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.

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.

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.

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。

绿色金融支持我国东部地区BIPV建筑发展评价及耦合分析

以我国东部地区的10个省(市)为例,建立2017-2021年绿色金融和光伏建筑一体化(BIPV)发展的评价指标体系,并利用熵值法与耦合协调度模型开展实证分析。研究结果表明:从区域性发展差异上看,绿色金融发展和BIPV建筑发展水平较高的是上海市和北京市,相对落后的是河北省和海南省;从发展态势上看,绿色金融和BIPV建筑发展总体上呈上升趋势;从耦合特征上看,近年来我国东部地区绿色金融和BIPV建筑发展两系统之间的耦合度及耦合协调度均较高,且总体呈逐步增长的趋势。

基于PVsyst的光伏设计及阴影仿真

为了降低光伏电站的初始投资,以常州科教城为例,根据当地的气象、环境等因素,设计了一套并网光伏发电系统,对光伏组件倾角选择、组件串并联、逆变器选型、方阵最小间距等进行了优化设计。在组件布置过程中,对阴影遮挡现象进行了分析,运用PVsyst软件对设计方案进行模拟仿真。通过仿真结果提出了电站设计的可行性建议,对光伏电站的降本增效具有指导意义。

BIPV/T–DSF与新风一体化系统性能模拟研究

为提高光伏光热建筑一体化技术中光伏组件发电效率,充分利用其光热能量,同时满足室内人员对新风的需求,本研究将光伏光热建筑一体化技术与双层皮玻璃幕墙相结合,组成BIPV/T–DSF与新风一体化系统。以沈阳市一间30 m2的卧室为研究对象,通过实地测量室内污染物浓度并进行系统仿真模拟,对室内空气质量状况进行评估,并对系统的热电性能、空气通道内流场的流动特性进行研究。结果表明:系统运行时,冬季热效率达到0.22,电效率达到0.178;夏季电效率由原来的0.151提高到0.156。新风对于室内甲醛浓度有较好的净化效果,系统通风运行20 min后,甲醛浓度即可稳定在0.033 mg/m3。

Synergetic optimization operation method for distribution network based on SOP and PV

The integration of distributed generation brings in new challenges for the operation of distribution networks,including out-of-limit voltage and power flow control.Soft open points(SOP)are new power electronic devices that can flexibly control active and reactive power flows.With the exception of active power output,photovoltaic(PV)devices can provide reactive power compensation through an inverter.Thus,a synergetic optimization operation method for SOP and PV in a distribution network is proposed.A synergetic optimization model was developed.The voltage deviation,network loss,and ratio of photovoltaic abandonment were selected as the objective functions.The PV model was improved by considering the three reactive power output modes of the PV inverter.Both the load fluctuation and loss of the SOP were considered.Three multi-objective optimization algorithms were used,and a compromise optimal solution was calculated.Case studies were conducted using an IEEE 33-node system.The simulation results indicated that the SOP and PVs complemented each other in terms of active power transmission and reactive power compensation.Synergetic optimization improves power control capability and flexibility,providing better power quality and PV consumption rate.

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.

应用PSO-RBF神经网络预测太阳能PV/T系统的热、电性能

为准确预测太阳能光伏光热(Solar Photovoltaic/Thermal,PV/T)系统的热、电性能,文章利用PSO(Particle Swarm Optimization)算法优化了RBF(Radial Basis Function)神经网络,并基于此方法建立了太阳能PV/T系统性能的仿真预测模型,与基于未优化RBF神经网络建立的预测模型进行了对比分析。同时,搭建了太阳能PV/T实验平台,通过云平台采集实验数据用于上述模型。研究结果表明:使用PSO算法优化后的RBF神经网络模型相较于未优化模型预测精度提高了20%,预测稳定性提高了30%,拟合优度R值有所提升。基于PSO-RBF神经网络建立的预测模型可精确预测太阳能PV/T系统的热、电性能。

太阳能PV/T+相变能与直蒸式水源热泵供热(冷)系统特性分析

为解决河北农村建筑清洁供暖问题和太阳能利用具有不稳定性问题,设计了太阳能PV/T+相变能与直蒸式水源热泵供热(冷)系统进行实验研究。实验结果表明,冬季典型日系统发电量为4.453kWh,制热系数COP平均值3.41;夏季典型日系统发电量为5.945kWh,制冷系数EER平均值3.2;将发电量用于系统运行,制热系数COP为4.22,制冷系数EER为4.19,分别提高了23.75%和30.12%;夏季单纯PV/T太阳能电池发电量5.537kWh,本系统的发电量提高了7.37%。该系统经济效益高,运行稳定,是一种实现河北农村清洁供暖有效途径。

从BIPV(光伏建筑一体化)到BIPVES(光伏储能建筑一体化)

[目的]随着光伏、储能、新型建材及装配式建筑产业的发展,将光伏组件与屋面、墙体、遮阳等构件进行一体化设计与制造的光伏建筑一体化(Building Integrated Photovoltaic,BIPV)技术开始延伸为光伏储能建筑一体化(Building Integrated Photovoltaic and Energy Storge,BIPVES)技术。[方法]文章提出世界首个可充电水泥电池,将建筑墙体与光伏发电装置、储放电装置相融合;对设备和材料进行跨界创新,在玻璃表面打印高清晰度、高透光率花纹图案,制造高效光伏建材;研发预制式储能墙体,与各类钢结构装配式建筑体系进行结合,实现订制式生产、装配式施工,形成建筑构件与光伏、储能一体化的变革趋势。[结果]水泥基电池实现了建筑墙体具有光伏发电、储电以及供电等多种功能;新一代光伏建材可节省建筑外立面装饰材料的成本,降低建筑物碳排放;光伏和储能等可再生能源技术在建筑中的一体化集成,可取得最大化收益。[结论]新型光伏建材技术和水泥电池等新型储能技术具有发展前景,将可充电电池构件、光伏外墙板与装配式建筑墙体及预埋件进行组合集成并推广应用具有可行性。

Study on Image Recognition Algorithm for Residual Snow and Ice on Photovoltaic Modules

The accumulation of snow and ice on PV modules can have a detrimental impact on power generation,leading to reduced efficiency for prolonged periods.Thus,it becomes imperative to develop an intelligent system capable of accurately assessing the extent of snow and ice coverage on PV modules.To address this issue,the article proposes an innovative ice and snow recognition algorithm that effectively segments the ice and snow areas within the collected images.Furthermore,the algorithm incorporates an analysis of the morphological characteristics of ice and snow coverage on PV modules,allowing for the establishment of a residual ice and snow recognition process.This process utilizes both the external ellipse method and the pixel statistical method to refine the identification process.The effectiveness of the proposed algorithm is validated through extensive testing with isolated and continuous snow area pictures.The results demonstrate the algorithm’s accuracy and reliability in identifying and quantifying residual snow and ice on PV modules.In conclusion,this research presents a valuable method for accurately detecting and quantifying snow and ice coverage on PV modules.This breakthrough is of utmost significance for PV power plants,as it enables predictions of power generation efficiency and facilitates efficient PV maintenance during the challenging winter conditions characterized by snow and ice.By proactively managing snow and ice coverage,PV power plants can optimize energy production and minimize downtime,ensuring a sustainable and reliable renewable energy supply.

基于PV/T的双源热泵热水系统的实验研究

为提高热泵热水循环的效率,构建基于光伏/光热一体化(PV/T)的双源热泵热水系统,选取全年中4个典型日,测试系统的可靠性、热泵运行性能以及PV/T运行特性。结果表明:系统的电源和热源可稳定使用;4个典型工况中,环境温度为27.3℃、太阳辐照度为975.6 W/m^(2)时热泵运行性能最优,制热系数(COPh)达到6.2,PV/T性能最优,平均光电转换效率相对于传统光伏组件高6.6%,总发电量比传统光伏组件高0.11 kWh。

PV/T耦合水环热泵系统全年运行性能分析

为研究裸板型PV/T组件与水环热泵耦合系统的电热联供性能,本文基于天津某办公楼的零碳化改造项目,搭建了PV/T耦合水箱、水环热泵,通过温差控制,实现PV/T集散热独立循环,耦合热泵制热和制冷,以满足建筑多种用能需求的低碳能源系统。测试分析了冬季典型日、夏季典型日,PV、PV/T和水箱内的温度变化特性,PV/T、PV系统的发电功率、发电效率、PV/T的集热效率以及综合效率,比较了PV/T系统和PV系统的性能。结果显示,在冬季典型日,PV/T组件与PV组件的平均温差达16.1℃,PV/T发电效率较PV提高了2.2%,PV/T集热效率为42.2%,综合效率为52.6%,系统平均性能系数为6.06;在夏季典型日,PV/T发电效率较PV提高了3.8%,PV/T集热效率为59.1%,综合效率最高为73.6%,系统平均性能系数为6.86。研究表明,PV/T耦合水环热泵系统全年较PV发电效率可提高2%以上,集热效率>40%,系统平均性能系数>6.0,具有较强的节能减排特点。

分体式太阳能PVT热泵系统试验运行性能分析

在既有光伏组件的基础上,安装集热背板形成分体式PVT组件,搭建分体式PVT热泵系统试验台,在晴天和多云典型日2种工况下进行系统运行性能试验,将水箱内的水从常温加热到60℃。试验结果表明,在晴天和多云典型日下,系统平均COP分别为4.11和4.20,均高于相同工况下的空气源热泵;最大发电效率分别为13.2%和19.9%,PVT组件表面温度分布均低于40℃,有明显的降温提效作用;平均得热因子分别为48%和71%,无量纲压力损失系数保持在0.030~0.047,均流性较好。

Electro-Optical Model of Soiling Effects on Photovoltaic Panels and Performance Implications

In this paper,a detailed model of a photovoltaic(PV)panel is used to study the accumulation of dust on solar panels.The presence of dust diminishes the incident light intensity penetrating the panel’s cover glass,as it increases the reflection of light by particles.This phenomenon,commonly known as the“soiling effect”,presents a significant challenge to PV systems on a global scale.Two basic models of the equivalent circuits of a solar cell can be found,namely the single-diode model and the two-diode models.The limitation of efficiency data in manufacturers’datasheets has encouraged us to develop an equivalent electrical model that is efficient under dust conditions,integrated with optical transmittance considerations to investigate the soiling effect.The proposed approach is based on the use of experimental current-voltage(I-V)characteristics with simulated data using MATLAB/Simulink.Our research outcomes underscores the feasibility of accurately quantifying the reduction in energy production resulting from soiling by assessing the optical transmittance of accumulated dust on the surface of PV glass.

“双碳”背景下BIPV的应用与探索

“双碳”目标提出后,中国的绿色经济发展有了更加明确的方向。城镇化率不断增长的同时,中国的建筑业进入了鼎盛发展时期;但与此同时出现的建筑能耗问题也越来越严重,这种发展形式与“双碳”目标背道而驰。而光伏发电技术与建筑相结合成为解决这一问题的有效方式,光伏建筑一体化(BIPV)产业的发展是实现“双碳”目标的重要途径。针对当前BIPV产业的发展状况及发展优势进行了分析,并分析了影响BIPV建筑发电量的因素,然后从技术、法律法规、市场3个方面提出了优化举措。分析结果显示:光伏组件方位角及安装倾角、光伏组件表面灰尘及其安装方式是制约BIPV建筑发电量的主要因素,BIPV后续发展需要从技术方面进行改进以确保年发电量达到预期目标;BIPV产业应从技术、法律法规及市场3个方面进行改进和完善,有助于其更好的发展。该研究结果对BIPV理论研究和工程人员施工设计具有一定的参考价值。