Photovoltaic System Research Articles

Rural development through solar and pyrolysis systems: Towards energy sustainability

Rural communities require socio-economic development and technologies that lead to the deployment of renewable energy systems. For these reasons, a solar parabolic dish cooker (SPDC), solar PV and fast pyrolysis systems were developed. The fast pyrolysis system is designed to generate biogas and biochar using an average biomass consumption and the generated waste per person per day in rural areas at a feed rate of 0.65 kg. 0.157 kg of biogas (CH4, H2 and CO) was recovered at the given feed rate and 73 % of the produced biogas is expected to be handed over to the feed provider since 27 % was burnt in the pyrolyser furnace. The SPDC utilised both aluminium and silver as the reflector materials and higher efficiency (4.182 %) was achieved using a silver dish reflector. Solar PV cooling from 82 °C to 25 °C was investigated and the findings revealed that 439.12 L of H2O and 0.164 kW are required at an operating cost of $0.571. An efficiency of 45.46–75.41 % for the pyrolysis unit, 60 % for the SPDC and 17 % for the solar PV were recorded. This study also recommends the installation of one pyrolysis system in each rural community and equip each rural household with the developed solar systems.

Estimating electrical distribution network length and capital investment needs from real-world topologies and land cover data

Green technologies such as solar photovoltaic systems and electric vehicles play a fundamental role in the global decarbonization effort. To enable their diffusion, electricity distribution networks need to be upgraded, which is a complex and expensive endeavor. However, utilities face budgetary constraints and seek to reduce planning uncertainty. Here, we utilize 7,527 real-world grid topologies and land cover data to develop a model for estimating conductor and capital investment needs for electrifying a specific area. Our work yields three main contributions: First, we demonstrate the important role of land cover data in power line planning. We show that, for medium and large networks, distinct methodologies are needed due to the significant impact of land cover, particularly buildings and roads. Second, we introduce a parsimonious model of power line length and identify the number of consumption points as the primary determinant of network investment costs. Third, we present a cost assessment model tailored for regulators and investors, offering valuable insights for network planning, policymaking, due diligence, and research. Our work highlights the importance of combining land cover data and operations research algorithms in distribution network planning and provides policymakers with a tool to ensure cost-efficient network expansion.

Analyzing the effects of shading on power output in curved photovoltaic array on airship

This study investigates the use of photovoltaic (PV) arrays on airships, focusing on challenges due to the curved structure that affects solar radiation distribution. A novel Photo-Thermal-Electric Model (PTEM), developed in MATLAB/Simulink, is introduced to simulate PV array behavior under various conditions, including the impact of solar altitude, laying angle, and airship flight attitude on power generation. PTEM's effectiveness is demonstrated through detailed power output graphs, revealing that radiation gradients significantly affect power generation, often leading to overestimations in the Photo-Thermal Model (PTM) model by 3 %–30 %. Comparative analysis shows that PTEM provides more accurate energy output estimates for individual PV modules, especially in areas with pronounced radiation gradients, differing from PTM estimates by hundreds of watts. These findings offer valuable insights for enhancing PV module lifespan and optimizing energy system designs, contributing to more efficient renewable energy solutions for long-endurance aircraft.

Design of perovskite solar brick for textile ceramic technology

Textile Ceramic Technology (TCT) is an innovative industrialised façade cladding system that consist of a steel wire mesh in where ceramic pieces are inserted in. This paper presents the first steps in the design of a Solar Brick (SB) for TCT capable of producing energy. The perovskite solar thin-film emerging technology is the photovoltaic system considered for the design in this study considering its excellent electrical performances and its ability to be fabricated on flexible substrate. The present research shows the first SB prototype and the experimental tests carried out to check the performance and market viability possibilities.

Optimization of shared energy storage configuration for village-level photovoltaic systems considering vehicle charging management

Distributed renewable energy is more abundant in rural areas, and a large amount of distributed photovoltaic grid-connected power brings challenges to the stable of the power grid. How to promote the self-generation and self-consumption of distributed renewable energy has become an urgent problem. In this paper, a village-level distributed photovoltaic power generation system including energy storage and electric vehicles is constructed. With the goal of minimizing the photovoltaic grid-connected power and maximizing the annual comprehensive revenue, the planning model of energy storage capacity allocation for village-level distributed power generation system is constructed. Considering the charging management for different numbers of electric vehicles, the optimal energy storage capacity allocation strategy is solved using the improved particle swarm algorithm.Five scenarios are set up as examples to be analyzed.The conclusions are:(1)After the configuration of a reasonable energy storage,the grid-connected generation of the system is significantly reduced,and the annual comprehensive revenue of the system is significantly increased.(2)After considering charging management for different numbers of electric vehicles, the capacity and power of the energy storage configuration can be significantly reduced, thus reducing the energy storage investment cost and operation and maintenance cost, and further significantly improving the annual comprehensive revenue of this system.

Effect of Ga Variation on the Bulk and Grain‐Boundary Properties of Cu(In,Ga)Se2 Absorbers in Thin‐Film Solar Cells and Their Impacts on Open‐Circuit Voltage Losses

ABSTRACTPolycrystalline widegap Cu(In,Ga)Se2 (CIGSe) absorbers for top cells in photovoltaic tandem devices can be synthesized via [Ga]/([Ga] + [In]) (GGI) ratios of > 0.5. However, the power conversion efficiencies of such high‐GGI devices are smaller than those of the record cells with GGI < 0.5. In the present work, the effects of the GGI ratio on various CIGSe material properties were studied and correlated with the radiative and nonradiative open‐circuit voltage (VOC) deficits of the thin‐film solar cells. Average grain sizes, grain boundary (GB) recombination velocities, fluctuations in luminescence energy distribution, barrier heights at GBs, effective electron lifetimes, and Urbach energies were investigated in five solar cells with GGI ratios from 0.13 to 0.83. It was found that the GGI variation affects GB recombination velocities, fluctuations in spatial luminescence distributions, the average grain size, the electron lifetime, and the Urbach energy. In contrast, the detected ranges of barrier heights at GBs are independent of the GGI ratio. Mainly Ga/In gradients give rise to substantial radiative VOC losses in all solar cells. Nonradiative VOC deficits are dominant especially for solar cells with GGI > 0.5, which can be attributed to low bulk lifetimes and enhanced recombination at GBs in CIGSe absorbers in this compositional range.

Practical application of machine learning in energy and thermal management: Long-term data analysis of solar-assisted AC systems in portable cabins in Kuwait and Australia

Machine learning techniques are advancing rapidly in theoretical grounds, but their practical application and real evaluation in engineering disciplines are limited. This study investigates one-year of experimental data for indoor air conditions and energy monitoring of two identical portable cabins in Kuwait. Additionally, a 9-month period of solar photovoltaic energy production is experimentally obtained for assessing energy saving aspects of a solar assisted air conditioning system in one of the cabins. A transient system simulation tool model is developed and validated for the portable cabins. Both one-year experimental data and the validated simulation data are used for developing machine learning models for six case studies in Kuwait and Australia. In simulations, there are issues related to lack of access to real-time weather data from a locally installed weather station. In experimental works, there were issues related to disruption of data collection due to power or internet shutdowns. To resolve these issues, nineteen regression models are investigated. It was found that all models performed very well although the Matern 5/2 and Exponential gaussian process regression model performed slightly better, with all models achieving high accuracy, as indicated by R-squared values close to 1.0 in all six case studies. Overall, it was found that the photovoltaic solar-assisted air conditioning system could save annually 26.2 % and 75.7 % energy in Kuwait and Rockhampton, Australia, respectively.

Techno – economic and environmental design of a three – phase hybrid renewable energy system for UNVDA Ndop Cameroon using meta-heuristic and analytical approaches

A three – phase hybrid renewable energy system have been proposed in this study as an alternate current grid power supply for an agro – company in the North – West Region of Cameroon. In this study, an industrial load profile with an energy demand of 383.45 kWh/day, 72.79 kWp peak and a residential load with energy demand of 33.26 kWh/day, 2.7 kWp peak have been considered in solving the economic, technical and environmental aspects of the optimization problem. To achieve the best results, a two step methodology has been implored to design the system. The first method requires an analytical approach used to determine the required battery, inverter, diesel generator capacities and the number of three phase PV arrays (NF). The second methodology is a techno – economic and environmental analysis conducted for different number of NF using three meta-heuristic algorithms; ABC, GA and PSO. The obtained results from these methodologies showed that for different values of NF, the REF was in the range 62.9–99.8 % in the Photovoltaic hybrid system (PVHS). The lowest cost of energy was 0.1441 €/kWh at a final REF of 99.8 % compared to a standalone system with an energy cost of 0.1655 €/kWh. The PVHS consist of a 117 kW PV array, 30 kW inverter, 160 kW diesel generator operating at a load factor of 75 % and a battery bank capacity of 43.2 kWh. The Standalone option consist of a 126 kW PV array, 135 kW inverter and a battery bank capacity of 475.2 kWh. The large inverter capacity and battery bank in the standalone system accounts for the high energy cost compared to the PVHS. This study can be used to evaluate and validate the performance of hybrid renewable energy systems for agro – companies whose load profile lack time series data and require a three – phase supply for industrial applications.

Investigating the performance of water-mounted solar photo-voltaic systems using different simulation tools

Water-mounted solar photovoltaics plants, which include canal-top and floating systems, offer several advantages over traditional ground mounted systems. However, studying their feasibility can be challenging due to limitations in commercial simulation tools. These tools often rely on unrealistic parameters, and studies comparing them have concluded that they may not be suitable for simulating these newer systems. This research addresses the above-mentioned gap by developing improved simulation methods for water–mounted solar plants. The study compared the actual performance of a 1 MW canal-top system and a 732 kW floating system in India with simulations from six different commercial tools. The analysis revealed that PVsyst and SolarGIS were the most accurate in predicting performance for the canal-top system, while PVsol and SolarGIS–Prospect performed best for the floating system. By following comprehensive methodology outlined in this study, minimal Root–Mean–Square error values ranging from 0.74 to 3.33 for the canal-top system and 2.13 to 5.20 for the floating system were achieved for different parameters. These results highlight that accurate performance predictions depend on three factors: the precision of meteorological data, the capabilities of the simulation tool for water-mounted systems, and the tool’s ability to be customized for specific system details. This study helps solar developers and researchers choose the most suitable simulation tools and customize them for feasibility studies. It also helps stakeholders predict the energy output of existing water–mounted systems more accurately, reducing the risk of penalties due to deviations from predicted output.

Mapping development potential and priority zones for utility-scale photovoltaic on the Qinghai-Tibet Plateau

Sustainable renewable energy is a critical goal of the 2030 Sustainable Development Agenda. The scientific and rational development of solar power in the Qinghai-Tibet Plateau (QTP) is vital for China's carbon peak and carbon neutrality goals. However, more accurate, high spatial resolution assessments are needed to evaluate the utility-scale photovoltaic (PV) development potential on the QTP. To address this, we integrated geographical and technical potentials into a unified framework for assessing PV development potential. Using the spatial multi-criteria decision analysis technique, supported by the Bayesian Best-Worst method, we generated a 30-m suitability map for assessing geographical and technical potentials, along with priority zones. We found that approximately 35.22 % of the study area is suitable for utility-scale PV development, mainly concentrated in the Qaidam Basin in Qinghai and the northern Tibet Plateau in Xizang. The estimated PV technical potential for highly suitable and suitable classes is approximately 42.34 million GWh/a, which is equivalent to reduction of approximately 31.43 billion t/a of carbon emissions. We also formulated four priority development strategies using a spatially explicit model to meet the urgent 2030 target for utility-scale PV installations. Moreover, validation of existing PV projects and sensitivity analysis were conducted, confirming the accuracy and robustness of the results. This study provides practical guidance for informed decision-making by the government, investors, and stakeholders.

A novel technique to detect and mitigate harmonic during islanding in grid connected PV system

The integration of photovoltaic (PV) systems into the power grid has become increasingly prevalent, providing sustainable and renewable energy solutions. However, the occurrence of islanding events, where a portion of the PV system operates independently from the main grid, presents challenges in maintaining power quality. This research paper investigates the harmonic distortions during islanding in grid-connected PV systems and proposes effective mitigation strategies. The study employs advanced simulation tools to analyse the dynamic behavior of the PV system during islanding scenarios, focusing on the occurrence and characteristics of harmonics. A detailed investigation into the root causes of harmonic distortions is conducted, considering factors such as grid fluctuations, inverter operation, and system impedance. Based on the findings, this paper introduces novel harmonic mitigation techniques tailored for islanding conditions. These techniques encompass advanced control algorithms, filter designs, and modulation strategies to suppress harmonics and enhance the overall system performance during islanded operation. Comparative assessments of different mitigation approaches are presented, evaluating their effectiveness in minimizing harmonic distortions and maintaining grid code compliance. The research contributes valuable insights to the field of grid-connected PV systems, offering a comprehensive understanding of harmonic issues during islanding events and proposing innovative solutions for their mitigation. The outcomes of this study are crucial for advancing the reliability, stability, and power quality of PV systems that are connected to the grid, which makes it possible for green energy sources to be added to the grid without any problems.

Research on fault diagnosis for three-phase rectifier device in direct current transmission system based on continuous wavelet transform and vision transformer

Abstract As a core component of photovoltaic power generation systems, the three-phase rectifier device plays a crucial role, and its failure can potentially reduce energy conversion efficiency and output quality. Presently, the performance of fault time-domain signal diagnosis methods based on three-phase rectifier circuits is challenging to enhance. This paper proposes a novel fault detection method for three-phase rectifier devices based on Vision Transformer, referred to as CWT-ViT, to address this issue. This method transforms time-domain fault signals into images through Continuous Wavelet Transform (CWT), subsequently inputting these images into a Vision Transformer model. Relying on its powerful self-attention mechanism and fully connected layers, it realizes the extraction and learning of rectifier device image features. A Simulink simulation model of a three-phase bridge controllable rectifier circuit is established for fault injection to collect fault signals. Fault diagnosis experiments demonstrate that the proposed diagnostic method achieves a prediction accuracy of 98.6%, maintaining a relatively high precision level. In comparison to four excellent classification models currently available: AlexNet, RepVGG, ResNet, and GoogLeNet, the proposed method demonstrates superior diagnostic performance. Additionally, this paper conducts ablation experiments to meticulously analyze the impact of each module in the fault diagnosis process. This research achieves more precise and efficient fault diagnosis in photovoltaic power generation systems, thereby reducing downtime and maintenance costs for actual equipment and enhancing the stability of photovoltaic power generation systems. This research provides an innovative, intelligent solution for the intelligent operations and maintenance of photovoltaic power generation.

Optimising building performance for a resilient Future: A Multi-Objective approach to Net Zero energy strategies

The escalating impacts of climate change on urban environments underscore the imperative for energy-efficient buildings. As the building sector constitutes approximately 40% of global energy consumption, the implementation of NZE designs is critical for emission reduction. This study utilised Building Performance Optimisation methodologies alongside a multi-stage optimisation framework to evaluate energy consumption, Life cycle cost and carbon emissions under various climate scenarios (RCP 2.6, 4.5, and 8.5) in three Algerian cities—Constantine (semi-arid), Algiers (Mediterranean), and Ghardaïa (arid).The results revealed that the integration of passive, active, and renewable energy strategies significantly curtailed energy consumption and CO2 emissions across different climatic contexts. Specifically, passive measures achieved reductions in energy use ranging from 39% in Ghardaïa to 15% in Constantine. Active systems, including high-efficiency HVAC technologies, resulted in energy savings of 59% in Ghardaïa, 52% in Algiers, and 47% in Constantine. Furthermore, renewable energy sources, with a focus on solar photovoltaics, contributed additional reductions: 44% in Algiers, 26% in Ghardaïa, and 20% in Constantine. The multi-stage optimisation approach also enhanced computational efficiency, significantly reducing simulation time and facilitating the rapid identification of optimal strategies.These findings highlight the efficacy of integrating a range of energy strategies to achieve NZE. Nevertheless, while these systems demonstrate robust performance under current conditions, their effectiveness diminishes under future climate scenarios, underscoring the necessity for adaptive and resilient design approaches. Ongoing optimisation and innovation will be essential to maintaining the efficacy of NZE strategies in the face of extreme future climate conditions.

Energy system models should consider evolving charging profiles

Abstract Globally, sales of battery electric vehicles (BEVs) are surpassing records every year, and their growing charging needs will ultimately reshape power infrastructure planning practices. While studies have analyzed the impact of light-duty BEVs on the electricity sector, they have overlooked the prospective evolution in charging profiles. We developed a framework for analyzing passenger vehicle electrification futures accounting for the evolution in charging infrastructure, BEVs technical features, and socio-demographics. We soft-link a BEV charging profiles generator with an energy system optimization model to analyze a light-duty vehicle (LDV) electrification scenario in the U.S. from 2020-2050. Compared to static charging profiles, common in prior work, evolving profiles lead to substantial differences in projected power plant installed capacity (up to ~300 GW more solar PV) and activity (up to ~460 TWh more solar PV generation). Hence, future studies should consider not only different charging profiles (e.g., day, night, uncontrolled) but also how these evolve over time.

Recent investigation on VHF sound exposure sources around us

We have reported recent investigation of sound exposure sources in very-high frequency (VHF) region as the activities for research project of VHF sounds in Japan. Recently, the devices which utilize or generate VHF sounds as like rodent repelling devices, ultrasonic cleaning machines, IH cookers and corner sensors of automobile continue to increase in public space or our living environment. The VHF sounds in high level have physical or/and psychological effects for young people who can hear such sounds. So, in environment around us, we identified VHF sound sources using acoustic camera and measured the sound pressure level for such sources. In this paper, we introduce newly-discovered several VHF sounds: for example, ultrasounds from corner sensors of automobile car, VHF sounds from photovoltaic installation and VHF sounds of interior train, and so on. From both the results measured by acoustic camera and microphones show source positions and frequency characteristics of VHF sounds. However these play important role in our life environment, we need to note that these contain potential hazard for young people who can hear such VHF sounds.

Detecting fault in photovoltaic system with a hybrid PDACNN-IDMOA methodology

Detecting fault in photovoltaic system with a hybrid PDACNN-IDMOA methodology

Current-Sensorless Method for Photovoltaic System Using Capacitor Charging Characteristics

The installed capacity of photovoltaic (PV) systems has increased significantly over the past few decades, and related technologies have advanced significantly. The electrical characteristics of a PV system change nonlinearly based on irradiation and temperature, and the I–V characteristic curve, expressed in terms of the voltage and current, is used to verify these characteristics. The maximum power point tracking (MPPT) control method was applied to maximize the performance of the PV system. Voltage and current sensors are used to control the I–V characteristic curve and MPPT; however, current sensors have various disadvantages in terms of price and system configuration. Therefore, this study presents a method for calculating the current of a PV system using the charging characteristics of a capacitor. The method presented in this paper analyzes the I–V characteristic curve’s qualities through simulations and experiments under normal, shaded, and mismatched conditions of the PV module.

A novel interleaved BIFRED-Zeta with intelligent MPPT for PV applications

ABSTRACT The current energy perspective postulates profound presence of Renewable Energy Sources (RESs), resulting in need for optimal DC-DC converter design to assure efficient power conversion and minimise losses. By minimising energy losses and improving power quality, an optimal converter design helps ensure a stable and reliable power supply from RESs, which is essential for meeting the growing demand for clean energy. Therefore, this research introduces an innovative Interleaved BIFRED-Zeta converter configuration, designed to meet all criteria associated with an optimal converter design. The interleaved architecture of converter allows the reduction of current ripples and voltage stress along with the improvement of efficiency. Furthermore, the absence of transformer in converter structure enables it to be simple, cost effective and less bulky. The Interleaved Boost Integrated Flyback Rectifier Energy Storage DC-DC (BIFRED)-Zeta converter duty cycle is adjusted continuously using Cascaded Artificial Neural Network (ANN) Maximum Power Point Tracking (MPPT) to further maximise Photovoltaics (PV) system power output. The capability of suggested converter design is demonstrated by the results obtained using simulation and laboratory prototype implementation. Thereby, a peak efficiency of 97.6% is estimated to be achieved using suggested converter design.

Anomaly detection of photovoltaic power generation based on quantile regression recurrent neural network

Distributed photovoltaic (PV) power generation systems are widely spread. Moreover, due to the randomness of meteorological conditions and the complexity of installation environments, it is difficult to eliminate the interference of factors such as meteorological fluctuations in the monitoring of abnormal states of PV equipment. Based on this, this paper proposes a PV power generation anomaly detection method based on Quantile Regression Recurrent Neural Network (QRRNN). First, the characteristics of solar irradiance on clear days are analyzed, and the clear day masking method is used to eliminate the interference of cloudy and rainy weather. Then, the output correlation of different power stations is analyzed to obtain PV stations with high output correlation as the horizontal reference, which is used to exclude interferences such as permanent faults at the power stations. At the same time, vertical comparison of the output curves of the station under test on different clear days is conducted to eliminate interference factors such as weather and environmental conditions. Subsequently, the metered active power output data, which is free from interference, is input into the QRRNN model to obtain the normal active power output range of the PV. The power threshold of the normal output range is utilized to identify anomalies in PV power generation. Finally, simulation analysis of actual PV system data is conducted, and the results show that the method can effectively identify PV power generation anomalies and has high accuracy in PV fault detection.

Monolithically integrated neuromorphic electronic skin for biomimetic radiation shielding.

Melanogenesis, a natural responsive mechanism of human skin to harmful radiation, is a self-triggered defensive neural activity safeguarding the body from radiation exposure in advance. With the increasing significance of radiation shielding in diverse medical health care and wearable applications, a biomimetic neuromorphic optoelectronic system with adaptive radiation shielding capability is often needed. Here, we demonstrate a transparent and flexible metal oxide-based photovoltaic neuromorphic defensive system. By using a monolithically integrated ultraflexible optoelectronic circuitry and electrochromic device, seamless neural processing for ultraviolet (UV) radiation shielding including history-based sensing, memorizing, risk recognition, and blocking can be realized with piling the entire signal chain into the flexible devices. The UV shielding capability of the system can be evaluated as autonomous blocking up to 97% of UV radiation from 5 to 90 watts per square meter in less than 16.9 seconds, demonstrating autonomously modulated sensitivity and response time corresponding to UV environmental conditions and supplied bias.