Neural network based estimation of maximum power generation from PVmodule using environmental information

This paper presents an application of an artificial neural network for the estimation of maximum power generation from PV module. The output power from a PV module depends on environmental factors such as irradiation and cell temperature. For the operation planning of power systems, the prediction of the power generation is inevitable for PV systems. For this purpose, irradiation, temperature and wind velocity are utilized as the input information to the proposed neural network. The output is the predicted maximum power generation under the condition given by those environmental factors. The efficiency of the proposed estimation scheme is evaluated by using actual data on daily, monthly and yearly bases. The proposed method gives highly accurate predictions compared with predictions using the conventional multiple regression model     

Remote PV-system monitored via satellite

A majority of autonomous PV systems are used to supply electricity in regions with no grid, no telephone coverage, and limited accessibility. Commonly, systems in such regions are supervised by visits in conjunction with a data logger. Over the lifetime of a PV-system costs for supervision often exceed the cost of the system itself. Response time for failures is very poor. To overcome these disadvantages a data satellite transmission system was set up. From the PV system site the most relevant data—such as irradiance, PV generation, state of the battery and load—is collected and sent to the ARGOS-SCD satellite. The satellite data is transferred from the receiving ground station to the Internet, providing worldwide access via WWW. The advantages are manifold: sponsors (NGOs, foundations, public, etc.) have an immediate access to the projects, manufacturers can use the data to improve products, and the online monitoring system enables more public interest in the PV area.     

Calculating the shading reduction coefficient of photovoltaic system efficiency using the anisotropic sky scattering model

The front-row shading reduction coefficient is a key parameter used to calculate the system efficiency of a photovoltaic (PV) power station. Based on the Hay anisotropic sky scattering model, the variation rule of solar radiation intensity on the surface of the PV array during the shaded period is simulated, combined with the voltage–current characteristics of the PV modules, and the shadow occlusion operating mode of the PV array is modeled. A method for calculating the loss coefficient of front shadow occlusion based on the division of the PV cell string unit and Hay anisotropic sky scattering model is proposed. This algorithm can accurately evaluate the degree of influence of the PV array layout, wiring mode, array spacing, PV module specifications, and solar radiation on PV power station system efficiency. It provides a basis for optimizing the PV array layout, reducing system loss, and improving PV system efficiency.     

SolarPV 3D在光电建筑中光伏发电系统设计时的应用研究

自主开发了一款基于SketchUp软件的三维数字化设计插件SolarPV 3D,并对该插件的主要算法进行了介绍,算法包括光伏阵列自动化布置算法和逐时阴影遮挡计算方法,解决了光伏发电系统数字化设计过程中的关键技术难题,并提高了其设计效率。以河海大学常州校区英才楼的屋面光伏发电系统布置为例,结合无人机拍照三维成像技术及SolarPV 3D,完成了屋面光伏发电系统的布置及系统性能的仿真。SolarPV 3D使光伏发电系统设计的三维可视化程度得到明显提升,此外其还可提供光伏发电系统的性能数据,从而提高了光伏发电系统设计的经济性和实用性,具有重要的工程应用价值。     

Modeling snow melting on heated pavement surfaces. Part II: Experimental validation

This paper describes an experimental validation exercise for a newly developed numerical model of the snow melting process on heated pavement surfaces. The model is able to predict the conditions of the snow, ice and water during the snow melting process on hydronically-heated pavements given time-varying weather and heating system boundary conditions. Validation results show that the model satisfactorily predicts the surface temperature and conditions, the degree of snow cover over the heated surface, and outlet fluid temperature given the weather data, inlet fluid temperature, and the fluid mass flow rate. It can therefore be used to analyze the performance of hydronic snow melting systems and can be used in the system design process. Development of the model is described in a companion paper.     

温度对屋顶分布式光伏系统发电效率的影响分析

提高发电效率是光伏模块进一步大规模应用的关键。温度是影响光伏模块发电效率的重要因素之一,尤其对屋顶分布式光伏系统而言。基于某屋顶分布式光伏电站运行数据,分析了温度对光伏模块发电效率的影响。通过建立多元线性回归模型探讨了环境温度与电池板发电效率的关系,并提出了一种拟合度较高的理论发电量计算模型。该模型可用于计算电站的应发电量和相应的损失发电量,以便综合考虑收益与成本,判断是否采取适当的降温措施。     

Climate change impacts on techno-economic performance of roof PV solar system in Australia

The techno-economic performance of roof PV solar system depends on local climatic conditions. The energy conversion behavior of PV system will change as a result of the new solar irradiation data caused by climate change. This study aims to investigate the quantified impacts of climate change on the future performance of PV roof system with a general electricity load and legal maximum size of solar array. In this study, the morphing method is employed to predict the future hourly mean global solar irradiation data for the year 2030, 2050 and 2070. By using the current and future solar irradiation data as the inputs, a simulation model of PV system is built to simulate the long-term implementation of the systems in the capital cities of Australian states. The solutions of the model given by computer programme, includes the system's electricity generation, greenhouse gas emissions, and cost of energy are analysed, and all the solutions are compared between different climatic conditions of all the capital cities. It is shown that there is a nearly linear correlation between the increase of average external air temperature and the increase of solar irradiation from 2030 to 2070. For the PV system in the majority of cities, a 10–20% increase of economic costs between the 2030 and 2050 climate scenario would be required. It is also found that the Hoba system has the best techno-economic performance with the lowest economic costs and higher renewable fraction, at both current climate and future climate.     

地热能道路融雪过程的临界融化面积比现象

建立了地热能道路融雪过程的理论预测模型,其中考虑了雪层的毛细作用与热质交换特性。对融雪过程中临界融化面积比现象的产生机理进行了深入分析。结果表明,临界融化面积比不随加热流体温度、环境条件以及埋管布置(埋深和间距)等因素而变化,是由埋管布置本身导致的不均匀路面热流以及雪层本身的多孔特性二者共同作用的结果。与加热流体温度相比,埋管布置和待融时间对融雪时间的影响更大,是融雪系统优化设计的最重要因素。     

Optimal design and operation of a photovoltaic–electrolyser system using particle swarm optimisation

In this study, hydrogen generation is maximised by optimising the size and the operating conditions of an electrolyser (EL) directly connected to a photovoltaic (PV) module at different irradiance. Due to the variations of maximum power points of the PV module during a year and the complexity of the system, a nonlinear approach is considered. A mathematical model has been developed to determine the performance of the PV/EL system. The optimisation methodology presented here is based on the particle swarm optimisation algorithm. By this method, for the given number of PV modules, the optimal sizeand operating condition of a PV/EL system areachieved. The approach can be applied for different sizes of PV systems, various ambient temperatures and different locations with various climaticconditions. The results show that for the given location and the PV system, the energy transfer efficiency of PV/EL system can reach up to 97.83%.     

基于遗传算法优化粗糙决策模型的光伏电站发电量的影响因素研究

通常光伏电站设计时要考虑2个主要目标,一个是使光伏电站的发电量最大,另一个是使光伏电站的度电成本最低。影响光伏电站发电量的因素众多,不同因素之间的相互影响及其交互影响极其复杂。在粗糙决策模型的基础上,引入遗传算法来寻找光伏电站发电量的主要影响因素。以光伏电站发电量作为决策属性,选取8个参数作为条件属性,建立了光伏电站发电量的诊断模型,通过计算分析,得到了影响光伏电站发电量的决策规则。结果表明:光伏组件串联数、热交换系数及交流线损是影响光伏电站发电量的决定性因素;对热交换系数较大的大型地面光伏电站而言,通过控制交流线损和光伏组件串联数可以更有效地提高光伏电站的发电量。     

Modeling and simulation of grid-connected photovoltaic energy conversion systems

Solar power generation using PV (photovoltaic) technology is a key but still evolving technology with the fastest growing renewable-based market worldwide in the last decade. In this sector with tremendous potential for energy security and economic development, grid-connected PV systems are becoming today the most important application of solar PV generation. Based on this trend, PV system designers require an accurate and reliable tool in order to predict the dynamic performance of grid-tied PV systems at any operating conditions. This will allow evaluating the impact of PV generation on the electricity grids. This paper presents a detailed characterization of the performance and dynamic behavior of a grid-connected PV energy conversion system. To this aim, a flexible and accurate PV simulation and evaluation tool (called PVSET 1.0) is developed. The PV system is modeled, simulated and validated under the MATLAB/Simulink environment. The accuracy of simulation results has been verified using a 250 Wp PV experimental set-up.     

Coupled thermal model of photovoltaic-thermoelectric hybrid panel for sample cities in Europe

In general, modeling of photovoltaic-thermoelectric (PV/TEG) hybrid panels have been mostly simplified and disconnected from the actual ambient conditions and thermal losses from the panel. In this study, a thermally coupled model of PV/TEG panel is established to precisely predict performance of the hybrid system under different weather conditions. The model takes into account solar irradiation, wind speed and ambient temperature as well as convective and radiated heat losses from the front and rear surfaces of the panel. The model is developed for three sample cities in Europe with different weather conditions. The results show that radiated heat loss from the front surface and the convective heat loss due to the wind speed are the most critical parameters on performance of the hybrid panel performance. The results also indicate that, with existing thermoelectric materials, the power generation by the TEG is insignificant compared to electrical output by the PV panel, and the TEG plays only a small role on power generation in the hybrid PV/TEG panel. However, contribution of the TEG in the power generation can be improved via higher ZT thermoelectric materials and geometry optimization of the TEG.     

Performance results and analysis of 3 kW grid-connected PV systems

Four 3 kW grid-connected photovoltaic (PV) generation systems have been installed and monitored at the Field Demonstration Test Center in Korea since October 2002. To observe the overall effect of meteorological conditions on their operation characteristics by field test, the monitoring system has been constructed for measuring and analyzing the performance of PV systems and components in November 2002. In this paper, the performance of PV systems is evaluated and analyzed not only for component perspective but also for global perspective by reviewing one year of monitoring results and loss factors of PV systems. On the basis of these monitoring results, the performance of PV systems is compared to the measured performance of PV systems with the estimated performance by simulation. These results will indicate that it is highly imperative to develop evaluation, analysis and application technology for PV systems.     

基于小波-智能算法组合模型的光伏出力预测

光伏出力具有强非线性和非规律性的特点,因而其预测存在诸多困难。通过对光伏出力数据进行小波分解,获得其出力数据的低频与高频部分,再分别选取合适的智能算法模型预测低频和高频部分,最后将各部分加总还原为原始数据的预测值。通过对某光伏发电设备的出力数据进行预测计算,证明基于小波分解的组合预测模型在光伏出力预测方面具有较高的准确性与可靠性。     

An evaluation method of PV systems

Data evaluation methods have wide adaptations, such as feedbacks to PV system operation management and design. The authors have already developed sophisticated verification method (SV method) of PV systems, which is a simple evaluation method to identify six kinds of system loss rates using basic information and simple four measurable data. This time, the authors introduced quality diagnosis to our previous model for compensating the measurement errors in field data, and improved the algorithm of the model. Consequently, validity of the evaluation result became better than the previous model.     

Computer-aided design of PV/wind hybrid system

A complete set of match calculation methods for optimum sizing of PV/wind hybrid system is presented. In this method, the more accurate and practical mathematic models for characterizing PV module, wind generator and battery are adopted; combining with hourly measured meteorologic data and load data, the performance of a PV/wind hybrid system is determined on a hourly basis; by fixing the capacity of wind generators, the whole year’s LPSP (loss of power supply probability) values of PV/wind hybrid systems with different capacity of PV array and battery bank are calculated, then the trade-off curve between battery bank and PV array capacity is drawn for the given LPSP value; the optimum configuration which can meet the energy demand with the minimum cost can be found by drawing a tangent to the trade-off curve with the slope representing the relationship between cost of PV module and that of the battery. According to this match calculation method, a set of match calculation programs for optimum sizing of PV/wind hybrid systems have been developed. Applying these match calculation programs to an assumed PV/wind hybrid system to be installed at Waglan island of Hong Kong, the optimum configuration and its hourly, daily, monthly and yearly performances are given.     

A photovoltaic voltage regulation impact investigation technique.I. Model development

With changing weather patterns or clouds moving over a given utility service area, the power generated by any photovoltaic (PV) power systems in that service area will vary tremendously. Depending on the percentage penetration of these PV systems on a distribution feeder, these variations in the PV systems' performance may cause undesirable voltage fluctuations along the feeder and also may impact the operation of the voltage regulating equipment on the distribution feeder. A computer program was developed to allow the utility engineer to determine the impact of the fluctuating PV generation due to moving cloud patterns. This impact is determined on the distribution system level by monitoring the feeder voltage profile and the operation of any voltage regulating devices. The model is rigorous and includes modeling capabilities beyond those of previous investigations     

跟踪式光伏发电系统研究

根据某地实测的太阳辐射数据,仿真比较了配备有单轴跟踪和双轴跟踪等4种跟踪控制的光伏发电系统与固定式光伏发电系统的太阳辐射利用率。并在此基础上对4种跟踪系统的跟踪角控制规律及跟踪控制方式进行了详细的分析,得出倾纬度角单轴跟踪系统控制规律最为简单,算法实施更为实用的结论。同时,也在理论上证明了采用步进式控制方式的跟踪系统能够在保持较高太阳辐射利用率情况下简化控制系统设计,有利于工程设计及应用。     

Satellite-based snow identification and its impact on monitoring photovoltaic systems

Earth observation allows the separation of snow cover and cloudiness using multispectral measurements. Several satellite-based snow monitoring services are available, ranging from regional to world-wide scales. Using these data enables photovoltaic (PV) plant management to differentiate between failures due to snow coverage on a PV system and other error sources. Additionally, yield estimates for solar siting are improved. This paper presents a validation study from January to April 2006 comparing satellite-based datasets with ground measurements from German and Swiss meteorological stations. A false alarm rate, an error due to irradiance underestimation, the availability of daily data, and the classification accuracy are introduced as quality metrics. Compared to Switzerland, generally a higher accuracy is found in all datasets for Southern Germany. The most significant difference among the datasets is found in the error pattern shifting from too much snow (which results in an error due to underestimation of irradiance) to too little snow detection, causing a false alarm in PV monitoring.Overall, the data records of the Land Surface Analysis Satellite Application Facility (LSA SAF), the German Aerospace Center (DLR) and the Interactive Multisensor Snow and Ice Mapping System (IMS) are found to be most suitable for solar energy purposes. The IMS dataset has a low false alarm rate (4%) and a good data availability (100%) making it a good choice for power plant monitoring, but the error due to underestimation relevant in site auditing is large with 59%. If a cumulative snow cover algorithm is applied to achieve information every day as needed both for power plant monitoring and site auditing, both the DLR and the LSA SAF datasets are comparable with classification accuracies of 70%, false alarm rates of 37% and 34%, respectively, and errors due to irradiance underestimation in 26% and 27% of all coincidences.     

Influence of photovoltaic generation model and time resolution on the reliability evaluation of distribution systems

This paper aims to investigate the influence of photovoltaic (PV) generation on reliability evaluation of distribution systems. Two PV generation models are used to predict the output power injected into the grid, taking into account the main relevant environmental variables, the irradiance and ambient temperature. Issues that directly affect the output power, such as the spatial smoothing effect due to the plant size and the influence of the irradiance and temperature measurement interval are taken into consideration. Using measurement time series of irradiance and local temperature, the models are used to generate power series in 4‐minute and hourly resolutions. The generated power series are used in a reliability assessment model, with the objective of evaluating the impact of solar resource variability on the reliability indices of the system. Case studies on the IEEE RBTS‐Bus 2 and on the real distribution system of Fernando de Noronha in Brazil are presented and discussed, for power plants of different capacities, considering the effect of the PV generation models, the temporal resolution of the time series and the spatial smoothing of the power output fluctuations. The results show that the power time series in hourly resolution significantly underestimates the frequency of interruptions. For the real system, this index is underestimated at the system level (up to 43%) and at the load points (up to 72%). On the other hand, for the interruption duration index, the temporal aggregation results in a small underestimation (just 4%). The results also indicates that the smoothing effect is irrelevant for typical PV system sizes of distribution systems with discretization equal to or above 4 minutes.