Managing New PV Plant Connection to Available Grids to Stay within Standard Limits with a Case Study

PV plants are increasing all over the world and they are becoming a distinct part of electric grids.Due to abundance of solar irradiation and almost constant amount of it in certain geographical latitudes,selection of proper capacity of PV plants depends mostly on available places for the site.In this paper,important measures for safe connection of a PV plant in terms of voltage requirements are addressed and several guidelines are introduced for this purpose.In addition,simulation results are included to prove some of the mentioned suggestions.A general algorithm is fi nally proposed to show the directions for safe connection of PV plants.

Inter-Row Spacing of PV Power Plant

When designing a solar power plant, it is much more important to avoid the shadow on the PV Panels. As the shadow falls on the PV Panels;it significantly reduces the generation of required power as planned and designed. This research paper and case study will help a lot to avoid shadow, especially when selecting inter-row spacing between the strings of solar power plants.

Hybrid Network Model Based on Data Enhancement for Short-term Power Prediction of New PV Plants

This study proposes a hybrid network model based on data enhancement to address the problem of low accuracy in photovoltaic(PV)power prediction that arises due to insuffi cient data samples for new PV plants.First,a time-series gener ative adversarial network(TimeGAN)is used to learn the distri bution law of the original PV data samples and the temporal correlations between their features,and these are then used to generate new samples to enhance the training set.Subsequently,a hybrid network model that fuses bi-directional long-short term memory(BiLSTM)network with attention mechanism(AM)in the framework of deep&cross network(DCN)is con structed to effectively extract deep information from the origi nal features while enhancing the impact of important informa tion on the prediction results.Finally,the hyperparameters in the hybrid network model are optimized using the whale optimi zation algorithm(WOA),which prevents the network model from falling into a local optimum and gives the best prediction results.The simulation results show that after data enhance ment by TimeGAN,the hybrid prediction model proposed in this paper can effectively improve the accuracy of short-term PV power prediction and has wide applicability.

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%.

Stability Study of Low Voltage Electrical Distribution Network: Audit and Improvement of DJEGBE Mini Solar Photovoltaic Power Plant in the Commune of OUESSE (Benin)

The supply of quality energy is a major concern for distribution network managers. This is the case for the company ASEMI, whose subscribers on the DJEGBE mini-power station network are faced with problems of current instability, voltage drops, and repetitive outages. This work is part of the search for the stability of the electrical distribution network by focusing on the audit of the DJEGBE mini photovoltaic solar power plant electrical network in the commune of OUESSE (Benin). This aims to highlight malfunctions on the low-voltage network to propose solutions for improving current stability among subscribers. Irregularities were noted, notably the overloading of certain lines of the PV network, implying poor distribution of loads by phase, which is the main cause of voltage drops;repetitive outages linked to overvoltage caused by lightning and overcurrent due to overload;faulty meters, absence of earth connection at subscribers. Peaks in consumption were obtained at night, which shows that consumption is greater in the evening. We examined the existing situation and processed the data collected, then simulated the energy consumption profiles with the network analyzer “LANGLOIS 6830” and “Excel”. The power factor value recorded is an average of 1, and the minimum value is 0.85. The daily output is 131.08 kWh, for a daily demand of 120 kWh and the average daily consumption is 109.92 kWh, or 83.86% of the energy produced per day. These results showed that the dysfunctions are linked to the distribution and the use of produced energy. Finally, we proposed possible solutions for improving the electrical distribution network. Thus, measures without investment and those requiring investment have been proposed.

Modelling and Optimization of Hydroelectric Power Plants in Cameroon for the Development of the Green Energy Market in Neighboring Countries Using Homer Software

Renewable energy is increasingly in demand for a variety of applications in both urban and rural areas. There are, however, a number of implementation constraints in some countries, even though sunshine, wind and water are abundant and available. As part of this research, we are carrying out a technical and economic study on the availability of renewable energy in Cameroon, with a view to combining several sources of solar, biomass, wind and hydroelectric power to meet energy demand both inside and outside the country, in countries such as Chad, Gabon and Nigeria. In this work, the implementation of the entire system in the HOMER software demonstrates the feasibility and possibility of implementing a multi-source power plant based on renewable energies. Calculation of the levelized cost of energy (LCOE) and the net present cost (NPC) shows that a capacity of 485 GW can meet the energy demand of the countries bordering Cameroon. Furthermore, the calculation of the performance ratio gives a PR = 46.52 and a Capacity factor of CF = 11.64. The system is profitable not only economically but also environmentally, as it reduces greenhouse gas emissions and energy losses.

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。

A Techno-Economical Characterization of Solar PV Power Generation in Rwanda:The Role of Subsidies and Incentives

Standalone Solar PV systems have been vital in the improvement of access to energy in many countries.However,given the large cost of solar PV plants’components,in developing countries,there is a dear need for such components to be subsidised and incentivised for the consumers to afford the produced energy.Moreover,there is a need for optimal sizing of the solar PV plants taking into account the solar information,energy requirement for various activities,and economic conditions in the off-grid regions in Rwanda.This study aims to develop optimally sized solar PV plants suited to rural communities in Rwanda.Likewise,it aims at characterizing the impacts of subsidies and incentives on the profitability and affordability of solar PV plants’energy in Rwanda.In the study,we have developed a model on basis of which the plant power(peak power)and costs of energy can be predicted given the load requirements using PVSyst.The model was validated using data corrected at eight different sites.Our generalized predictive model’s results matched the results obtained using field measurement data as inputs.The models have been able to replicate with a by degree of accuracy the peak powers and the plants’costs for different loads and were used to evaluate the economic viability of solar PV plants in Rwanda.It was found that with incentives and subsidies of 20%,the solar PV systems’costs,the Levelised Cost of Energy would drop from a maximum of 0.098 Euro to a minimum of 0.072 Euro,the payback period was reduced from a maximum of 7.5 years to a minimum of 6.0 years while the return on investments was seen to vary between 425.72 and 615.32 per cent over the plants’lifetime of 25 years.Overall our findings underscore the importance of government subsidies and incentives for solar PV energy generation projects to be significantly profitable.

Functional identification of phenazine biosynthesis genes in plant pathogenic bacteria Pseudomonas syringae pv. tomato and Xanthomonas oryzae pv. oryzae

Phenazines are secondary metabolites with broad spectrum antibiotic activity and thus show high potential in biological control of pathogens. In this study, we identified phenazine biosynthesis （phz） genes in two genome-completed plant pathogenic bacteria Pseudomonas syringae pv. tomato （Pst） DC3000 and Xanthomonas oryzae pv. oryzae （Xoo） PXO99A. Unlike the phz genes in typical phenazine-producing pseudomonads, phz homologs in Pst DC3000 and Xoo PXO99A consisted of phzC/D/E/F/G and phzC/E1/E2/F/G, respectively, and the both were not organized into an operon. Detection experiments demonstrated that phenazine-l-carboxylic acid （PCA） of Pst DC3000 accumulated to 13.4 IJg L-1, while that of Xoo PXO99A was almost undetectable. Moreover, Pst DC3000 was resistant to 1 mg mL-1 PCA, while Xoo PXO99A was sensitive to 50 IJg mL ~ PCA. Furthermore, mutation of phzF blocked the PCA production and significantly reduced the pathogenicity of Pst DC3000 in tomato, while the complementary strains restored these phenotypes. These results revealed that Pst DC3000 produces low level of and is resistant to phenazines and thus is unable to be biologically controlled by phenazines. Additionally, phz-mediated PCA production is required for full pathogenicity of Pst DC3000. To our knowledge, this is the first report of PCA production and its function in pathogenicity of a plant pathogenic P. syringae strain.

基于功率信号分析的光伏电站故障诊断方法

为提高光伏电站故障诊断精度,提出一种基于功率信号分析的光伏电站故障诊断方法。首先,用卷积神经网络结合长短记忆CNN-LSTM(convolutional neural networks-long short-term memory)模型和岭回归模型对历史发电的时序信息进行充分挖掘,再依据实际与预测发电功率之间的动态时间规整DTW(dynamic time warping)距离进行电站故障检测;其次,提出一个基于实际发电功率频域特征的故障分类指标,建立分类规则库,将电站故障分为通信故障、设备故障、限电故障,结合故障影响等效发电小时数评估电站故障程度;最后,通过算例分析验证了该算法的有效性。

PV Power Short-Term Forecasting Model Based on the Data Gathered from Monitoring Network

The degree of accuracy in predicting the photovoltaic power generation plays an important role in appropriate allocations and economic operations of the power plants based on the generating capacity data gathered from the geographically separated photovoltaic plants through network. In this paper, a forecasting model is designed with an optimization algorithm which is developed with the combination of PSO （Particle Swarm Optimization） and BP （Back Propagation） neural network. The proposed model is further validated and the experiment results show that the predication model assures the prediction accuracy regardless the day type transitions and other relevant factors, in the proposed model, the prediction error rate is worth less than 20% in all different climatic conditions and most of the prediction error accuracy is less than 10% in sunny day, and whose precision satisfies the management requirements of the power grid companies, reflecting the significance of the proposed model in engineering applications.

应用PV技术对7种针阔叶幼树抗旱性的研究

为进一步探讨PV(Pressure-Volume)技术在树木抗旱性研究中的应用前景,比较成、幼龄树木的抗旱性差别,在对樟子松等7种成龄树木抗旱性生理指标研究的基础上,对其幼树的抗旱性进行了研究。结果表明,对成、幼龄树木一年生小枝用PV曲线所测得的诸水分状况参数随年生长发育进程的的变化规律是一致的;用嫩枝生长初期和枝条完全木质化时期两个阶段的水分参数比较树木的抗旱性、具有较大的可靠性和实用性;幼树在嫩枝生长初期的抗旱性较成树弱,当新枝完全木质化之后,二者的抗旱性基本相近。

多能互补发电系统故障识别与测距方法

随着大量新能源的接入,使得多端柔性直流系统(modular multilevel converter based multi-terminal direct current, MMC-MTDC)故障特征愈加复杂,快速准确的故障识别与测距是亟需解决的关键难题之一。为此,提出了一种风-光-储-蓄互补发电站经柔性直流输电外送系统故障识别与测距方法。首先,搭建风-光-储-蓄互补发电站经柔直外送系统,在此基础上,提出了一种Teager能量算子能量熵的新方法,利用测量点正负极Teager能量算子能量熵的比值构建故障选极及区段识别判据。接着,针对已识别的故障线路,提出变分模态分解(variational mode decomposition, VMD)与Teager能量算子(teager energy operator, TEO)相结合的故障测距方法。最后,利用PSCAD/EMTDC进行仿真,结果表明所提识别方法可以准确判断故障所在线路,所提测距方法能在故障发生2 ms时间窗内实现故障测距,误差率不超过2.55%,并具有较高的耐过渡电阻能力。

内陆水面漂浮式光伏开发分析与可行技术方案

光伏作为我国目前最重要的新能源发电形式之一,对实现我国双碳战略目标有着重要的作用。基于开发水库、内陆水面漂浮式光伏电站的各类影响因素及政策导向,分析了未来开发内陆水面漂浮式光伏电站,形成水光互补发电格局的挑战与前景。对漂浮式光伏电站的技术方案进行了调查、研究与初步设计,形成了可供参考的内陆漂浮式光伏开发初步方案。

跟踪支架光伏电站场平优化研究

基于预选址开发的阿布扎比光伏电站项目,通过对该场地地形的分析,以该场地的土方平整设计及优化过程为启发,对比国内传统土方优化设计方法,提出1种场地平整优化的新方法。该方法可明显减少场地平整土方工程量,节约建设成本。

旭升光伏电站光伏储能与光伏电站负荷预测研究

针对光伏储能和光伏电站负荷存在明显的随机性和间歇性问题,分别提出了基于长短期记忆神经网络的光伏发电预测模型和基于BP神经网络的电站负荷预测模型。在光伏发电预测模型中,采用皮尔逊相关系数分析光伏发电功率的影响因素,并将相关性较高的因素作为长短期记忆神经网络模型的输入变量,然后通过K-means聚类分析将数据分为4种季节类型,处理后的数据集放入预测模型中进行训练。在光伏电站负荷预测模型中,将处理后的历史负荷数据输入基于时间序列的BP神经网络进行迭代训练,同时对模型的权值和阈值进行自适应优化。最后,验证了所提出的预测模型具有极高的预测精度以及该光伏电站负荷预测模型较PSO-BP、GA-BP神经网络具有更高的精度和稳定性。

光伏-光热-风冷热泵式供能植物工厂空调系统设计

针对目前植物工厂供能方式单一、盈利性与可持续性差等问题,文章设计了太阳能光伏-光热-风冷热泵联合供能的植物工厂空调系统。该系统采用风冷热泵为植物工厂提供冷量,太阳能集热为植物工厂提供热量以及太阳能光伏供部分植物工厂的用电。通过确定植物工厂的冷热负荷,选型制热量和制冷量分别为8.5 kW和7.2 kW的风冷热泵,通过计算集热器的集热面积确定光伏光热一体化组件的数量,确定了光伏光热一体化组件的发电量及光伏能够提供的植物工厂电耗百分比,最后分析了配置光伏光热一体化组件的植物工厂投资经济性与碳减排潜力。

Low Voltage Ride through Control Capability of a Large Grid Connected PV System Combining DC Chopper and Current Limiting Techniques

This paper presents the development and performance capability of a comprehensive Low voltage ride through (LVRT) control scheme that makes use of both the DC chopper and the current limiting based on the required reactive power during fault time. The study is conducted on an 8.5 MW single stage PV power plant (PVPP) connected to the Rwandan grid. In the event of fault disturbance, this control scheme helps to overcome the problems of excessive DC-link voltage by fast activation of the DC chopper operation. At the same instance, AC current is limited to the maximum rating of the inverter as a function of the injected reactive current. This helps overcome AC-over- current that may possibly lead to damage or disconnection of the inverter. The control scheme also ensures voltage support and power balance through the injection of reactive current as per grid code requirements. Selected simulations using MATLAB are carried out in the events of different kinds of fault caused voltage dips. Results demonstrate the effectiveness of the proposed LVRT control scheme.

PV-green Roofs植被层高度对系统性能影响

绿化屋顶(GR)和光伏发电系统(PV)在调节室内热湿环境与降低建筑能耗中发挥着重要作用,利用两系统互效性耦合而成的光伏-绿化屋顶(PV-green Roofs)是推进建筑节能的创新型举措。结合PV-green Roofs数学模型,分析植物高度对系统性能的影响,通过实验测定,以落地生根和佛甲草为绿化屋顶植被层材料,实测不同工况下PV-green Roofs系统的电量输出值,同时结合EnergyPlus数值模拟结果分析采用不同植株高度的PV-green Roofs系统对建筑消耗净能量的影响。结果表明:植物高度通过改变绿化屋顶种植层蒸发阻力和植被层冠状层风速影响系统性能;在夏热冬冷的气候条件下,植物生命中期对应的高度对光伏系统工作环境的冷却效果最为明显,引起输出电量的增值最大,且环境湿度对系统性能存在影响。

Economic Performance Optimization of a PV-BESS Power Generator: A Case Study La Reunion Island

This paper proposes an economic performance optimization strategy for a PV plant coupled with a battery energy storage system. The case study of La Reunion Island, a non-interconnected zone (NIZ) with a high level of renewable energy sources (RES), is considered. This last decade, to reach the ambitious target of electricity autonomy by 2030 set by the local authorities, local and national plans have been launched to promote renewable energy sources integration that led to a noticeable development of photovoltaic (PV) systems. To avoid a decrease of the grid reliability due to a large integration of intermittent energy sources into a non-interconnected grid, the authorities have introduced new regulatory rules for RES producers. The proposed optimization strategy relies on these new regulatory rules and takes into account the energy market data, the amount of PV production subject to penalties for imbalance, the batteries and the PV technological characteristics together with a PV production forecast model. Due to its high convergence rate to the true global minimum and its perfect suitability to practical engineering optimization problems, the recently developed Modified Cuckoo Search algorithm is used as optimization algorithm. The effectiveness and relevance of the proposed strategy are assessed on experimental data collected on a real PV power plant. An economical analysis demonstrates that the proposed optimization strategy is able to fulfill the new regulatory rules requirements while increasing the economic performance of the system.