Multimodel Ensemble Forecast of Global Horizontal Irradiance at PV Power Stations Based on Dynamic Variable Weight

In the present study,multimodel ensemble forecast experiments of the global horizontal irradiance(GHI)were conducted using the dynamic variable weight technique.The study was based on the forecasts of four numerical models,namely,the China Meteorological Administration Wind Energy and Solar Energy Prediction System,the Mesoscale Weather Numerical Prediction System of China Meteorological Administration,the China Meteorological Administration Regional Mesoscale Numerical Prediction System-Guangdong,and the Weather Research and Forecasting Model-Solar,and observational data from four photovoltaic(PV)power stations in Yangjiang City,Guangdong Province.The results show that compared with those of the monthly optimal numerical model forecasts,the dynamic variable weight-based ensemble forecasts exhibited 0.97%-15.96%smaller values of the mean absolute error and 3.31%-18.40%lower values of the root mean square error(RMSE).However,the increase in the correlation coefficient was not obvious.Specifically,the multimodel ensemble mainly improved the performance of GHI forecasts below 700 W m^(-2),particularly below 400 W m^(-2),with RMSE reductions as high as 7.56%-28.28%.In contrast,the RMSE increased at GHI levels above 700 W m^(-2).As for the key period of PV power station output(02:00-07:00),the accuracy of GHI forecasts could be improved by the multimodel ensemble:the multimodel ensemble could effectively decrease the daily maximum absolute error(AE max)of GHI forecasts.Moreover,with increasing forecasting difficulty under cloudy conditions,the multimodel ensemble,which yields data closer to the actual observations,could simulate GHI fluctuations more accurately.

Short-term prediction of photovoltaic power generation based on LMD-EE-ESN with error correction

Considering the instability of the output power of photovoltaic(PV)generation system,to improve the power regulation ability of PV power during grid-connected operation,based on the quantitative analysis of meteorological conditions,a short-term prediction method of PV power based on LMD-EE-ESN with iterative error correction was proposed.Firstly,through the fuzzy clustering processing of meteorological conditions,taking the power curves of PV power generation in sunny,rainy or snowy,cloudy,and changeable weather as the reference,the local mean decomposition(LMD)was carried out respectively,and their energy entropy(EE)was taken as the meteorological characteristics.Then,the historical generation power series was decomposed by LMD algorithm,and the hierarchical prediction of the power curve was realized by echo state network(ESN)prediction algorithm combined with meteorological characteristics.Finally,the iterative error theory was applied to the correction of power prediction results.The analysis of the historical data in the PV power generation system shows that this method avoids the influence of meteorological conditions in the short-term prediction of PV output power,and improves the accuracy of power prediction on the condition of hierarchical prediction and iterative error correction.

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.

PSO-BP-Based Optimal Allocation Model for Complementary Generation Capacity of the Photovoltaic Power Station

To improve the operation efficiency of the photovoltaic power station complementary power generation system,an optimal allocation model of the photovoltaic power station complementary power generation capacity based on PSO-BP is proposed.Particle Swarm Optimization and BP neural network are used to establish the forecasting model,the Markov chain model is used to correct the forecasting error of the model,and the weighted fitting method is used to forecast the annual load curve,to complete the optimal allocation of complementary generating capacity of photovoltaic power stations.The experimental results show that thismethod reduces the average loss of photovoltaic output prediction,improves the prediction accuracy and recall rate of photovoltaic output prediction,and ensures the effective operation of the power system.

基于PVsyst软件模拟发电量数据的光伏电站电能损耗的分析方法研究

电能损耗是光伏电站非常重要的综合性指标,对其进行分析可以为光伏电站能效管理提供数据支持。在电能损耗的计算过程中,最大负荷损耗小时数的选取非常关键。提出了一种基于PVsyst软件模拟所得的发电量数据来分析光伏电站电能损耗的方法,结合工程实际情况给出了精确计算年最大负荷损耗小时数的改进算法数学模型,并对采用不同算法得到的年最大负荷损耗小时数进行了比较分析;以山西省大同市鸦儿崖乡100 MW光伏电站为算例,对其电气设备及线缆的电能损耗进行详细分析,验证了所提出光伏电站电能损耗分析方法的正确性。研究结果表明:1)由于光伏电站容配比的影响,应分别计算光伏电站直流侧和交流侧的年最大负荷损耗小时数,直流侧和交流侧的电能损耗也需要分别计算。2)该方法基于PVsyst软件模拟得到的光伏电站全年各小时的发电量数据,可准确计算出光伏电站的年最大负荷损耗小时数,在数学逻辑上合理,可以提高光伏电站电能损耗计算的准确度。该方法也可应用于其他实际运行的发电项目的电能损耗分析。

基于PVLIB的光伏组件串联数量计算条件及方法分析

为得到更为高效且合理的光伏组件串联数量的计算条件和计算方法,选取位于不同纬度、不同气候类型的119个拟定项目地点,基于PVLIB和NASA的气象数据获取119个拟定项目地点的20年逐小时气象数据,对采用不同计算条件时得到的光伏组件开路电压及其对应的光伏组件串联数量进行了分析。分析结果显示:基于200 W/m^(2)太阳辐照度及历史最低气温计算得到的光伏组件串联数量与基于多年逐时气象数据计算得到的光伏组件串联数量结果相近,且计算方法较为简便,不需要长序列逐时气象数据,可用于光伏电站设计中光伏组件串联数的计算条件。

基于PVsyst的单面与双面光伏组件最佳安装倾角对比

随着光伏发电技术不断进步,单面光伏组件与双面光伏组件的价差不断缩小。得益于发电量增益大,双面光伏组件在实际项目中受到愈来愈多的青睐。当光伏发电项目采用单面或双面光伏组件时,光伏组件的最佳安装倾角成为一个重要的考虑因素。选取了3个太阳能资源等级地区,利用PVsyst对在这3个地区建设的光伏电站分别采用单面和双面光伏组件时的安装倾角与光伏电站首年发电量及光伏组件正面接收的太阳辐照量之间的关系进行了仿真模拟。得到以下结论:1)以光伏电站首年发电量最大为衡量标准时,双面光伏组件的最佳安装倾角大于或等于有阴影遮挡的单面光伏组件的最佳安装倾角,但小于无阴影遮挡的单面光伏组件的最佳安装倾角。2)就单面光伏组件而言,无阴影遮挡条件下增加光伏组件安装倾角带来的发电量增益高于有阴影遮挡安装条件时。3)在无阴影遮挡情况下,在一定范围内增大单面光伏组件的安装倾角可以相应提升其发电量;相对于双面光伏组件,无阴影遮挡的单面光伏组件通过适当提高其安装倾角所获得的发电量增益较小,且增大安装倾角,光伏阵列之间的间距也需要相应增加,这会增大用地量,从而增加项目总成本。因此,在实际项目中,尽可能采用双面光伏组件是一个较为理想的选择。

基于PVsyst的倾角可调固定式光伏支架的调节次数及倾角偏差影响分析

以位于内蒙古自治区的采用倾角可调固定式光伏支架的某光伏电站为例,首先利用PVsyst软件对不同光伏支架倾角下的年发电量进行模拟,得到最佳倾角;然后对光伏支架倾角的浮动范围进行分析;最后针对倾角可调固定式光伏支架的调节时间及调节次数进行研究,并分析1年调节2次倾角时倾角偏差对发电量的影响。研究结果显示:1)相对于全年采用最佳倾角固定式光伏支架的光伏电站,光伏支架倾角年调节次数由2次增加到12次,光伏电站年发电量增益可由4.72%增至5.81%。2)光伏支架倾角调节次数与季节无直接相关性;相对于全年采用最佳倾角固定式光伏支架的光伏电站,随着光伏支架倾角调节次数的增加,光伏电站的年发电量增益逐渐增加,但增幅在逐渐减小。3)在确定光伏支架年调节次数时,需要综合考虑发电量的增益和需要投入的成本,选择2~4次较为合适。4)倾角可调固定式光伏支架1年调节2次倾角时,每次倾角可允许存在±5°的偏差范围,且综合考虑现场工况和调节精度等实际情况后,年理论发电量的最大损失率仅约为0.3%。以期研究结果可为光伏电站的光伏支架倾角设计方案比选、运维时的倾角调节优化及技术标准制定等工作提供参考。

基于PVsyst软件的光伏电站PR影响因素的灵敏度分析

随着全球光伏行业的蓬勃发展及高度竞争,优异的系统效率(PR)成为越来越多融资行和投资方决策项目可行性的先决条件,因此,有必要对光伏电站PR所关联的影响因素进行灵敏度分析。PVsyst是一款专业的光伏电站设计和仿真软件,用于指导光伏电站设计及发电量模拟计算。基于PVsyst软件,以沙特阿拉伯某座地面光伏电站为例,从光伏支架参数、光伏组件性能参数、电缆损耗、灰尘和污秽损失、不可利用率5个方面仿真分析了不同设计方案对光伏电站PR的影响,重点分析了不同影响因素对光伏电站PR的灵敏度,并有针对性的提出了可用于光伏电站设计的指导原则。研究结果表明:温度损耗系数、光伏组件功率偏差、光伏组件开路电压偏差和短路电流偏差、IAM测试方式、低压电缆损耗、灰尘和污秽损失,以及白天发电时间段停电这些因素对光伏电站PR的灵敏度均较高;光伏支架高度及其结构参数对光伏电站PR的灵敏度需要结合实际的项目边界条件进行分析。

光伏建筑一体化(BIPV)技术在综合能源服务站中的应用

分别分析了综合能源服务站风力发电和光伏发电的优缺点,简要介绍了光伏建筑一体化(BIPV)技术和该技术在某综合能源服务站的应用情况,从用电、安全环保以及运行效益方面对光伏建筑一体化(BIPV)技术在综合能源服务站的应用进行了分析,为综合能源服务站实现“双碳”目标提供了路径。

Equivalent Method of Integrated Power Generation System of Wind, Photovoltaic and Energy Storage in Power Flow Calculation and Transient Simulation

针对工程实际开展风光储联合发电系统在潮流计算和机电暂态仿真中的等值方法研究，旨在为大容量风光储联合发电系统的并网仿真分析奠定基础。将潮流计算的等值分为单元机组和集电系统2部分来研究。单元机组等值采用根据不同控制模式选取不同节点类型的方法，针对集电系统等值提出基于损耗不变原则的方法。等值模型和详细模型的算例结果表明，潮流计算等值方法具有较好的精度。在机电暂态仿真动态等值中，基于实际工程计算的最严重工况分析原则，提出运行在满出力点的单机“倍乘”等值模型，为工程计算中的风光储联合发电系统动态等值提供了一种解决方案。

Solar Energy Resource Characteristics of Photovoltaic Power Station in Shandong Province

[Objective] The aim was to analyze characters of solar energy in photo- voltaic power stations in Shandong Province. [Method] The models of total solar radiation and scattered radiation were determined, and solar energy resources in pho-tovoltaic power stations were evaluated based on illumination in horizontal plane and cloud data in 123 counties or cities and observed information in Jinan, Fushan and Juxian in 1988-2008. [Result] Solar energy in northern regions in Shandong proved most abundant, which is suitable for photovoltaic power generation; the optimal angle of tilt of photovoltaic array was at 35°, decreasing by 2°-3° compared with local latitude. Total solar radiation received by the slope with optimal angle of tilt exceeded 1 600 kw.h/（m2.a）, increasing by 16% compared with horizontal planes. The maximal irradiance concluded by WRF in different regions tended to be volatile in 1 020-1 060 W/m2. [Conclusion] The research provides references for construction of photovoltaic power stations in Shandong Province.

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。

Comparative assessment of maximum power point tracking procedures for photovoltaic systems

The fast growing demands and increasing awareness for the environment, PV systems are being rapidly installed for numerous applications.However, one of the important challenges in utilizing a PV source is the maximum power harnessing using various maximum power point tracking techniques available. With the large number of MPPT techniques, each having some merits and demerits, confusion is always there for their proper selection. Discussion on various proposed procedures for maximum power point tracking of photovoltaic array has been done. Based on different parameters analysis of MPPT techniques is carried out. This assessment will serve as a suitable reference for selection, understanding different ways and means of MPPT.

A PV powered shunt active power filter for power quality improvement

This paper deals with power quality improvement using a three-phase active power filter(APF) connected to a PV power system. A direct power control(DPC) approach is proposed to eliminate harmonic current caused by any nonlinear loads and at the same time guarantees the delivery of a part of the load request from the same PV source. A boost converter is used for maximum power point(MPP) tracking purposes under various climate conditions through a fuzzy logic technique. The suggested study is tested under a MATLAB/Simulink environment. The obtained results depict the efficacy of the proposed procedures to meet the IEEE 519-1992 standard recommendation on harmonic levels.

Overview of Maximum Power Point Tracking Control Methods for PV Systems

Maximum power point tracking (MPPT) controllers play an important role in photovoltaic systems. They maximize the output power of a PV array for a given set of conditions. This paper presents an overview of the different MPPT techniques. Each technique is evaluated on its ability to detect multiple maxima, convergence speed, ease of implementation, efficiency over a wide output power range, and cost of implementation. The perturbation and observation (P & O), and incremental conductance (IC) algorithms are widely used techniques, with many variants and optimization techniques reported. For this reason, this paper evaluates the performance of these two common approaches from a dynamic and steady state perspective.

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。

Research and practice of designing hydro/ photovoltaic hybrid power system in microgrid

Small-hydro power station is often used in remote areas beside a river,but it doesn't match electricity demand so well,especially in dry seasons. A photovoltaic (PV) system with battery is a suitable option to complement the electricity gap. In this paper,a new structure of megawatt-class PV system integrating battery at DC-bus (DC: direct current) is proposed to be used in hydro/PV hybrid power system,and 4 main designing considerations and several key equipments are discussed. In 2011,a 2 MWp PV station with the proposed structure was built up in Yushu,China. From stability analysis,the station shows a strong stability under load cut-in/off and solar irradiance's fluctuation.

Maximum Power Point Tracking Control Using Neural Networks for Stand-Alone Photovoltaic Systems

The employment of maximum power point tracking techniques in the photovoltaic power systems is well known and even of immense importance. There are various techniques to track the maximum power point reported in several literatures. In such context, there is an increasing interest in developing a more appropriate and effective maximum power point tracking control methodology to ensure that the photovoltaic arrays guarantee as much of their available output power as possible to the load for any temperature and solar radiation levels. In this paper, theoretical details of the work, carried out to develop and implement a maximum power point tracking controller using neural networks for a stand-alone photovoltaic system, are presented. Attention has been also paid to the command of the power converter to achieve maximum power point tracking. Simulations results, using Matlab/Simulink software, presented for this approach under rapid variation of insolation and temperature conditions, confirm the effectiveness of the proposed method both in terms of efficiency and fast response time. Negligible oscillations around the maximum power point and easy implementation are the main advantages of the proposed maximum power point tracking (MPPT) control method.