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.

Comparative Study of Solar PV Power Plant Dimensionnement Connected to Network Based on Monofacial and Bifacial Modules

This article presents the results of comparative study of two PV solar modules technologies,namely monofacial and bifacial.This study main objective is to identify conditions and parameters that make it possible to obtain better energy and economic efficiency from one or other of two technologies.The study reason lies in revival observed on bifacial module in recent years where all the major manufacturers of PV solar panels are developing them where in a few years,this technology risks being at the same price as the monofacial solar panel with better efficiency.Economic indicator used is energy levelized cost(LCOE)which is function technology type,energy productivity,annual investment and operation cost.To achieve this,a 3.685 MWc solar PV power plant was dimensioned and simulated under Matlab for a 3.5 ha site with a 2,320,740,602 FCFA budget for monofacial installation,against 1,925,188,640 FCFA for 2.73 MWc bifacial installation.The LCOE comparative analysis of two technologies calculated over a period of 25 years,showed that plant with bifacial panels is more beneficial if bifacial gain is greater than 9%.It has further been found that it is possible to gain up to 40%of invested cost if bifacial gain reaches 45%.Finally,a loss of about 10%of invested cost could be recorded if bifacial gain is less than 9%.

Research on energy storage capacity configuration for PV power plants using uncertainty analysis and its applications

Compensating for photovoltaic(PV)power forecast errors is an important function of energy storage systems.As PV power outputs have strong random fluctuations and uncertainty,it is difficult to satisfy the grid-connection requirements using fixed energy storage capacity configuration methods.In this paper,a method of configuring energy storage capacity is proposed based on the uncertainty of PV power generation.A k-means clustering algorithm is used to classify weather types based on differences in solar irradiance.The power forecast errors in different weather types are analyzed,and an energy storage system is used to compensate for the errors.The kernel density estimation is used to fit the distributions of the daily maximum power and maximum capacity requirements of the energy storage system;the power and capacity of the energy storage unit are calculated at different confidence levels.The optimized energy storage configuration of a PV plant is presented according to the calculated degrees of power and capacity satisfaction.The proposed method was validated using actual operating data from a PV power station.The results indicated that the required energy storage can be significantly reduced while compensating for power forecast errors.

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.

Investigation on Grid Connections of Wind Power and PV Power in China

In order to fully comprehend the developing status of wind power and photovoltaic (PV) power generation, a special investigation on the integration of wind power and PV power was launched by the agencies of the State Electricity Regulatory Commission (SERC) throughout China during July-October 2010. This report is completed based on the investigation along with routine supervisory and management programs. There are totally 573 wind power projects and 94 PV power projects involved. Existing problems in these projects are pointed out and proposals for regulation are put forward.

Analysis of the Performance Indicators of the PV Power System

The energy assessment of the PV power systems is carried out by using different types of performance indicators that benchmark the output of these systems against the PV panel maximum output at hypothetical operation conditions. In this paper, a comparative analysis of six types of performance indicators is conducted and a new performance indicator which considers PV panel slope and orientation is proposed. The proposed indicator is benchmarking the PV system actual output against the maximum output of the same system if it would operate in two axis tracking mode. The proposed performance indicator is used to develop a friendly user calculator of PV system output that can be used by, energy providers and PV system installers to evaluate the output of the PV grid connect network. The advantage of the developed calculator is high-lighted by a case study that estimates energy capacity of different residential rooftop PV systems installed in a residential suburb in Sydney.

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.

PV Power Forecasting Using an Integrated GA-PSO-ANFIS Approach and Gaussian Process Regression Based Feature Selection Strategy

This paper presents a hybrid approach for the forecasting of electricity production in microgrids with solar photovoltaic(PV)installations.An accurate PV power generation forecasting tool essentially addresses the issues resulting from the intermittent and uncertain nature of solar power to ensure efficient and reliable system operation.A day-ahead,hourly mean PV power generation forecasting method based on a combination of genetic algorithm(GA),particle swarm optimization(PSO)and adaptive neuro-fuzzy inference systems(ANFIS)is presented in this study.Binary GA with Gaussian process regression model based fitness function is used to determine important input parameters that significantly influence the amount of output power of a PV generation plant;and an integrated hybrid algorithm combining GA and PSO is used to optimize an ANFIS based PV power forecasting model for the plant.The proposed modeling technique is tested based on power generation data obtained from Goldwind microgrid system found in Beijing.Forecasting results demonstrate the superior performance of the proposed method as compared with commonly used forecasting approaches.The proposed approach outperformed existing artificial neural network(ANN),linear regression(LR),and persistence based forecasting models,validating its effectiveness.

Model predictive control of grid-connected PV power generation system considering optimal MPPT control of PV modules

Because of system constraints caused by the external environment and grid faults,the conventional maximum power point tracking(MPPT)and inverter control methods of a PV power generation system cannot achieve optimal power output.They can also lead to misjudgments and poor dynamic performance.To address these issues,this paper proposes a new MPPT method of PV modules based on model predictive control(MPC)and a finite control set model predictive current control(FCS-MPCC)of an inverter.Using the identification model of PV arrays,the module-based MPC controller is designed,and maximum output power is achieved by coordinating the optimal combination of spectral wavelength and module temperature.An FCS-MPCC algorithm is then designed to predict the inverter current under different voltage vectors,the optimal voltage vector is selected according to the optimal value function,and the corresponding optimal switching state is applied to power semiconductor devices of the inverter.The MPPT performance of the MPC controller and the responses of the inverter under different constraints are verified,and the steady-state and dynamic control effects of the inverter using FCS-MPCC are compared with the traditional feedforward decoupling PI control in Matlab/Simulink.The results show that MPC has better tracking performance under constraints,and the system has faster and more accurate dynamic response and flexibility than conventional PI control.

Calculation Method and Analysis for the Annual Power Generation of PV Faades in China

The application of PV facades emerges greatly in recent years and however its calculation methods and analysis remains insufficient under the weather conditions of China. In such demand, this paper investigates PV facade in terms of PV electricity generation in different arrangements and weather conditions of four major cities in China. The calculation models for PV facade are developed and validated by comparing the results with the measured data from the field experiments. A parametric study is carried out to provide a reference for the optimal design of the PV facades. The results show that with various cities, building orientations, building forms, materials and arrangements of PV modules, there is a distinct difference in the electrical output energy of PV facades. Weather conditions nlav a very important role in terms of PV generation nerformance of PV facades.

Exploring the merits of geographical diversification of solar PV power plants for a resilient PV-dominated electricity grid in India

India is highly dependent on solar photovoltaics(PV)to harness its vast solar resource potential and combat climate change.However,∼90%of the installed PV capacity in India is concentrated in the top nine states,with the remaining states lagging behind.The research reveals that during monsoons,heavy cloud cover and rain lead to high solar resource variability,intermittency and the risk of very low PV generation,which can result in reliability issues in future PV-dominated electricity grids.Although energy storage can help in overcoming high intermittency,there are multiple challenges associated with it.The novelty of this study lies in demonstrating the benefits of combining multiple PV sites in various regions to mitigate the risks of low PV generation and high variability.The variability of individual sites was found to be up to∼3.5 times higher than the variability of combined generation.During noon,prominent solar park sites like Bhadla and NP Kunta experience a decrease in power generation to values as low as∼10%of the rated PV capacity.However,the minimum generation of the large-scale dispersed PV generation is>30%.Furthermore,the research identifies other benefits of dispersing PV generation across the country,viz.,reduction of seasonal variability by adding PV capacity in the southern region,widening of the PV generation span,more room for PV capacity addition,reduction in storage and ramping needs,utilization of hydroelectric potential of the north-east and PV potential of Ladakh,and creating opportunities for sustainable development in rural agrarian regions through agrivoltaics.

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.

“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。

Power System Harmonics Study for Unbalanced Microgrid System with PV Sources and Nonlinear Loads

Harmonics distortion is a crucial problem in microgrid. Harmonic sources can be categorized as two main factors: renewable energy integration and nonlinear loads. Both factors are investigated in this paper. For renewbale energy, photovoltaic (PV) power is one of the most effective solutions for energy crisis and it is showing great potential for serving customers in microgrid. A three- phase PV source model is establised and integrated at different locations in order to observe the impact of harmonics on a microgrid and power quality (PQ). A composite load is modeled using Crossed Frequency Admittance Matrix theory. A practicdal microgrid loacated at GA, USA is used as a study system. The microgrid, PV model and nonlinear load model are simulated in MATLAB/ Simulink environment. The results show the impact of installing PV sources at two types of locations considering linear and composite nonlinear loads. In addition, three PQ indices are discussed to show the numerical impacts with various perspectives.

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。

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。

BIPV模式在工业厂房屋顶的应用研究

中国大力推进分布式光伏发电的同时,存在许多工业厂房屋顶无法满足光伏发电系统安装条件的问题,这极大制约了光伏发电技术的推广。由于传统的光伏发电系统是直接附着在建筑物屋顶,即采用的是BAPV模式,这会导致因需增加建筑物的承载力而增加建设成本的情况出现,从而制约了分布式光伏发电的应用,而将光伏发电系统与建筑集成的光伏建筑一体化(BIPV)模式可有效解决此类问题。针对BIPV模式和BAPV模式对工业厂房钢结构的影响进行了研究,并根据实际案例对这两种模式下的光伏发电系统建设、维护成本进行了分析。研究结果表明:1)BIPV模式相较于BAPV模式可以减少工业厂房钢结构屋顶恒荷载,对于轻微超限的项目可以省去加固成本,对于超限明显的项目可以减少加固成本。2)在同等建设条件下,BIPV模式相较于BAPV模式可以减少屋顶建设成本;并且从中长期来看,相较于BAPV模式,BIPV模式平均1万m^(2)的厂房可以减少126万建设维护成本。

Maximum Power Point Tracking Using the Incremental Conductance Algorithm for PV Systems Operating in Rapidly Changing Environmental Conditions

Maximum Power Point Tracking (MPPT) is an important process in Photovoltaic (PV) systems because of the need to extract maximum power from PV panels used in these systems. Without the ability to track and have PV panels operate at its maximum power point (MPP) entails power losses;resulting in high cost since more panels will be required to provide specified energy needs. To achieve high efficiency and low cost, MPPT has therefore become an imperative in PV systems. In this study, an MPP tracker is modeled using the IC algorithm and its behavior under rapidly changing environmental conditions of temperature and irradiation levels is investigated. This algorithm, based on knowledge of the variation of the conductance of PV cells and the operating point with respect to the voltage and current of the panel calculates the slope of the power characteristics to determine the MPP as the peak of the curve. A simple circuit model of the DC-DC boost converter connected to a PV panel is used in the simulation;and the output of the boost converter is fed through a 3-phase inverter to an electricity grid. The model was simulated and tested using MATLAB/Simulink. Simulation results show the effectiveness of the IC algorithm for tracking the MPP in PV systems operating under rapidly changing temperatures and irradiations with a settling time of 2 seconds.

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.

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。