electricity. However, the efficiency and performance of PV systems heavily rely on cleanliness, as dust accumulation can significantly obstruct their effectiveness over time. This study undertook a comprehensive literature review and carried out multiple interviews with experts in the PV systems field to propose a map for selecting the optimal PV cleaning method for PV systems within MENA region. These factors, covering meteorological conditions, the local environment, PV system design, module characteristics, dust deposition attributes, exposure time to dust, and socio-economic and environmental considerations, were employed as criteria in a Multi-Criteria Decision-Making (MCDM) model, specifically, an Analytic Network Process (ANP). The results indicate that partially automated cleaning is the most suitable method for existing utility-scale PV projects in the MENA region. The findings provide robust guidelines for PV system stakeholders, aiding informed decision-making and enhancing the sustainability of PV cleaning processes.

A non-isolated converter of switching current stress in DC-DC converter for integrating PV and battery storage system

ABSTRACT High-gain DC-DC converters have seen significant adoption in renewable energy systems like Photovoltaic (PV), Fuel Cells (FC), and other systems. However, their effectiveness is increasingly tied to the availability of renewable resources. As Renewable Energy Sources (RES) typically generate electricity at low voltage levels, integrating high-gain DC-DC converters with RES is crucial for optimal performance. This paper introduces an innovative DC-DC converter design that achieves high gain and is specifically able to integrate smoothly with RES like PV systems and battery storage. The innovation of the proposed converter lies in its integration of conventional boost and buck-boost converters, enabling a high voltage gain while minimizing output voltage ripple and reducing switch current stress. Additionally, its unidirectional power transfer port allows efficient energy flow from solar PV or battery sources to the load, making it highly adaptable for managing fluctuating energy sources, a feature that distinguishes it from current modern converters. Its design simplifies architecture by combining traditional converter types, reducing the number of components, which leads to cost savings, lower weight, and improved reliability. Additionally, the design minimizes output voltage ripple and reduces switching current stress, enhancing the converter’s durability under variable operating conditions. The converter’s performance is evaluated through simulation and experimental studies, demonstrating a 96.3% efficiency and 5.5 times of voltage gain. The converter’s feasibility and effectiveness are validated under dynamic scenarios with varying solar irradiation, making it an ideal solution for clean energy generation systems, including hybrid energy generation setups. The proposed converter topology offers an auspicious solution for high-gain DC-DC conversion in renewable energy systems.

A FINANCIAL EVALUATION OF WHEAT PRODUCTION PROJECTS UNDER CENTER PIVOT IRRIGATION SYSTEMS IN ANBAR GOVERNORATE

The research aims to identify the financial feasibility of cultivating the wheat crop under modern irrigation systems in desert areas and to clarify the impact of the capacity of the systems in those projects in achieving the financial feasibility of their establishment, using the economic evaluation criteria for the projects. The research included a study of 60 projects in Anbar Governorate for the 2020-2021 production season. It has been shown that projects that use several systems, despite their high investment costs, can recover the money invested in them within a relatively short period. The projects that use modern irrigation systems covering 60 donums were among the best projects that achieved technical efficiency in the productivity of the wheat crop, and the average net income reached the cash in the sample is about 1.3 billion dinars, while the average net income per donum in the research sample is about 189 thousand dinars. The sample was not able to achieve accounting profits, The research recommended the need to use electric power systems as an alternative to relying on electric power generators, as the average price of solar power systems in the Iraqi market is currently within reach.

Distributed Photovoltaic Communication Anomaly Detection Based on Spatiotemporal Feature Collaborative Modeling

As distributed photovoltaic (PV) technology rapidly develops and is widely applied, the methods of cyberattacks are continuously evolving, posing increasingly severe threats to the communication networks of distributed PV systems. Recent studies have shown that the Transformer model, which effectively integrates global information and handles long-distance dependencies, has garnered significant attention. Based on this, our research proposes a model named STformer, which is applied to the task of attack detection in distributed PV communication. Specifically, we propose a temporal attention mechanism and a variable attention mechanism. The temporal attention mechanism focuses on capturing subtle changes and trends in data sequences over time, ensuring a highly sensitive recognition of patterns inherent in time-series data. In contrast, the variable attention mechanism analyzes the intrinsic relationships and interactions between different variables, uncovering critical correlations that may indicate abnormal behavior or potential attacks. Additionally, we incorporate the Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction technique. This technique not only helps reduce computational complexity but, in certain cases, can enhance anomaly detection performance. Finally, compared to classical and advanced methods, STformer demonstrates satisfactory performance in simulation experiments.

Comparative LCA of thermal power plant with CCS and solar PV system: sustainability assessment in Indian context.

The study's objective is to evaluate and compare the sustainability of power production techniques for India's transition to clean power generation. It specifically focuses on coal-based power generation with emission control technologies, flue gas desulfurization (FGD) with carbon capture and storage (CCS), and compares it with solar photovoltaic (PV) systems. The study conducted a life cycle assessment (LCA) to determine the environmental impact of electricity generation in each scenario. Inventory data has been collected for each case through plant visits, emission modelling, and literature searches. The study evaluated midpoint and endpoint impact indicators utilizing the ReCiPe (H) assessment methodology. The economic viability of all the cases was determined by calculating the levelized cost of electricity (LCOE). The results showed that retrofitting an existing power plant with flue gas desulfurization (FGD) and carbon capture and storage (CCS) reduced efficiency by 30%, required 1.2 times more auxiliary power, and increased heat rates. The LCA results showed that the global warming potential (GwP) for FGD and CCS together was 0.614 kg CO2 eq. per kWh of power generation. On the other hand, the GwP for the solar PV system was much lower, at 0.043 kg CO2 eq. per kWh. There were trade-offs in both cases, but solar PV plants are more environmentally friendly than thermal power plants equipped with CCS systems in almost all categories. Furthermore, the LCOE results showed Rs 3.87 per kWh for an on-grid solar PV plant and Rs 5.33 for thermal power, with CCS and FGD showing solar as an economically more feasible option. Retrofitting thermal power facilities with emission control technology is necessary to achieve net zero emissions, but transition torenewable energy sources isinevitable.

New Approach for Tracking, Monitoring, and Diagnosing Faults in a Photovoltaic System in Real Time: An Experimental and Case Study

Photovoltaic installations have emerged as a cornerstone of sustainable energy production, playing a pivotal role in the global transition towards renewable sources of electricity. As the demand for clean energy surges, so too does the need for robust monitoring and diagnostic strategies to ensure the efficient operation of these systems. This study presents a novel methodology for the real-time tracking, monitoring, and diagnosing of faults in photovoltaic systems (PVSs), emphasizing their crucial role in sustainable energy production amid the global shift to renewable energy. The study was conducted in Guelma, Algeria, during the spring and summer seasons. The investigation utilized WatchPower simulation software over a 24-hour performance analysis of the photovoltaic system. On June 19, 2024, with a high temperature of 32°C, the system achieved a peak output power of 600W under optimal conditions, validating its efficiency in energy generation. The study also analyzed the effects of shading on energy output by comparing data from a shaded day on May 14, 2024, at 25°C, to an unshaded day on June 21, 2024, at 32°C, during peak sunlight hours from 9:00 AM to 2:15 PM, the period when sunlight is at its strongest. The results showed a significant drop in output power from 600W to 450W due to shading, underscoring the importance of real-time monitoring to detect performance inefficiencies. This research not only enhances operational reliability and maintenance strategies for PV systems but also demonstrates the effectiveness of integrating real-time data analytics to support decision-making in similar environments.

Transformerless High Voltage Gain Y-Source DC–DC Converter with Switched Capacitor for Grid-Connected Photovoltaic Applications

A high voltage gain DC–DC converter with a Y-source network is proposed in this paper for applications such as fuel cells and PV systems. The proposed converter topology is a combination of a Y-source module with a switched capacitor boost module. It is a single switch topology to produce high voltage gain at the load. The superiority of the proposed topology is the high voltage transfer ratio and continuous input current. The voltage gain of the converter can be achieved up to twenty times the input voltage at a duty cycle of 25% itself. The steady state analysis of the converter is carried out using mathematical equations and the working of the converter is explained. The design and analysis of the passive components in the circuit are explained. To illustrate the highlights of the converter, the proposed topology is compared with similar converters in the literature. The simulation of the converter is carried out using MATLAB/SIMULINK. The circuit is verified in the laboratory using a 100[Formula: see text]W prototype.

Water-surface photovoltaic systems have affected water physical and chemical properties and biodiversity

The implementation of water-surface photovoltaic systems as a source of renewable power has expanded rapidly worldwide in recent decades. Water-surface photovoltaic avoids negative impacts on terrestrial ecosystems, while the impacts on aquatic physical and chemical properties and biodiversity are unclear. To understand the ecological and environmental impacts of water-surface photovoltaic systems, here we conducted a field survey on water physical and chemical properties, plankton and bird communities of 26 water-surface photovoltaic systems in the Yangtze River basin in China during the winter and summer of 2022. We found that water-surface photovoltaic systems decreased water temperature, dissolved oxygen saturation and uncovered area of the water surface, which caused a reduction in plankton species and individual density, altering the community composition. Water-surface photovoltaic systems also caused an overall decrease in bird diversity and changed bird community compositions. These findings suggested that water-surface photovoltaic systems have impacts on the water environment and ecology. Since water-surface photovoltaic systems will continue to expand in the future, our results emphasize that rational planning is critical for the sustainable development of water-surface photovoltaic systems and the protection of the aquatic environment and biodiversity.

Design, modeling and cost analysis of 8.79 MW solar photovoltaic power plant at National University of Sciences and Technology (NUST), Islamabad, Pakistan

Climate change, as a critical global concern, has fueled our efforts to address it through different strategies. In response to the critical worldwide issue of climate change, we suggested a Photovoltaic (PV) system at the National University of Sciences and Technology (NUST) in Islamabad, Pakistan (latitude: 33.724530 N, longitude: 73.046869, terrain elevation: 552 m). Islamabad is located in a region blessed with enormous solar resources, boasting a daily horizontal solar irradiance of 1503.45 kWh/m2 and an average daily solar irradiance of 5.89 kWh/m2, with an exceptional solar fraction of 98.99%. The ambient air temperature, averaging 23.21 °C, reaches its maximum in June and its minimum in December. Our research thoroughly evaluates the system’s performance, accounting for various losses and utilizing modern PVsyst software. Over the course of 18 years, our PV system is expected to save 75,478.60 tons of CO2, the equivalent of planting 348,754 teak trees. Furthermore, the cost of energy generation is an affordable 0.0141 US $/kWh, much lower than traditional rates, including the Sherif cost of 0.028$/kWh. Along with the performance research, we conducted a detailed cost analysis, projecting the starting cost and cash flow, and discovered that the plant would be in surplus within 12 years of installation. Our system is positioned to generate 11,270,771 kWh/year with a respectable performance ratio (PR) of 76.2% and a Capacity Utilization Factor (CUF) of 16%. Our findings not only highlight the potential of renewable energy but also provide important insights for future sustainable energy programs.

Optimization of coupling phase-change materials and thermal screens in façade-integrated hybrid photovoltaic collectors for optimal energy production and thermal comfort in buildings

The operation of building-integrated photovoltaic (BIPV) systems gives rise to a significant proportion of the solar radiation absorbed by the cells being unable to be converted into electricity. This phenomenon consequently increases the temperature. This temperature increase impacts the cells' electrical efficiency, leading to a reduction in their performance and accelerating their degradation. The combination of phase-change materials with insulating fluid blades, situated behind photovoltaic cells, represents a passive cooling solution that optimizes the performance of hybrid photovoltaic systems when incorporated into facades. The present study assesses a system that incorporates paraffin as a PCM and an argon layer in a PV-PCM-argon layer physical model (PVT/ArPCM), in comparison with a PV-PCM system (PVT/PCM), to enhance the thermoelectric performance of photovoltaic systems mounted on façades while ensuring optimal thermal comfort within buildings. The discrete heat transfer equations were solved using the Thomas algorithm and the iterative Gauss-Seidel method in conjunction with the implicit finite difference method. The findings illustrate that the electrical efficiency experienced only a slight increase, estimated at 0.01%, while there was a notable enhancement in the indoor thermal comfort experienced by occupants, with a 65% improvement observed due to the incorporation of an argon-filled thermal screen. The incorporation of an argon layer led to a minor reduction in temperature of 0.01°C in the photovoltaic cells, resulting in a minimal improvement of 0.014% in electrical power production. The phase-changing material incorporated into PVT/ArPCM demonstrated superior thermal management capabilities in comparison to the same material employed in PVT/PCM.

Clean energy transition in rural Bangladesh: Challenges in adoption and impact

ABSTRACT At the household level, the solar photovoltaic (PV) system is an off-grid clean energy source with significant poverty reduction potential, thereby contributing to the attainment of several sustainable development goals. Nevertheless, there has been limited adoption of renewable or clean energy technologies in Bangladesh. At present, renewable energy sources account for only 3% of the country’s electricity generation. This study thus investigates the drivers of solar PV adoption and the impact of this on household income and poverty in Bangladesh. We present an econometric analysis of data from the International Food Policy Research Institute’s Bangladesh Integrated Household Survey, 2020. Our findings indicate that only 5.51% of the sample households adopted solar PV, with the likelihood of adoption 3.8% higher in households with a mobile phone, 1.7% higher in households with internet access, and 2.8% higher among homeowners. However, the government’s programs to expand the electricity grid made the delivery of solar PV by partner organizations less competitive. Our analysis reveals that the adoption of solar PV has a positive effect on household income of between 9.31% and 13.50%. The poverty gap is likely to decrease by around 20% to 26% due to adoption. These findings are pertinent to ongoing policy development efforts targeted at increasing the adoption of renewable energy to meet the sustainable development goals. Solar PV information could be potentially disseminated through mass media and modern communication technologies that require internet access. Furthermore, increasing the installation of solar PV systems in rented houses may promote the adoption of solar PV. It is imperative to implement policies that provide incentives for the installation and utilization of solar PV.

Design of reliable standalone utility-scale pumped hydroelectric storage powered by PV/Wind hybrid renewable system

With a target of 35 % renewable energy in the country’s energy mix by 2030, the goal of this research is to support the Libyan government’s plan to maximize the use of environmentally friendly and sustainable energy sources. This will be accomplished by making effective use of the region’s plentiful natural resources. The feasibility of wind and solar energy has been established by local research, and the presence of highlands that can store pumped hydropower (PHS) makes hybrid renewable energy systems (HRES) even more feasible. These systems might offer a sizable edge over competitors in the regional energy market. In this study, PHS was utilized to stabilize electricity production in addition to storing energy. A hydropower turbine provides electricity to the load, and the PHS system is powered by a PV/wind supply. By lowering the volatility of wind and photovoltaic power generation, the suggested system could offer a more dependable renewable energy source without requiring complicated control mechanisms. This strategy could encourage a wider adoption of renewable energy, which could be especially advantageous for developing nations. Under particular load and climate conditions, the energy production of different solar PV array and wind turbine farm configurations was estimated using the System Advisor Model (SAM) software. The ideal HRES configuration consists of a 290 MW wind farm, a 154 MW solar PV field, and a 508 MW PHS system. This configuration will provide 100 % of the annual electrical demand of 513 GWh, plus a 20 % safety margin. The levelized cost of energy (LCOE), estimated at $211.65/MWh, is reduced by this configuration. It is anticipated that the $929.02 million initial investment will be recovered in 11 years, and the system will turn a profit in the following 9 years. Also, the planned HRES will stop 532.17 tons of CO2 emissions from being released each year.

A Maximum Power Point Tracking (MPPT) Strategy Based on Harris Hawk Optimization (HHO) Algorithm

To address the multi-peak characteristics of the P-U output characteristic curve when the photovoltaic array is partially shaded, a Maximum Power Point Tracking (MPPT) method combining Harris Hawk optimization, and a variable step conductance increment method is proposed in this article. Although the Harris Hawk Optimization algorithm has advantages in optimizing multi-modal P-U curves, when the lighting conditions suddenly change, the output characteristic curve will undergo drastic changes, causing the algorithm to oscillate repeatedly at the maximum power point. Moreover, due to its inherent limitations, the Harris Hawk algorithm has a low convergence accuracy, slow tracking speed, and is prone to getting trapped in a local optimum. In order to compensate for the shortcomings of the Harris Hawk Optimization algorithm, the variable step conductance increment method is switched for local exploration to improve the algorithm’s ability to escape from the local optimal solution and reduce power oscillation. Finally, the MPPT control of the proposed strategy was simulated and verified on the MATLAB/Simulink simulation (2021) platform. In the MPPT test experiment, the proposed composite algorithm was applied to simulate and verify uneven irradiance conditions.

Design of photovoltaic and battery energy storage systems through load demand characterization: A case study in Thailand

The integration of photovoltaic (PV) system at behind the meter has gained popularity due to the growing trend toward environmentally friendly energy solutions. Coupling PV systems with battery energy storage systems (BESS) addresses the uncertainties of PV energy production while enhancing energy management. Load characteristics have influence on PV and BESS design both in technical and economic aspects. This paper presents a comprehensive analysis of load demand characterization methodologies tailored for the design of PV and BESS. The fundamental load properties such as daily maximum power, minimum power, and load energy, categorizing loads based on their daily and annual variation degrees are investigated. The techno-economic performance of PV-only and PV+BESS systems is analyzed, focusing on metrics such as excess energy, peak limiting performance, and economic feasibility using the levelized cost of energy (LCOE). The findings of this study reveal three distinct load characteristics based on daily variation: moderate (50–70 %), moderate to high (70–80 %), and high (80–90 %). Load profiles with moderate variation (50–70 %) demonstrate economic feasibility when sized with a PV-only system matching maximum power demand. With BESS prices reduced to less than 140 USD/kWh, these loads could also integrate a 1C-BESS sized at half capacity under the same control strategy, resulting in lower excess energy and LCOE. Conversely, loads with higher variation (>70 %) and lower self-consumption rates (<70 %) face fewer viable options for both PV-only and PV+BESS configurations, especially if BESS costs remain high. These loads require custom-designed solutions and more extensive load analysis. Through analysis, this study establishes the relationship between load characteristics and system design suitability for the loads studied. The findings underscore the importance of incorporating load demand characterization techniques in the design systems, highlighting the need for tailored approaches based on specific load characteristics and economic viability.

Exploring rooftop solar potential through deep learning: a comparative case study of U-Net and Attention U-Net

Photovoltaic systems are increasingly gaining popularity for rooftop installations in urban areas. These devices contribute to the self-sufficiency of electricity supply and reduce greenhouse gas emissions in urban settings. In this study, we implement deep learning techniques and compare the U-Net and Attention U-Net architectures to detect rooftops in the city of Sidi Bel Abbes (North Africa) for the installation of solar panels. Contrary to trends observed in the literature and previous research, our results show that U-Net achieved a higher accuracy of 90.49%, while Attention U-Net achieved an accuracy of 89.96%. Using the U-Net method, we identified a 1.9-square-kilometer area of rooftops suitable for solar panel installation in the southern part of the town of Sidi Bel Abbes. This discovery represents a potential electrical capacity of 89 MVA, capable of largely satisfying the energy needs of the studied region. This work is a novelty, being the first study of its kind undertaken in Algeria.

An optimized controller for novel asymmetrical 51-level inverter in hybrid solar and wind turbine-connected power system

An optimized controller for novel asymmetrical 51-level inverter in hybrid solar and wind turbine-connected power system

Experimental investigation on the electrical and hydrogen-production performance of a novel PEM electrolyzer driven by CdTe PV with a tracking system

Addressing the challenges of intermittent and variable energy supply, solar hydrogen production via electrolysis has garnered significant attention due to its unique advantages, emerging as a hot topic in the scientific research domain. However, the application of this technology is currently mainly related to the non-tracking system, which undergoes a rapid change in solar irradiation during the day. To expand the matching relationship of solar irradiation, PV characteristics, and electrolyzer, this paper proposes the development of a Proton Exchange Membrane (PEM) electrolyzer driven by Cadmium Telluride (CdTe) photovoltaic (PV) modules with a tracking system for hydrogen production. An experimental platform was set up in Chengdu and the performance tests were carried out for different operating modes during summer. The experimental results demonstrate that the average electrical and hydrogen production efficiencies of the system are 13.11% and 7.88%, respectively, on a sunny day, with a total of 566.7 L of hydrogen produced within 7 h of operation. Furthermore, the solar irradiation received by the tracking surface of the system is significantly enhanced by 10.29% in comparison to the horizontal surface. On a cloudy day with an electrolyzer inlet water temperature of 45 °C, the system has the potential to achieve a hydrogen production efficiency of 11.15 %. At a constant current density of 1.0 A/cm2, the efficiency of the electrolysis process increased by 2.07% and 1.25% for each 10 °C increase in the temperature of the electrolyzer, having an inlet temperature of 35 °C. This study offers a novel approach for a PV-PEM system with a higher hydrogen production efficiency while also establishing a robust foundation for technology optimization and broader implementation.

State-of-Art Techniques for Photovoltaic (PV) Power Systems and their Impacts

State-of-Art Techniques for Photovoltaic (PV) Power Systems and their Impacts