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Outdoor Performance and Modelling of Innovative Crystalline Silicon Photovoltaic Modules Under Hot Climatic Conditions
Abstract
The outdoor assessment of photovoltaic (PV) systems provides useful data to validate performance modelling approaches. The scope of this work is to analyse and model the outdoor performance of different grid-connected poly-crystalline Silicon (poly-c Si) PV systems installed at the PV Technology Laboratory of the University of Cyprus (UCY). These systems provided by Hanwha Q CELLS were installed side-by-side at a fixed-plane and monitored for a period of one year. Apart from PV system operational data, meteorological data were also extracted. Specifically, the focus of this ongoing analysis is to compare the performance of different modelling methods against real outdoor energy measurements and to investigate the impact of using real meteorological data for the simulation using the PVWATTS model and the PVSYST simulation software. The annual DC Performance Ratio (PRDC) results using the PVWATTS model and calculated using the PVSYST software showed that the prediction error (PE) was below 2 % for the PVSYST simulation, whereas for the PVWATTS model PE differences of up to 8 % were observed when compared to the measured PRDC.
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Several recent independent kWh/kWp studies have found similar energy yields (<;±5%) for various c-Si and thin films without any consistent technology bias. A comparison of various modelling methods such as the matrix method, 1 or 2 diode models, SV method and empirical equations has been performed to see how they predict PV performance. The values of thermal and low light level coefficients used in some simulation models have been found to be different from what is measured to IEC standards. These discrepancies mean simulation programs often predict larger variations between technologies and usually favouring thin films. Suggestions are made as to the best way to predict and validate system performance.
In this paper, a new method is demonstrated for online remote simulation of photovoltaic systems. The required communication technology for the data exchange is introduced and the methods of PV generator parameter extraction for the simulation models are analysed. The method shown for parameter extraction from the manufacturer data is especially useful for the commissioning procedure, where the measured installed power is transferred to standard test conditions using the simulation model and can then be easily compared with the design power. At a simulation accuracy of 2% using the software environment INSEL ® any problems with the PV generator can reliably be detected. Online simulation of a grid connected PV generator is then carried out during the operation of the photovoltaic plant. The visualisation includes both the monitored and the simulated online data sets, so that a very efficient fault detection scheme is available. The method is implemented and validated on several grid connected photovoltaic power plants in Germany. It is excellently suited to provide automatic and real time fault detection and significantly improve the commissioning procedure for photovoltaic plants of all sizes.
The U.S. Department of Energy has supported development of the Solar Advisor Model (SAM) to provide a common platform for evaluation of the solar energy technologies being developed with the support of the Department. This report describes a detailed comparison of performance-model calculations within SAM to actual measured PV system performance in order to evaluate the ability of the models to accurately predict PV system energy production. This was accomplished by using measured meteorological and irradiance data as an input to the models, and then comparing model predictions of solar and PV system parameters to measured values from co-located PV arrays. The submodels within SAM which were examined include four radiation models, three module performance models, and an inverter model. The PVWATTS and PVMod models were also evaluated.
Mathematical, empirical, and electrical models have long been implemented and used to predict the energy yield of many photovoltaic (PV) technologies. The purpose of this paper is to compare the annual DC energy yield prediction errors of four models namely the single-point efficiency, single-point efficiency with temperature correction, the Photovoltaic for Utility-Scale Applications (PVUSA), and the one-diode model, against outdoor measurements for different grid-connected PV systems in Cyprus over a 4-year evaluation period. The different models showed a wide variation of prediction errors, demonstrating a strong dependence between model performance and the different technologies. In particular, it was clearly shown that the application of temperature loss correction based on the manufacturer's temperature coefficients of power at maximum power point assisted in improving the energy yield prediction significantly especially for the crystalline silicon (c-Si) technologies. In most cases, the best agreement between the modeled results and outdoor-measured annual DC energy yield for mono-crystalline silicon (mono-c-Si) and multi-crystalline silicon (multi-c-Si) technologies was obtained using the one-diode model. The energy yield for the thin-film technologies was more accurately predicted using the PVUSA model with the exception of the copper-indium-gallium-diselenide (CIGS) technology, which was best predicted using the single-point efficiency with temperature correction and one-diode models, thus demonstrating similar physical properties to c-Si technologies. The paper further quantifies the combined uncertainties associated with the predicted energy yield as a function of the input parameters for the single-point efficiency, single-point efficiency with temperature correction, and the PVUSA models. Copyright © 2011 John Wiley & Sons, Ltd.
Sandia National Laboratories has integrated improved photovoltaic (PV) system modelling techniques into a simplified program named PVFORM. The new model simulates hourly performance for a one-year period and is applicable to a grid-interactive or stand-alone PV flat-plate system. The program can be run on mainframe or personal computers. This manual describes how to operate the PVFORM program, with detailed examples of the required inputs. Sample outputs are also included and discussed. 8 refs.
By a careful study of data collected from seven varieties of photovoltaic (PV) module it is demonstrated that a simple modified form of the Hottel–Whillier–Bliss (HWB) equation, familiar from the analysis of flat-plate solar–thermal collectors, can be employed to predict module temperatures within an accuracy comparable to the cell-to-cell temperature differences typically encountered within a module. Furthermore, for modules within the range of construction parameters employed in this study, the actual values of the two modified HWB constants do not appear to depend upon module type. The implication of these results for the accuracy of outdoor module characterization is discussed. Copyright © 2008 John Wiley & Sons, Ltd.
Measurements of the power produced by a photovoltaic (PV) system are important for technical as well as financial reasons, especially in large installations. The energy produced by a PV system is modeled through its nominal power, the incoming irradiance and the major energy loss mechanisms. These mechanisms involve the temperature of the cells, the response of a cell to low intensity light, the spectrum and polarization of the light, the deviation from maximum power point tracking, module mismatch and ohmic losses. The experimental quantities needed by the model are the solar irradiance at the plane of the array, the cell temperature and the nominal power of the system. In this work, we present part of the results of the theoretical calculations and their comparison with actual experimental measurements.
This paper describes the features of the PV system integrated evaluation software (PVI) developed by the authors. "PVI" was developed to assist in the design of grid-connected PV system applications and consists of a main tool and three optional tools. The main tool is the basic design tool. This tool is used to determine the PV system output energy based on the loss percentage of the PV system. The proportion of losses is based on development data calculated by the evaluation method developed at our Lab., "the sophisticated verification (SV) method". This method allows the user to feedback the performance of existing systems performance and loss pattern information to new PV system design projects. "PVI" has also three optional tools. The main optional tool is a PV array simulation tool. This tool is available for estimating annual, monthly or daily output power of PV arrays with different azimuth and orientation for the maximum of four surfaces at the same time. This simulation model calculates output power from I-V characteristic, considering effects of irradiance, ambient temperature, module rating, and so on. The other optional tool is for shading analysis that evaluates shading problems based on fish-eye lens pictures. This tool enables the user to determine the shading losses at the PV system under complex conditions. Additionally, PVI is able to input the database of SV method. The database includes the total design factor, which is analyzed data of existing PV systems.
The performance of grid connected systems is usually reported by AC energy (kWh/kWp) and performance ratio (PR) values (S. Ransome et al., 2003). If there are any outages or underperformance due to temporary faults or effects like shading these all need to be carefully corrected to give a true value for the performance otherwise these systems specific losses can dominate comparative kWh/kWp values. This paper proposes a way of calculating system performance using the final yield YF and the performance ratio versus plane of array irradiance G1. When the system is performing well the data points are in a narrow range that can be curve fitted with empirical formulae. Underperforming points (which may depend on random events like outages) can be easily identified, as they are not lying on the narrow line. The expected yield in kWh/kWp can then be determined by folding in the curve fit to the good performance points by the expected irradiance and temperature data. These techniques are being used to test different module technologies and improvements such as anti reflection coated glass in Sydney, Australia and at ISET in Kassel, Germany.
An electrical simulation model for photovoltaic cells, modules and
arrays has been developed that will be useful to a wide range of
analysts in the photovoltaic industry. The Microsoft(R) Windows<sup>TM
</sup> based program can be used to analyze individual cells, to analyze
the effects of cell mismatch or reverse bias (“hot spot”)
heating in modules, and to analyze the performance of large arrays of
modules including bypass and blocking diodes. User defined statistical
variance can be applied to the fundamental parameters used to simulate
the cells and diodes. The model is most appropriate for cells that can
be accurately modeled using a two-diode equivalent circuit. This paper
describes the simulation program and illustrates its versatility with
examples
The RETScreen(R) software was developed to assist in the
preliminary assessment of potential renewable energy projects. First
released for on-grid applications, the RETScreen PV model was recently
upgraded to cover off grid applications. These include stand-alone,
hybrid and water pumping systems. The program guides the users in the
design of their systems, by providing Initial estimates of array,
battery, or pump size. By changing a few of the system's parameters,
users are able to quickly screen the most effective technology and
system size depending on load, climatic conditions, and season of use.
This paper describes various models (radiation, array, battery, whole
system) used to predict energy production from PV systems, given
climatic variables and system parameters
This paper describes the development of a simulation model for predicting the performance of a solar photovoltaic (PV) system under specified load requirements and prevailing meteorological conditions at the site location. This study is aimed at situations where the loads are provided by alternating current (AC) electrical devices. The model consists of several submodels for each of the main components of the PV system; namely, PV array, battery, controller, inverter and various loads. Mathematical equations developed for modeling the performance of each component are explained along with the methodology to determine the performance coefficients. In order to validate the developed simulation model, an experimental system has been set up and tested under a variety of climatic conditions. Simulated results from the model under the same operating and environmental conditions are compared with those observed from the experimental tests. Good agreement is found in the comparison. Slight discrepancies appearing in the results are described and recommendations are given for further improvement. The simulation model developed can be used not only for analyzing the PV system performance, but also for sizing the PV system which is most suitable to the load requirements at any specified location provided that the local meteorological data is available.
The purpose of the present study was to develop a sufficiently good fit for the measured I–V curve of a PV module and array using only three easily measurable parameters: —the open-circuit voltage (Voc); —the short-circuit current (Isc); —the maximum power (Pm). With an additional three parameters (; ; ) it is possible to describe any I–V curve, taking into account cell temperature T and solar radiation Q. This method has been tested on various solar array panels as well as on a single 10 cm dia. solar cell. The difference between the real curve and the proposed fit was found to be less than 3 percent for a fixed temperature and radiation and about 6 percent for various combinations of temperature and radiation.
Manufacturers of photovoltaic panels typically provide electrical parameters at only one operating condition. Photovoltaic panels operate over a large range of conditions so the manufacturer’s information is not sufficient to determine their overall performance. Designers need a reliable tool to predict energy production from a photovoltaic panel under all conditions in order to make a sound decision on whether or not to incorporate this technology. A model to predict energy production has been developed by Sandia National Laboratory, but it requires input data that are normally not available from the manufacturer. The five-parameter model described in this paper uses data provided by the manufacturer, absorbed solar radiation and cell temperature together with semi-empirical equations, to predict the current–voltage curve. This paper indicates how the parameters of the five-parameter model are determined and compares predicted current–voltage curves with experimental data from a building integrated photovoltaic facility at the National Institute of Standards and Technology (NIST) for four different cell technologies (single crystalline, poly crystalline, silicon thin film, and triple-junction amorphous). The results obtained with the Sandia model are also shown. The predictions from the five-parameter model are shown to agree well with both the Sandia model results and the NIST measurements for all four cell types over a range of operating conditions. The five-parameter model is of interest because it requires only a small amount of input data available from the manufacturer and therefore it provides a valuable tool for energy prediction. The predictive capability could be improved if manufacturer’s data included information at two radiation levels.
A method is presented for estimating the monthly-average conventional energy displaced by photovoltaic systems. Monthly-average array efficiency is estimated in terms of array parameters and monthly-average meteorological data. Monthly-average excess capacity is estimated for systems having a constant load during daylight hours. If the system does not have battery storage, excess capacity must be dissipated or fed back to the utility. With battery storage, a portion of the excess capacity can be stored for later use. A method is presented for estimating the monthly-average system performance for a constant 24 hr-per-day load with a battery of specified capacity.
A new model is presented for accurate simulation of the external (I–V) characteristic of solar cells generators and the model is applied to direct analytical evaluation of the maximum power points, without involving time consuming numerical techniques. The model is compared with the traditional (iI–V) characteristic, which is chosen from the published literature, and very satisfactory match is obtained between the two. The new model lends itself for easy analytical manipulations. To this end it is applied to resistive load and closed form solution is obtained for the performance which is not readily obtainable from the traditional (I–V) characteristic.
Improved two-diode model for more detailed simulation of I- U-curves for solar cells and modules
- S Elies
- M Hermle
- B Burger
S. Elies, M. Hermle, and B. Burger, " Improved
two-diode model for more detailed simulation of I-
U-curves for solar cells and modules, " in 24 th
European Photovoltaic Solar Energy Conference,
2009, pp. 3737–3740.
Analysis of PV grid installations performance, comparing measured data to simulation results to identify problems in operation and monitoring
- B Wittmer
- A Mermoud
- T Schott
B. Wittmer, A. Mermoud, and T. Schott, " Analysis
of PV grid installations performance, comparing
measured data to simulation results to identify
problems in operation and monitoring, " in 30th
European Photovoltaic Solar Energy Conference
and Exhibition, 2015, pp. 2265 – 2270.
PVWATTS-An online performance calculator for grid-connected PV systems PVsyst photovoltaic software
- W Marion
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W. Marion and M. Anderberg, " PVWATTS-An
online performance calculator for grid-connected
PV systems, " in ASES Solar Conference, 2000.
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