Numerical Assessment of the Thermal Efficiency of a Concentrated Photovoltaic/Thermal (CPV/T) Hybrid System Using Air as Heat Transfer Fluid

In this paper, we propose a thermal model of a hybrid photovoltaic/thermal concentration system. Starting from the thermal balance of the model, the equation is solved and simulated with a MATLAB code, considering air as the cooling fluid. This enabled us to evaluate some of the parameters influencing the electrical and thermal performance of this device. The results showed that the temperature, thermal efficiency and electrical efficiency delivered depend on the air mass flow rate. The electrical and thermal efficiencies for different values of air mass flow are encouraging, and demonstrate the benefits of cooling photovoltaic cells. The results show that thermal efficiency decreases air flow rate greater than 0.7 kg/s, whatever the value of the light concentration used. The thermal efficiency of the solar cell increases as the light concentration increases, whatever the air flow rate used. For a concentration equal to 30 sun, the thermal efficiency is 0.16 with an air flow rate equal to 0.005 kg/s;the thermal efficiency increases to 0.19 with an air flow rate equal to 0.1 kg/s at the same concentration. An interesting and useful finding was that the proposed numerical model allows the determination of the electrical as well as thermal efficiency of the hybrid CPV/T with air flow as cooling fluid.

Performance Assessment of a Real PV System Connected to a Low-Voltage Grid

The generation of photovoltaic(PV)solar energy is increasing continuously because it is renewable,unlimited,and clean energy.In the past,generation systems depended on non-renewable sources such as oil,coal,and gas.Therefore,this paper assesses the performance of a 51 kW PV solar power plant connected to a low-voltage grid to feed an administrative building in the 6th of October City,Egypt.The performance analysis of the considered grid-connected PV system is carried out using power system simulator for Engineering(PSS/E)software.Where the PSS/E program,monitors and uses the power analyzer that displays the parameters and measures some parameters such as current,voltage,total power,power factor,frequency,and current and voltage harmonics,the used inverter from the type of grid inverter for the considered system.The results conclude that when the maximum solar radiation is reached,the maximum current can be obtained from the solar panels,thus obtaining the maximum power and power factor.Decreasing total voltage harmonic distortion,a current harmonic distortion within permissible limits using active harmonic distortion because this type is fast in processing up to 300 microseconds.The connection between solar stations and the national grid makes the system more efficient.

Forestvoltaics,Floatovoltaics and Building Applied Photovoltaics(BAPV)Potential for a University Campus

The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs of slowing down,with solar photovoltaic(PV)panels being the primary technology for converting sunlight into electricity.Advancements are continuously being made to ensure cost-effectiveness,high-performing cells,extended lifespans,and minimal maintenance requirements.This study focuses on identifying suitable locations for implementing solar PVsystems at theUniversityMalaysia PahangAl SultanAbdullah(UMPSA),Pekan campus including buildings,water bodies,and forest areas.A combined technical and economic analysis is conducted using Helioscope for simulations and the Photovoltaic Geographic Information System(PVGIS)for economic considerations.Helioscope simulation examine case studies for PV installations in forested areas,lakes,and buildings.This approach provides comprehensive estimations of solar photovoltaic potential,annual cost savings,electricity costs,and greenhouse gas emission reductions.Based on land coverage percentages,Floatovoltaics have a large solar PV capacity of 32.3 Megawatts(MW);forest-based photovoltaics(Forestvoltaics)achieve maximum yearly savings of RM 37,268,550;and Building Applied Photovoltaics(BAPV)have the lowest CO2 emissions and net carbon dioxide reduction compared to other plant sizes.It also clarifies the purpose of using both software tools to achieve a comprehensive understanding of both technical and economic aspects.

Probabilistic Global Maximum Power Point Tracking Algorithm for Continuously Varying Partial Shading Conditions on Autonomous PV Systems

A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.

Analysis for Effects of Temperature Rise of PV Modules upon Driving Distance of Vehicle Integrated Photovoltaic Electric Vehicles

The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO2 emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV.

Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Systematic Review on Ground-Based Cloud Tracking Methods for Photovoltaics Nowcasting

Renewable energies are highly dependent on local weather conditions, with photovoltaic energy being particularly affected by intermittent clouds. Anticipating the impact of cloud shadows on power plants is crucial, as clouds can cause partial shading, excessive irradiation, and operational issues. This study focuses on analyzing cloud tracking methods for short-term forecasts, aiming to mitigate such impacts. We conducted a systematic literature review, highlighting the most significant articles on cloud tracking from ground-based observations. We explore both traditional image processing techniques and advances in deep learning models. Additionally, we discuss current challenges and future research directions in this rapidly evolving field, aiming to provide a comprehensive overview of the state of the art and identify opportunities for significant advancements in the next generation of cloud tracking systems based on computer vision and deep learning.

PV Capacity Evaluation Using ASTM E2848: Techniques for Accuracy and Reliability in Bifacial Systems

A variety of test methodologies are commonly used to assess if a photovoltaic system can perform in line with expectations generated by a computer simulation. One of the commonly used methodologies across the PV industry is an ASTM E2848. ASTM E2848-13, 2023 test method provides measurement and analysis procedures for determining the capacity of a specific photovoltaic system built in a particular place and in operation under natural sunlight. This test method is mainly used for acceptance testing of newly installed photovoltaic systems, reporting of DC or AC system performance, and monitoring of photovoltaic system performance. The purpose of the PV Capacity Test and modeled energy test is to verify that the integrated system formed from all components of the PV Project has a production capacity that achieves the Guaranteed Capacity and the Guaranteed modeled AEP under measured weather conditions that occur when each PV Capacity Test is conducted. In this paper, we will be discussing ASTM E2848 PV Capacity test plan purpose and scope, methodology, Selection of reporting conditions (RC), data requirements, calculation of results, reporting, challenges, acceptance criteria on pass/fail test results, Cure period, and Sole remedy for EPC contractors for bifacial irradiance.

Maximizing Solar Potential Using the Differential Grey Wolf Algorithm for PV System Optimization

Maximum Power Point Tracking(MPPT)is crucial for maximizing the energy output of photovoltaic(PV)systems by continuously adjusting the operating point of the panels to track the point of maximum power production under changing environmental conditions.This work proposes the design of an MPPT system for solar PV installations using the Differential Grey Wolf Optimizer(DGWO).It dynamically adjusts the parameters of the MPPT controller,specifically the duty cycle of the SEPIC converter,to efficiently track the Maximum Power Point(MPP).The proposed system aims to enhance the energy harvesting capability of solar PV systems by optimizing their performance under varying solar irradiance,temperature and shading conditions.Simulation results demonstrate the effectiveness of the DGWO-based MPPT system in maximizing the power output of solar PV installations compared to conventional MPPT methods.This research contributes to the development of advanced MPPT techniques for improving the efficiency and reliability of solar energy systems.

Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV units.However,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood.This study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the PV-ESS.First,SD and SMC models were set up.Second,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was constructed.Finally,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation.Additionally,negative electricity prices were considered during clearing processes.The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

Maximum Power Point Tracking Technology for PV Systems: Current Status and Perspectives

Maximum power point tracking(MPPT)technology plays a key role in improving the energy conversion efficiency of photovoltaic(PV)systems,especially when multiple local maximum power points(LMPPs)occur under partial shading conditions(PSC).It is necessary to modify the operating point efficiently and accurately with the help of MPPT technology to maximize the collected power.Even though a lot of research has been carried out and impressive progress achieved for MPPT technology,it still faces some challenges and dilemmas.Firstly,the mathematical model established for PV cells is not precise enough.Second,the existing algorithms are often optimized for specific conditions and lack comprehensive adaptability to the actual operating environment.Besides,a single algorithm may not be able to give full play to its advantages.In the end,the selection criteria for choosing the suitable MPPT algorithm/converter combination to achieve better performance in a given scenario is very limited.Therefore,this paper systematically discusses the current research status and challenges faced by PV MPPT technology around the three aspects of MPPT models,algorithms,and hardware implementation.Through in-depth thinking and discussion,it also puts forward positive perspectives on future development,and five forward-looking solutions to improve the performance of PV systems MPPT are suggested.

KnowledgeMapping of Hybrid Solar PV andWind Energy Standalone Systems: A Bibliometric Analysis

Renewable energy is becoming more attractive as traditional fossil fuels are rapidly depleted and expensive,and their use would release pollutants.Power systems that use both wind and solar energy are more reliable and efficient than those that utilize only one energy.Hybrid renewable energy systems(HRES)are viable for remote areas operating in standalone mode.This paper aims to present the state-of-the-art research on off-grid solar-wind hybrid energy systems over the last two decades.More than 1500 published articles extracted from the Web of Science are analyzed by bibliometric methods and processed by CiteSpace to present the results with figures and tables.Productive countries and highly cited authors are identified,and hot topics with hotspot articles are shown in landscape and timeline views.Emerging trends and new developments related to techno-economic analysis and microgrids,as well as the application of HOMER software,are predicted based on the analysis of citation bursts.Furthermore,the opportunities of hybrid energy systems for sustainable development are discussed,and challenges and possible solutions are proposed.The study of this paper provides researchers with a comprehensive understanding and intuitive representation of standalone solar-wind hybrid energy systems.

FaultMonitoring Strategy for PV System Based on I-V Feature Library

Long-term use in challenging natural conditions is possible for photovoltaic modules,which are extremely prone to failure.Failure to diagnose and address faults in Photovoltaic(PV)power systems in a timely manner can cause permanent damage to PV modules and,in more serious cases,fires.Therefore,research into photovoltaic module defect detection techniques is crucial for the growth of the photovoltaic sector as well as for maintaining national economic prosperity and ensuring public safety.Considering the drawbacks of the current real-time and historical data-based methods for monitoring distributed PV systems,this paper proposes a method for monitoring PV systems at the module or string level that can be achieved by monitoring only electrical signals.The approach doesn’t need a lot of tests to get the operational data of PV modules beforehand and only requires theoretical feature libraries of PV modules through panel parameter calculations.The present operating conditions and the open-circuit and short-circuit faults can be precisely identified by comparing the observed open-circuit voltage and short-circuit current with the corresponding data in the theoretical feature library.After that,by comparing the measured maximum power point voltage and current with the corresponding data in the theoretical feature library through the threshold method,aging and shadowing faults can be accurately determined.Experimental testing was done to see whether the suggested method was effective.The results show that the proposed technique is able to diagnose open-circuit faults,short-circuit faults,aging faults,and shadowing faults with shadow occlusion above 20%.

Investigating Load Regulation Characteristics of a Wind-PV-Coal Storage Multi-Power Generation System

There is a growing need to explore the potential of coal-fired power plants(CFPPs)to enhance the utilization rate of wind power(wind)and photovoltaic power(PV)in the green energy field.This study developed a load regulation model for a multi-power generation system comprising wind,PV,and coal energy storage using realworld data.The power supply process was divided into eight fundamental load regulation scenarios,elucidating the influence of each scenario on load regulation.Within the framework of the multi-power generation system with the wind(50 MW)and PV(50 MW)alongside a CFPP(330 MW),a lithium-iron phosphate energy storage system(LIPBESS)was integrated to improve the system’s load regulation flexibility.The energy storage operation strategy was formulated based on the charging and discharging priority of the LIPBESS for each basic scenario and the charging and discharging load calculation method of LIPBESS auxiliary regulation.Through optimization using the particle swarm algorithm,the optimal capacity of LIPBESS was determined to be within the 5.24-4.88 MWh range.From an economic perspective,the LIPBESS operating with CFPP as the regulating power source was 49.1% lower in capacity compared to the renewable energy-based storage mode.

Economic Feasibility Assessment of Motorized PV Louver System Considering the Near Shading Parameter, Array Incidence Losses and Other Environmental Factors

Seoul has good weather settings for incorporating renewable energies, hence, given its small land area living mode was mostly set in an apartment condition it is an ideal place for building applied photovoltaic (BAPV) for solar energy harvesting. On the other hand, the BAPV energy self-consumption hasn’t been thoroughly examined considering the overall energy consumption requirement. Therefore, presented in this communication are the viability of PVL to produce electricity from solar energy and insights on modulating and improving energy harvesting efficiency. To accomplish this objective, three major factors were considered: 1) the photovoltaic (PV) positioning;2) the solar tracking scenario;and 3) the mechanistic system energy consumption. The overall louver energy generation was thoroughly scrutinized from the net energy conception of the BAPV up to the mechanistic module energy expenditure. This work intends to provide insights into the economic feasibility of BAPV assessing its technological profitability in the specified location and building size.

Reliability-BasedModel for Incomplete Preventive ReplacementMaintenance of Photovoltaic Power Systems

At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.

Tilt Angle Optimality Criteria for Stand Alone PV Systems

The conventional approach to optimizing tilt angles for fixed solar panels aims to maximize energy generation over the entire year. However, in the context of a supply controlled electric grid, where solar energy availability varies, this criterion may not be optimal. This study explores two alternative optimization criteria focused on maximizing baseload supply potential and minimizing required storage capacity to address seasonality in energy generation. The optimal tilt angles determined for these criteria differed significantly from the standard approach. This research highlights additional factors crucial for designing solar power systems beyond gross energy generation, essential for the global transition towards a fully renewable energy-based electric grid in the future.

基于TRNSYS的扁平热管PV/T系统性能优化

基于太阳能技术现状分析,将太阳能光伏组件与扁平式热管高效结合,提出新型扁平热管PV/T系统.为实现该系统综合效率最大化,结合TRNSYS仿真,开展试验并进行优化分析.结果表明,安装扁平热管后夏季热水温度从原来的51.1℃升高到57.3℃,提高了12.1%,冬季热水温度从47.6℃升高到55.2℃,提高了15.9%.夏季系统的综合效率提高了4.7%、冬季系统的综合效率提高了4.8%.可以得出结论扁平热管对PV/T空调系统性能的优化效果明显,也为该技术在建筑领域的应用提供了依据.

基于人工神经网络的PV/T热电联供系统性能预测

为研究太阳能PV/T热电联供系统的性能和针对太阳能PV/T系统复杂的能量平衡方程,搭建了太阳能PV/T系统试验台,同时建立了基于改进灰狼优化的BP神经网络(back propagation neural network model based on improved grey wolf algorithm,IGWO-BP)预测模型,在晴朗天气下进行试验,并采用该模型对系统电功率以及蓄热水箱内水温进行预测。结果显示,晴朗日系统的电效率8.7%~12.2%、热效率51.7%;预测结果与BP神经网络预测模型、基于粒子群优化的BP神经网络(back propagation neural network based on particle swarm optimization,PSO-BP)预测模型和卷积神经网络(convolutional neural network,CNN)预测模型预测结果进行比较,结果显示IGWO-BP预测模型电效率预测模型的绝对百分比误差(mean absolute percentage error,MAPE)、决定系数(determination coefficient,R^(2))、均方根误差(root mean square error,RMSE)、效率因子(efficient factor,EF)和Pearson相关系数(pearson related coefficient,r)分别为4.5E-05、0.99、0.24、0.99和1.00,在储热罐温度预测中,上述指标分别为8.90E-04、0.98、0.07、0.98、0.99,均优于其他预测模型,IGWO-BP神经网络预测模型具有更好的预测性能。研究结果可为太阳能PV/T热电联供系统性能预测与优化控制提供参考。

PV-VSG光伏电站一次调频试验及性能评估方法研究与应用

光伏发电的随机性导致了不同光伏电站出现一次调频性能不足、接入电网频率失稳等问题。而光伏场站的一次调频能力是维持电网稳定性的关键,因此对光伏电站的一次调频能力进行测试与评估具有重要意义。以石城子某光伏电站机组为例,详细介绍了PV-VSG光伏电站实施一次调频的意义、原理及措施,并提出了适用于该光伏电站的一次调频试验技术方案和试验方法。通过频率阶跃及模拟实际电网频率扰动、防扰动性能及自动发电控制(Automatic generation control,AGC)协调的合格率对光伏电站的安全性及稳定性进行评估,具有实际应用价值和推广意义。