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.

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.

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.

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.

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.

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.

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.

太阳能光伏光热PV/T组件在建筑设计中的应用

建筑领域“双碳”目标的提出,使得降低建筑能耗成为目前亟需解决的问题。可再生能源同建筑领域的有机结合被认为是解决建筑能耗的重要环节。通过对太阳能光伏光热技术的发展进行总结,研究太阳能光伏光热技术在建筑领域中的设计方法,提出了对未来光伏光热建筑一体化的设计思考,为以后太阳能光伏光热PV/T技术产业的发展提供参考。

太阳能PV/T光储直驱热电联产系统性能

面对居民日益增长的生活热水和电能需求,光伏/光热(photovoltaic/thermal,PV/T)技术的应用可以降低建筑运行时的能源消耗。本文介绍了一种太阳能PV/T光储直驱热电联产(combined heat and power,CHP)系统,为了减少系统运行过程中的能量损失,采用直流压缩机和储能电池,并在兰州地区对系统的运行性能开展了实验测试。研究结果表明,PV/T系统的光伏板温度相比传统PV组件温度平均降低12.26℃,平均发电效率相对提升8.1%。在将24.4~27.2℃的水加热到50.1~50.7℃的过程中,平均性能系数(coefficient of performance,COP)可达到5.48,相比传统空气源热泵热水器提高82.1%~106.8%。平均集热效率和综合效率分别为37.30%和71.24%,PV/T系统的发电量和耗电量分别为3.33kWh和1.69kWh,发电量相比PV系统提高5.7%。太阳能PV/T光储直驱热电联产系统可以减少建筑部门的能源消耗,并提升PV/T系统的发电效率和综合效率,在晴天条件下可以实现离网运行。

风冷式PV/T空调系统日间冷电联产性能实验研究

提出了一种风冷式PV/T空调系统,对系统在夏季日间的冷电联产性能进行了实验测试,分析了环境因素、运行参数等对系统发电和制冷性能的影响。结果表明:光伏板温度随太阳辐照度的升高而升高,光伏板输出电效率随光伏板温度的升高而降低;太阳辐照度、室外温度和室外风速都对系统制冷性能有影响,其中室外温度对制冷量和COP的影响最大,当室外温度从23.6℃升高到32.8℃时,制冷量增大1.6倍,COP降低38.8%。该风冷式PV/T空调系统在夏季日间具有一定的冷电联产性能,可进一步优化以拓展其使用时间和应用范围。

考虑分布式光伏发电特性的CHPV组合优化调度

近年来光伏装机容量逐年提升,为进一步提高光伏的消纳能力,满足居民的电热需求,本文首先分析分布式光伏的发电特性,提出一种由微型热电联供机组和光伏机组的组合机组,简称CHPV组合,构建以运行成本最低为目标的CHPV组合优化模型,采用K-means聚类方法对某地一年的光伏数据进行聚类,生成3个典型的光伏出力场景并代入CHPV组合优化模型中,采用Cplex对本文所提模型进行仿真验证。结果表明,本文所构建的CHPV组合可有效满足居民不同季节下的电热需求和提高光伏的消纳能力。

“双碳”背景下基于BIPV的应用场景分析

建筑行业在全国碳排放总量中占据着较大的比例,约占三分之一,这使得建筑节能减排成为实现“碳达峰、碳中和”双碳目标的关键环节。目前,建筑行业很多采用的太阳能光伏建筑技术形式为“安装型”(BAPV),即将光伏组件直接附着在建筑表面而非作为建筑材料的一部分。而光伏建筑一体化技术(BIPV)是一种将光伏发电技术与建筑材料进行集成设计的技术,其将光伏发电技术与建筑设计紧密融合,真正实现降低建筑能耗、减少碳排放的目的。该文将从构建型、建材型、结合安装型等角度探讨BIPV技术在建筑场景中的应用,为实现建筑碳排放减排目标提供重要技术支持,以此促进建筑绿色化转型与光伏发电行业发展。

Photovoltaic Models Parameters Estimation Based on Weighted Mean of Vectors

Renewable energy sources are gaining popularity,particularly photovoltaic energy as a clean energy source.This is evident in the advancement of scientific research aimed at improving solar cell performance.Due to the non-linear nature of the photovoltaic cell,modeling solar cells and extracting their parameters is one of the most important challenges in this discipline.As a result,the use of optimization algorithms to solve this problem is expanding and evolving at a rapid rate.In this paper,a weIghted meaN oF vectOrs algorithm(INFO)that calculates the weighted mean for a set of vectors in the search space has been applied to estimate the parameters of solar cells in an efficient and precise way.In each generation,the INFO utilizes three operations to update the vectors’locations:updating rules,vector merging,and local search.The INFO is applied to estimate the parameters of static models such as single and double diodes,as well as dynamic models such as integral and fractional models.The outcomes of all applications are examined and compared to several recent algorithms.As well as the results are evaluated through statistical analysis.The results analyzed supported the proposed algorithm’s efficiency,accuracy,and durability when compared to recent optimization algorithms.

Performance Assessment of Motorized Solar Photovoltaic Louvers System Using PVSYST Software

In the realm of technological market penetration of solar photovoltaic louvers(PVL)addressing environmental difficulties and the industrial revolution,a new avenue of renewable energy is introduced.Moreover,solar energy exploitation through building façades was addressed through motorized solar photovoltaic louvers(MPVL).On the other hand,proponents exalted the benefits of MPVL overlooking the typical analyses.In this communication,we attempted to perform a thorough industrial system evaluation of the MPVL.This communication presents a methodology to validate the industrial claims about MPVL devices and their economic efficiency and the insight on how geographical location influences their utilization and augment their potential benefits.This task is carried out by evaluating the extent of solar energy that can be harvested using solar photovoltaic system(PVSYST)software and investigating whether existing product claims are associated with MPVL are feasible in different locations.The performance and operational losses(temperature,internal network,power electronics)were evaluated.To design and assess the performance of different configurations based on the geographical analogy,simulation tools were successfully carried out based on different topographical locations.Based on these findings,various factors affect the employment of MPVL such as geographical and weather conditions,solar irradiation,and installation efficiency.tt is assumed that we successfully shed light and provided insights into the complexity associated with MPVL.

基于光储混合配置的级联H桥型光伏逆变器功率平衡策略

级联H桥(cascade H-bridge,CHB)变换器由于其模块化结构,已成为大规模光伏(photovoltaic,PV)并网逆变器的优选方案。然而,在不同光照强度和温度下,不同区域PV组件之间发电功率不同,导致CHB变换器相间输出功率不均衡、不稳定等问题。为此,文中提出一种基于CHB结构的光储混合电能路由,在三相CHB光伏逆变器中配置少量的储能模块,利用光储协同控制,维持CHB内部功率稳定,消除分布式PV在相间产生的不均衡功率,且变换器输出功率能够时刻满足网侧上层功率调度,提高了光伏电站的稳定性。针对系统安全区域,在载波移相调制策略下,全桥子模块传输的功率受到约束,并对光伏和储能模块的配置作详细分析。最后,通过仿真以及实验验证所提拓扑及控制策略的正确性和有效性。

A New Flower Pollination Algorithm Strategy for MPPT of Partially Shaded Photovoltaic Arrays

Photovoltaic(PV)systems utilize maximum power point tracking(MPPT)controllers to optimize power output amidst varying environmental conditions.However,the presence of multiple peaks resulting from partial shading poses a challenge to the tracking operation.Under partial shade conditions,the global maximum power point(GMPP)may be missed by most traditional maximum power point tracker.The flower pollination algorithm(FPA)and particle swarm optimization(PSO)are two examples of metaheuristic techniques that can be used to solve the issue of failing to track the GMPP.This paper discusses and resolves all issues associated with using the standard FPA method as the MPPT for PV systems.The first issue is that the initial values of pollen are determined randomly at first,which can lead to premature convergence.To minimize the convergence time and enhance the possibility of detecting the GMPP,the initial pollen values were modified so that they were near the expected peak positions.Secondly,in the modified FPA,population fitness and switch probability values both influence swapping between two-mode optimization,which may improve the flower pollination algorithm’s tracking speed.The performance of the modified flower pollination algorithm(MFPA)is assessed through a comparison with the perturb and observe(P&O)method and the standard FPA method.The simulation results reveal that under different partial shading conditions,the tracking time for MFPA is 0.24,0.24,0.22,and 0.23 s,while for FPA,it is 0.4,0.35,0.45,and 0.37 s.Additionally,the simulation results demonstrate that MFPA achieves higher MPPT efficiency in the same four partial shading conditions,with values of 99.98%,99.90%,99.93%,and 99.26%,compared to FPA with MPPT efficiencies of 99.93%,99.88%,99.91%,and 99.18%.Based on the findings from simulations,the proposed method effectively and accurately tracks the GMPP across a diverse set of environmental conditions.

长三角地区集中式露地农业光伏方阵夏季光热环境试验研究

基于太阳照度和环境温度逐时变化,以长三角地区的集中式露地农业光伏方阵为研究对象,在跨度为6.8 m的单跨方阵中沿从南到北的跨度方向取0.65、3.40、6.15 m处的3个和长度方向共面的测试断面,即南区、中区、北区。基于此,进行夏季方阵内外的光热环境测试,分析并明确光伏组件下方区域的光热环境变化规律,为其太阳能资源合理利用、结构改进和夏季农业生产管理提供参考。结果表明,该地区光伏方阵夏季内部3个区域光热环境呈现规律性差异,整体表现为北区略优于南区,中区优于南、北两区。综合考虑作物生长的光热环境需求,一方面可通过结构改进、种植方式优化等方式改善或利用好内部光环境;另一方面基于热环境规律,分类做好内部3个区的夏季灌溉等田间管理,从而推动光伏农业发展升级。

光伏驱动式PV/T集热系统设计与实验研究

近年来,太阳能发展广受关注,本文提出并设计一种光伏驱动式PV/T热水集热系统,结构上以吸热板拼接小型PV板,利用光伏板产生的电能驱动循环水泵带动系统自驱动运行。其全天温度分为快速上升期、近匀速上升期、高位波动期与下降期四个部分,系统全天平均电效率可维持在10%上下,且热效率达到39.9%,综合效率68%,全天水箱升温达到32°C。经计算,系统每年可以节约73.5kWh电能,相当于节约了29.4kg的标准煤消耗同时减少近20kg碳排放,节能效果显著。

矩形管道PV/T集热器在企业中应用的实验研究

设计并构建基于矩形集热管道的光伏光热系统,将该系统与工厂原有的余热回收系统相结合,扩大太阳能的应用领域,提高PV/T组件的热效率与电效率。利用COMSOL软件对PV/T组件温度场仿真分析,得到光伏板及集热管道温度的具体变化情况,并与实验结果相验证,实现热能与电能的协调控制。搭建1000块PV/T板,环境温度24℃左右时,每日可将100m3水池升温18.6℃,用于工厂冬季供暖和居民生活用水,该PV/T组件最大热效率为44.1%,每日发电量约为741KWh,用于提供余热回收系统在用电高峰时耗电,相当于每日共节约357.7kg标准煤。该系统兼具了节能和环保的作用,促进了企业可持续发展,充分体现了光伏光热系统在工业企业实施的可行性,为双碳目标的实现做出贡献。

光伏幕墙辅助双源热泵系统在不同地区的多目标优化配置

为克服单一可再生能源应用的局限性,提出一种光伏幕墙辅助双源热泵系统。利用TRNSYS建立仿真模型,以系统能耗和生命周期成本为目标函数,采用非支配排序遗传算法(NSGA-Ⅱ),对不同地区系统配置规模进行多目标优化设计,并利用加权和法确定均衡解。结果表明:哈尔滨、长春、沈阳3个地区优化后的系统运行能耗比优化前分别增加5.9%、5.0%和3.9%,生命周期成本降低13.6%、17.1%和12.9%;与单目标优化相比,多目标优化在兼顾性能的前提下能明显降低生命周期成本,具有明显的优势。