Photovoltaic System Research Articles

A comparison between the ocean and offshore photovoltaic production system into microgrids: benefits and limits

The current work offers a detailed comparison of the advantages and disadvantages of microgrids concerning the developments of photovoltaic (PV) production installed near the shore and those installed offshore. As demand for renewable energy increases, integrating offshore and marine photovoltaic systems offers a promising approach to increase energy production while minimizing land use. This study explores the inherent advantages of offshore photovoltaic systems, including higher energy production due to the cooling effect of water, reduced reliance on land, and the ability to tap into sustained marine solar resources. On the other hand, this paper also addresses challenges associated with these systems, such as: B. Increased installation complexity, vulnerability to harsh ocean conditions, and potential impacts on marine ecosystems. The results in this paper show good performance for both offshore and floating PV systems, except that the offshore PV system excels over the other system by 3.13% in energy production. Moreover, the difference in the annual efficiency of the two PV systems reached 0.55%. These values are considered low because both systems are installed in water, given that both systems benefit from lower temperature and solar irradiation values. Nevertheless, these two systems equally present their own unique challenges including, but not limited to, operational and maintenance cost increase, effect on marine ecology and the technical hindrances on installation and grid interconnectivity. The aim of this review is to disentangle the achievements made regarding the current state of the art in floating photovoltaic technologies. When dealing with performance metrics, two solutions are examined in order to demonstrate the feasibility of providing the energy needs in an ecological way.

Using hybrid firebug swarm optimization and jellyfish search to enhance DC-DC converter efficiency in solar PV systems

Using hybrid firebug swarm optimization and jellyfish search to enhance DC-DC converter efficiency in solar PV systems

The Current Situation and Development Trends of the Solar Photovoltaic Industry in China and the United States

Climate change and environmental pollution have made clean energy increasingly valued, among which solar photovoltaic power generation occupies a pivotal position. In terms of the development of clean energy in the world today, major countries have mastered the core technology and occupied the main installed power generation capacity. China and the United States, the two major energy powers in the world, are also the major powers in the world today. They have completely different political systems and economic policies, and there are also many differences in the development of the solar photovoltaic power generation industry. This paper will conduct an in-depth comparative analysis of the development of the solar photovoltaic industry in China and the United States from the aspects of policy environment, key enterprises, development trends, etc., to more clearly reveal the differences and causes of the development of the solar photovoltaic industry between the two countries, and provide references for future cooperation and competition.

An intervention framework for the adoption of solar home system technology in rural Vhembe district, South Africa

BackgroundSolar photovoltaic technology is one of the promising renewable energy solutions of the twenty-first century. It successfully provides electricity to industries, homes and even the transport sector. The decreasing prices of solar modules from 2010 have made Solar Home Systems Technology (SHST) increasingly attractive compared to other renewable energy technologies. Paradoxically, in rural communities of South Africa the usage of SHS remains low. Households continue to rely on unclean energy sources such as firewood for cooking and water heating. Previous efforts to electrify rural communities with SHS have failed considerably. Thus, a comprehensive study was conducted in the Vhembe District, encompassing three villages, to explore this issue and develop a contextualised solution using a behavioural change model. A 35-item questionnaire was randomly administered to 310 households to understand the factors that contribute to the low adoption rate of SHS technology. The data gathered were analysed using IBM SPSS Statistics and Amos version 28. Confirmatory factor analysis and hypothesis testing were employed as the principal statistical methods.ResultsA 12-item model with five distinct factors consolidated into a single measurement model was revealed. All standardised factor loadings exceeded 0.7. Composite reliability values (CR) were above 0.8 and higher than MaxR(H) values, indicating the model’s reliability. Among the five factors influencing SHS adoption (perceived behavioural control, attitude, intention, trust, and subjective norms), only trust and attitude significantly impacted the intention to adopt SHS in the district (P < 0.05). Based on these findings, the conceptualised structural model reflected SHS adoption as determined by the integration of the technology’s social, technical and policy factors. Because of this, this should be regarded as a true reflection of the practical and behavioural intentions of local communities. Moreover, in this paper the barriers hindering SHS adoption are explained, emphasising the significance of attitude and trust. Highlights of policy imperatives are included together with a proposal for a contextual framework, and the way of promoting sustainable solutions. Emphasis is placed on the importance of scaling up renewable energy access.ConclusionsThis research provides a compelling academic exploration of the barriers to the adoption of SHS, the influential role of attitudes and trust, policy considerations, a contextual framework, and the need for promoting sustainable solutions and expanding access to renewable energy. The South African government should lead a change in how solar PV is deployed, considering its social impact, associated technical skills and policy support.

Thermo-energetic performance of two dwellings during a heat wave in the Buenos Aires province, Argentina: On-site response assessment and adaptation strategies testing

This study evaluates the effects of heat waves on habitability conditions, energy consumption and cooling expenses through on-site measurements in two houses in Buenos Aires Province: an urban house located in La Plata, with low thermal quality of the envelope and two air conditioners; and a rural one in Brandsen, with an intermediate thermal quality of the envelope and one fan. Energy strategies were simulated on both houses that, simultaneously, allow the adaptation to heat waves and reduce, or generate the least possible, impact on electricity grids: a photovoltaic (PV) system and a ground source heat pump (GSHP) system. Both locations experienced similar average outdoor temperatures (∼28°C), but La Plata had fewer fluctuations due to heat accumulation in built surroundings. Indoor temperatures were comparable (∼29°C living spaces/∼27°C bedrooms), but the house in La Plata experienced lower thermal fluctuations due to its air-conditioning (ACs) and outdoor temperatures. Average heat index values were alike (∼30°C living spaces/∼29°C bedrooms). Although La Plata’s dwelling had ACs, results show the influence of envelope performance and nighttime ventilation in the Brandsen’s rural setting. Adaptation assessment revealed that PV and GSHP systems are adequate measures to face heat waves; however, they require important incentives to achieve massiveness.

AgriPV system with climate, water and light spectrum control for safe, healthier and improved crop production

The PV4Plants project aims to optimise the synergy between agriculture and photovoltaic (agriPV) systems to improve crop yield, land use efficiency, and renewable energy generation. Using cutting-edge nanoparticles coated between PV panels to optimise light transmission, the system tailors conditions for specific crops and climatic regions. Demonstrations in Türkiye, Spain, and Denmark test the adaptability and effectiveness of these systems, to evaluate improvements in crop health and renewable energy output. Central to the project are efforts to increase recyclability and promote farmer engagement through innovative financing models and policy recommendations.

(RPh3P)[Mn(dca)3]: A Family of Glass-Forming Hybrid Organic-Inorganic Materials.

ABX3-type hybrid organic-inorganic structures have recently emerged as a new class of meltable materials. Here, by the use of phenylphosphonium derivatives as A cation, we study liquid- and glass-forming behavior of a new family of hybrid structures, (RPh3P)[Mn(dca)3] (R = Me, Et, Ph; dca = dicyanamide). These new compounds melt at 196-237 °C (Tm) and then vitrify upon cooling to room temperature, forming glasses. In situ glass formation of this new family of materials was probed on a large scale using a variable-temperature PXRD experiment. Structure analyses of the crystalline and the glasses were carried out by solid-state nuclear magnetic resonance spectroscopy and synchrotron X-ray total scattering techniques for using the pair distribution function. The mechanical properties of the glasses produced were evaluated showing promising durability. Thermal and electrical conductivities showed low thermal conductivities (κ ∼ 0.07-0.09 W m-1 K-1) and moderate electrical conductivities (σ ∼ 10-4-10-6 S m-1) at room temperature, suggesting that by the precise control of the A cation, we can tune meltable hybrid structures from moderate conductors to efficient thermal insulators. Our results raise attention on the practical use of this new hybrid material in applications including, e.g., photovoltaic devices to prevent light-deposited heat (owing to low κRT), energy harvesting thermoelectric, etc., and advance the structure-property understanding.

Solar Energy in Buildings: Feasibility Analysis of Integrated and Conventional Photovoltaic Panels

The feasibility study is crucial for decision-making in the investment stage of photovoltaic systems projects. A cost–benefit analysis for a project should not be evaluated solely in terms of money in-flows and outflows; it is important to consider other characteristics such as climate, solar irradiation, and the hours of sunshine in different spaces, as well as the electricity rates of the electricity supply company. Therefore, analyzing and simulating the performance conditions, both technical and economic, of photovoltaic systems is key. The objective of this study was to analyze the investment models in two types of photovoltaic systems: one integrated into the construction and the other conventional in a building in the Mexican Republic, considering ideal conditions, thus evaluating the energy efficiency in cities, as they consume around two-thirds of the world’s energy and are responsible for 70% of global greenhouse gas emissions. The methodological proposal was to select a location, determine the predominant type of climate and collect data on solar radiation, the electricity supplier rates, the profitability for a cost–benefit analysis, and the inflation rates to determine the viability of a project that comprehensively covers the variables for decision-making.

Comprehensive benefit optimization method for photovoltaic inverters participating in distribution network loss reduction by reactive compensation

When a large number of distributed photovoltaic (PV) systems are integrated into the distribution network, power flow becomes bidirectionally fluctuating, resulting in variable line losses. In the scenario of reverse flow, the increase in line loss is particularly significant. The bidirectional reactive power regulation of photovoltaic inverters is an effective approach to reduce losses in the distribution network. However, despite the benefits of reducing losses, reactive power regulation by photovoltaic inverters also incurs additional costs. Therefore, there is a need for research into a comprehensive benefit optimization method for inverters participation in reducing reactive power losses in distribution networks. Firstly, the cost quantification models for the investment, transformation, operation, and lifespan loss of the photovoltaic inverters involved in reactive power loss reduction are established. Secondly, the benefit quantification models for loss reduction and power factor improvement are developed. Thirdly, considering various operational scenarios of both photovoltaic systems and loads, a comprehensive benefit optimization method for photovoltaic inverters participating in reactive power loss reduction in distribution networks is proposed. Finally, through example analysis, the cost and benefit are calculated and fitted in different scenarios, and the optimization calculation is carried out. Compared to the scenario where the photovoltaic inverter operates at the maximum reactive power regulation capacity, the optimized comprehensive benefit is increased by 21.20%. The proposed method is validated to effectively enhance the comprehensive benefits of inverters participation in reactive power loss reduction.

Monarch butterfly optimization based energy management system for electric vehicle with interleaved landsman converter

The toxic emissions from combustion engine cars and businesses using fossil fuels have steadily increased over time in today's world of expanding needs and urbanization. Due to some advantages over vehicles with traditional engines, using electric vehicles is the most well-liked and successful alternative. The performance of electric cars is significantly influenced by an energy management system (EMS). In this study, a multifunctional power electronic interface capable of using two sources simultaneously throughout the charging process monarch butterfly optimization (MBO) based EMS for plug-in electric vehicles (PHEV) has been developed. The battery can be charged from the grid or solar photovoltaic (SPV), depending on the need. This study designs an electric vehicle (EV) charging system that uses an interleaved landsman converter followed by a flyback converter. As a result, the suggested converter helps in improving battery safety as well as user safety for the vehicle. The proposed control technique is simulated using system models created with MATLAB/Simulink. The outcomes of the simulation demonstrate that the devised technique offers better control in terms of vehicle stability. A number of simulations are run to evaluate the efficiency and performance of the proposed approach.

Trivalent Rare Earth Ion‐Doped Metal Halide Perovskite Near‐Infrared Semiconductors for High‐Performance Optoelectronic Devices

AbstractGiven the extensive application of near‐infrared (NIR) emission, the quest for efficient and versatile NIR semiconductors have attracted tremendous attention. Leveraging trivalent rare earth (RE3+) ions doping, the integration of metal halide perovskites with RE3+ ions makes it easy to achieve NIR‐II emission (1000–1700 nm). However, although showing promise in bioimaging, optical communication, and night vision, enhancing NIR‐II emission intensity to promote further progress in real‐world applications remains a challenge. This review summarizes the recent advancements in RE3+ ion‐doped perovskite NIR semiconductors, and discusses what kind of properties are needed and how to achieve desired optical properties in various applications. The review starts with the synthesis methods for various material types with rich examples. Following this, the mechanisms of strategies for optimizing NIR luminescence performance are discussed in detail. Furthermore, the review highlights their multifunctional applications both as an electrically driven emitter in NIR light‐emitting diodes (LEDs) and as a down‐conversion emitter in photovoltaic devices (PVs) or phosphor‐converted LEDs (pc‐LEDs). Finally, insights on how to fill the gap between current research and future goals are provided. This review aims to provide a deeper understanding of RE3+ ion‐doped NIR light‐emitting perovskite materials, and to promote the exploration of efficient NIR emitters.

Deep learning‐based barrier‐function super‐twisting sliding mode control for integrating renewables in smart grid

AbstractThis study presents a two‐step controller design for integrating wind and photovoltaic energy systems into the smart grid. In the first stage, an enhanced deep neural network (DNN), optimised by particle swarm optimisation and a genetic algorithm, is employed to generate maximum power point (MPP) targets for both wind and solar systems. The DNN incorporates advanced features like hyperparameter tuning, softmax attention, dropout, and early stopping to improve prediction accuracy and prevent overfitting. In the second stage, a barrier‐function‐based adaptive super‐twisting sliding mode controller is developed to track the MPP and maintain stable DC bus voltage. This controller effectively reduces chattering and operates without requiring detailed knowledge of disturbance limits. The proposed design aims to maximise power extraction, ensure DC bus voltage stability, and enable smooth power delivery to the grid. MATLAB simulations and real‐time hardware testing validate the controller's performance, demonstrating significant improvements over traditional methods.

DFT investigation on thermoelectric, electronic, optoelectronic, elastic, and structural properties of sodium‐based halide double perovskites Rb2NaSbZ6 (Z = Cl, Br, and I)

AbstractSodium‐based halide double perovskites (HDPs) present a promising alternative to Pb‐based perovskites for safe solar and thermal energy conversion devices due to their high durability and non‐toxic elements. This study examines the electronic, thermoelectric, elastic, optoelectronic, and structural properties of Rb2NaSbZ6 (Z = I, Br, Cl) double perovskite compounds using density functional theory (DFT). These compounds, characterized by a cubic structure, show increasing structural parameters as halogens are substituted from chlorine to iodine. Structural stability is confirmed by evaluating the enthalpy of formation, Gibbs free energy, Born and Huang criteria, and tolerance factor. Pugh's ratio indicates the ductile nature of the compounds. All investigated halide compounds exhibit an indirect band gap ranging from 3.9 to 2.34 eV, with valence and conduction band extrema located at different symmetry points, and a higher effective mass of holes is noted. This study also analyzes the refractive index, optical loss, light absorption, and polarization across the energy range of 0–10 eV. The spectral characteristics indicate that these HDPs are suitable for optoelectronic and photovoltaic devices due to their absorption in the visible and near‐ultraviolet spectra. High figures of merit (0.45–0.6) derived from power factor and thermal conductivity calculations suggest the potential of these compositions as thermoelectric devices. These findings provide a comprehensive understanding of these materials, facilitating their further deployment.

Smart energy: application of the photovoltaic system using genetic algorithms for decision making in industry 4.0

The growing demand for sustainable solutions and the digitalization of industrial processes have driven the adoption of photovoltaic systems and advanced decision-making technologies. In the context of Industry 4.0, where automation and artificial intelligence are fundamental, these systems stand out as a clean energy alternative, promoting savings and reducing pollutant emissions. This study aims to develop a photovoltaic energy control model that uses genetic algorithms to optimize energy efficiency in industrial environments, reducing costs and dependence on non-renewable sources. The methodology included the computational modeling of a photovoltaic system and the application of genetic algorithms to optimize parameters such as panel angle and operating hours, adapting the system in real time to variable consumption and generation conditions. The results showed that the use of genetic algorithms increased the system's efficiency by up to 20% compared to traditional methods, as well as minimizing consumption from the electricity grid at peak times. This study reinforces the importance of artificial intelligence in optimizing renewable resources, contributing to energy efficiency and sustainability in Industry 4.0.

Modeling of PV System Supported Intelligent Irrigation System in Iraq-Mosul Region

In this study, Matlab/Simulink is used to create a smart irrigation system that uses electricity generated by photovoltaic cells. In order to supply 90000 liters of water every irrigation period to meet the daily needs of farm irrigation, the system is intended for a rural location of Mosul city in the west. According to calculations, the necessary amount of water can be drawn from a 50 m water head well using a solar cell array that provides a submersible BLDC pump with a power of 1400 W. Employing smart irrigation demonstrated that the system's efficiency was increased and that it was more affordable than a standard pumping system. It is advised that Iraq, one of the solar-richest nations, employ smart irrigation systems, even though it now lacks energy.

Firefly-optimized PI and PR controlled single-phase grid-linked solar PV system to mitigate the power quality and to improve the efficiency of the system

Firefly-optimized PI and PR controlled single-phase grid-linked solar PV system to mitigate the power quality and to improve the efficiency of the system

Cooling of Air in Outdoor Areas of Human Habitation

This paper deals with the issue of air cooling in outdoor areas of human habitation. An analysis of air parameters during the summer season was carried out to determine the thermal comfort zone for a part of the northern platform of the local station in Rzeszow (Poland). The cooling capacity required for thermal comfort was calculated using outdoor air parameters and heat gains in the vicinity of the research object. Ten potential air-cooling systems were proposed for the outdoor zones. The systems differed in terms of cooling equipment, primary energy source, cooling medium, and recipients. They were divided into three categories: compressor, adsorption, and evaporative cooling. The electricity yield of the existing photovoltaic installation at the research facility was evaluated to identify potential synergies between the cooling demand and solar energy. An analysis assessed the energy, economic, and environmental impact of each proposed option. The best option for cooling the outdoor areas was found to be an evaporative cooling system with a PV system. Solar radiation can be effectively used for cooling outdoor zones in Poland in the summer. The optimal solution for the research facility is an evaporative cooling system based on direct evaporation combined with a photovoltaic system. The subject matter covered can be used as an effective tool for the optimal selection of outdoor air-cooling systems to ensure the thermal comfort of the occupants.

Scientific production on environmental impacts in photovoltaic energy generation: a systematic review of publications from 2012 to 2022

This study aimed to the scientific production on the environmental impacts of photovoltaic energy from 2012 to 2022. It employed a qualitative and exploratory approach, utilizing bibliographic, systematic, and bibliometric research methods. The analysis focused on articles available in Capes journals that included the keywords "photovoltaic" and "environmental impacts" in their content, as well as those with full-text availability on the platform. A total of 22 articles were individually evaluated, and information was cross-referenced between them. Manual analysis of the full texts revealed that while environmental impacts were not the central theme of the research, they were present in other areas, particularly in analyses of financial viability or studies on the efficiency of photovoltaic systems. This study contributed to the understanding of the main central themes researched in relation to photovoltaic energy and how the environmental impacts caused by it are addressed in studies on solar energy, but mainly it identified the need for studies that centrally address these impacts.

Implementation of a Realistic Multicell CFD Model to Investigate the Thermal Characteristics Within a Solar PV Module

Implementation of a Realistic Multicell CFD Model to Investigate the Thermal Characteristics Within a Solar PV Module

LSTM-Based MPPT Algorithm for Efficient Energy Harvesting of a Solar PV System Under Different Operating Conditions

Solar energy is one of the most favorable renewable energy sources and has undergone significant development in the past few years. This paper investigates a novel concept of harvesting the maximum power of a photovoltaic (PV) system using a long-short term memory (LSTM) to forecast the irradiance value and a feedforward neural network (FNN) to predict the maximum power point (MPP) voltage. This study paves a way to mitigate avoidable inefficiencies that hinder the optimal performance of a PV system, due to the intermittent nature of solar energy. MATLAB/Simulink software platform was used to validate the proposed algorithm with real irradiance data from different geographical and weather conditions. Furthermore, the maximum power point tracking (MPPT) algorithm was implemented in a laboratory setup. The simulation results portray the superiority of the proposed method in terms of tracking performance and dynamic response through a comprehensive case study conducted with five other state-of-the-art MPPT methods selected from conventional, AI based, and bio-inspired MPPT categories. In addition to that, faster response time and lesser oscillations around the MPP were observed, even during volatile weather conditions and partial shading.