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Automatic fault detection (AFD) is a key technology to optimize the Operation and Maintenance of photovoltaic (PV) systems portfolios. A very common approach to detect faults in PV systems is based on the comparison between measured and simulated performance. Although this approach has been explored by many authors, due to the lack a common basis for evaluating their performance, it is still unclear what are the influencing aspects in the design of AFD algorithms. In this study, a series of AFD algorithms have been tested under real operating conditions, using monitoring data collected over 58 months on 80 rooftop-type PV systems installed in Germany. The results shown that this type of AFD algorithm have the potential to detect up to 82.8% of the energy losses with specificity above 90%. In general, the higher the simulation accuracy, the higher the specificity. The use of less accurate simulations can increase sensitivity at the cost of decreasing specificity. Analyzing the measurements individually makes the algorithm less sensitive to the simulation accuracy. The use of machine learning clustering algorithm for the statistical analysis showed exceptional ability to prevent false alerts, even in cases where the modeling accuracy is not high. If a slightly higher level of false alerts can be tolerated, the analysis of daily PR using a Shewhart chart provides the high sensitivity with an exceptionally simple solution with no need for more complex algorithms for modeling or clustering., 33 pages, 30 figures, preprint submitted to Elsevier Solar Energy

Photovoltaies is expanding into new market segments. Photovoltaic noise barriers (PVNB) along motorways and railways permit today one of the most economic applications of grid-connected PV w ith the additional benefits of large scale plants (typical installed power: more than 100 kWp) and no extra land consumption. The aim of this study is to reveal the large potential that can be exploited for PV on noise barriers with the overall objective of raising the share of renewable energies for the EU's electricity market. In contrast to many PV-potential studies published before, this proposal is focusing on PVNB only, as one of the cheapest ways to implement large scale grid-connected PV installations.

Rising demand for solar power generation will lead to increased land use competition, and thus to potential economic and social conflict. A solution to this challenge is to produce food and energy within an agrophotovoltaics (APV) system. Since 2017, governments in Japan, France, Massachusetts (USA), South Korea, and China have introduced policies supporting APV implementation. Governments considering APV implementation – e.g. in India and Germany – for evidence-based policy making are demanding information on how levelized cost of electricity (LCOE) of APV differs from that of conventional ground-mounted photovoltaics (PV), as well as on how additional costs associated with APV installation relate to the benefit of maintaining agricultural activity under APV. Data for a techno-economic price-performance ratio calculation has been retrieved from an inter- and transdisciplinary APV case study in Germany. We observed that the LCOE of APV with €0.0828 kWh−1 is 38% higher than that of ground-mounted PV, resulting in an annual cropland preservation price of €9,052 ha−1 a−1. The annual revenue of potato and winter wheat production under APV resulted in a performance of €10,707 ha−1 a−1 and €1,959 ha−1 a−1 respectively, leading to a beneficial price-performance ratio of 0.85 for potato production and, with a ratio of 4.62, a disadvantageous result for winter wheat. Overall, APV is not necessarily recommended in crop rotating systems. However, in combination with permanent cultures – e.g. berries, fruits, or wine grapes – as the price for these types of applications is lower, while at the same time providing higher performance by optimizing techno-ecological synergies.

Combining agriculture and photovoltaics on the same land area gains in attention and political support in a growing number of countries accompanied by notable research activities in France, USA and Korea, amongst others. This study assesses the technical feasibility of agrivoltaic (APV), while it gives insights on how to design an APV system. Furthermore, it analyses the electrical yield and the behavior and productivity of four crops grown in Germany's largest agrivoltaic research facility installed in 2016 near Lake Constance within the research project APV-RESOLA by Fraunhofer Institute for Solar Energy Systems ISE. The German design differs from most other agrivoltaic approaches by allowing for a wide range of machine employment, facilitated by a vertical clearance of 5 m and a width clearance of up to 19 m. Crops cultivated under the APV system and on the reference field under a crop rotation scheme include potato, celeriac, clover grass and winter wheat. The land use efficiency measured by the Land Equivalent Ratio (LER) indicated a rise between 56% and 70% in 2017 while the dry and hot summer in 2018 demonstrated that the agrivoltaic system could increase land productivity by nearly 90%. Radiation simulations showed that deviating from full south by around 30° resulted in equal distribution of radiation on ground level, representing the basis for the agrivoltaic design. Considering climate change and increasing land scarcity, our overall results suggest a high potential of agrivoltaics as a viable and efficient technology to address major challenges of the 21rst century.

Models for the calculation of losses in PV systems are widely applied but typically focus on single components (i.e., the solar cell). We discuss relevant models and combinations thereof to analyze losses from wafer to system. We propose a holistic approach to analyze losses from laboratory to environmental conditions. The proposed approach focusses on practically relevant interfaces (i.e., STC module power) and is based on separated influence factors.

This article sheds new light on photovoltaic (PV) module rating according to predicted yield rather than power measured at standard testing conditions (STC). We calculate module performance ratios (MPR) for measured characteristics of eight different module types and compare them with a reference MPR calculated with typical crystalline silicon characteristics. In place of the not yet existing standardized weather data, we use commercially available weather data for three different locations. The reference MPR for the three locations were 95.5%, 94.6%, and 91.0%, respectively, with differences to the other module types of ±8% at maximum. MPR was calculated with reference to nominal power, and—following IEC 61853—without consideration of potential degradation. The strongest contribution to the initial differences between the module types was due to differences in irradiance dependency. Standard uncertainties for all initial MPR values were calculated and range from 1.8% to 3.0%, including STC power uncertainty. We propose a module rating method that indicates whether a module type's performance is significantly above, below, or essentially equal to the reference. The method evaluates the MPR difference between module type and reference, taking uncertainty into account. Significant differences were only found between modules with obviously different characteristics, but not between the crystalline silicon module types under scrutiny. As the uncertainty analysis did not cover degradation and influences due to the use of not standardized weather data, a sensitivity analysis was performed. Long-term degradation can change the comparative energy rating significantly, whereas the selection of tilt angle and assumptions regarding module operating temperature did not have a strong effect. Copyright © 2015 John Wiley & Sons, Ltd.

Yield predictions are performed to predict the solar resource, the performance and the energy production over the expected lifetime of a photovoltaic (PV) system. In this study, we compare yield predictions and monitored data for 26 PV power plants located in southern Germany and Spain. The monitoring data include in-plane irradiance for comparison with the estimated solar resource and energy yield for comparison with predicted performance. The results show that because of increased irradiance in recent years (‘global brightening’) the yield predictions systematically underestimate the energy yield of PV systems by about 5%. Because common irradiance databases and averaging times were used for the yield predictions analysed in this paper, it is concluded that yield predictions for areas where the global brightening effect occurred in general underestimated the energy yield by the same magnitude. Using recent satellite-derived irradiance time series avoids this underestimation. The observed performance ratio of the analysed systems decreases by 0.5%/year in average with a relatively high spread between individual systems. This decrease is a main factor for the combined uncertainty of yield predictions. It is attributed to non-reversible degradation of PV cells or modules and to reversible effects, like soiling. Based on the results of the validation, the combined uncertainty of state of the art yield predictions using recent solar irradiance data is estimated to about 8%. Copyright © 2015 John Wiley & Sons, Ltd.

Varying spectral irradiance affects performance of photovoltaic (PV) modules depending on their band gap and spectral response. Therefore, energy rating or yield prediction procedures should take into account the irradiance that is effectively available for a specific PV technology. This effective irradiance differs from broadband solar resource information first due to the different spectral sensitivity of PV devices and pyranometers, and second due to the difference between real and reference spectral distribution. The combined difference, also referred to as ‘spectral impact’, is to date considered in form of fixed spectral gain or loss factors applied to the broadband solar resource – if it is considered at all. Values for the monthly or annual spectral impact have been reported for several locations; however without estimates of their uncertainty. This article addresses the question of how large the uncertainty of the spectral impact is. Contributions to the uncertainty of the spectral impact are discussed, with focus on the method of determining the spectral impact by means of measured spectral irradiance and calculated spectral mismatch factor ( MM ). Using a simplified procedure, the uncertainty of spectral impact was estimated from the average spectral mismatch uncertainty. It was found to be of the same magnitude as the spectral impact itself, and dependent on the PV technology. For five single-junction PV technologies, amorphous silicon, cadmium telluride, standard crystalline silicon, high-efficiency crystalline silicon and a wide-band-gap CIGS technology, the estimated uncertainty values were 1.8%, 1.4%, 0.9%, 1.0% and 1.2%, respectively. The results were obtained from a specific measurement campaign conducted from 01.06.2010 to 31.12.2013 in Freiburg im Breisgau, Germany, but the order of magnitude is considered to be typical. In order to validate the simplified uncertainty estimation method, a sensitivity analysis was carried out to evaluate the influences of calibration and drift of the spectroradiometer, high-angle-of-incidence conditions, the available wavelength range of the spectroradiometer and results obtained with different spectroradiometers. With the smaller wavelength range of 350–1050 nm, which is a typical range for various instruments used in many scientific publications, the calculated spectral impact was significantly smaller. The other influences were found to affect the result only within the estimated uncertainty limits. The uncertainty values presented here should be considered lower limits until they are backed up by further analysis.

This article presents results from investigating the impact of varying spectral irradiance on the performance of different PV technologies. Relative gains or losses were quantified for five typical PV technologies with different band gaps and, consequently, different spectral responses using spectral irradiance measured from 01.06.2010 to 31.12.2013 in Freiburg im Breisgau, Germany. With the spectrally resolved data, the effectively available annual irradiation per technology was calculated using the spectral mismatch factor, and compared to the total broadband irradiation measured by a pyranometer. The process used to calculate the spectral impact produces a result that can directly be used to estimate the effectively available irradiation for yield prediction or energy rating. The annual spectral impact was +3.4% for amorphous silicon, +2.4% for cadmium telluride, +1.4% for crystalline silicon, +1.1% for high-efficiency crystalline silicon and +0.6% for small-band-gap CIGS. Technologies with a large band gap exhibited spectral gains in summer and spectral losses in winter, and vice versa for small-band-gap technologies. The results are discussed and interpreted with consideration to uncertainties and results published so far. Furthermore, it was investigated in how far average photon energy (APE) can be used as a quantitative indicator for the spectral impact. In summary, it was found that using APE does not present actual advantages over using the spectral mismatch factor, and should rather be used for qualitative than for quantitative evaluations.

Today, lifetime energy yield predictions should include an assessment of the uncertainties of the predicted values as a precondition for financing large PV plants in order to properly quantify risk and return. However, the approach to perform the yield prediction with attendant uncertainty estimation is not standardized which makes it difficult to compare one investment and another. Often important sources of uncertainties are not even included in the overall uncertainty assessment. A method to calculate uncertainties and P-values for year by year and lifetime energy yield predictions of PV systems is presented. The focus is on the cumulative impact of the combination of uncertainties on delivered energy going into the project pro-forma and downside financial analysis, not on estimation of uncertainties for individual modelling steps. The proposed approach is an effort to standardize the procedure of nncertaintv calculation of nrerlicted enerov vielrls of PV systems in order to properly estimate financial investment risk.

Influencing factors, including rooftop material, ventilation, module framing and other environmental conditions on module temperature of selected photovoltaic (PV) systems in Singapore have been analyzed in detail. The variance of module temperature has turned out to be much larger than the variance of ambient temperature on the different project sites. From the analysis of the influencing factors, guidelines for PV system installations are derived in order to achieve lower module temperatures, eventually leading to an optimized system performance in tropical regions.

In this study, we investigate the performance ratio (PR) of about 100 German photovoltaic system installations. Monitored PR is found to be systematically lower by ~2–4% when calculated with irradiation data obtained by pyranometers (henceforth denoted as PRPyr) as compared with irradiation amounts measured by reference cells (denoted as PRSi). Annual PRSi for the ~100 systems is found to be between ~70% and ~90% for the year 2010, with a median PR of ~84%. Next, simulations were performed to determine loss mechanisms of the top 10 performing systems, revealing a number of these loss mechanisms may still allow for some optimization. Despite the fact that we do not see such values from our monitoring data base up to now, we believe PRSi values above 90% are realistic even today, using today's commercially available components, and should be expected more frequently in the future. This contribution may help in deepening our knowledge on both energy loss mechanisms and efficiency limits on the system level and standardization processes of system-related aspects. Copyright © 2012 John Wiley & Sons, Ltd.

The German government is planning to increase the share of renewable energy sources. In this context, it is important to understand the decision-making behaviour of farmers regarding investments in renewable energy systems that generate energy from biomass and farmers' reactions to investment-support measures. To study this behaviour, we conduct a survey and confront farmers with a hypothetical opportunity to invest in a biogas plant. Our findings reveal that farmers have heterogeneous investment thresholds. Their investment decisions are mainly driven by capital costs and the subjective perception of the risk resulting from the investment. Other decision parameters like sustainability and non-monetary objectives that are also examined in this paper, play only minor roles. However, bounded rationality is an important factor. Moreover, the influence of an investment subsidy was analysed. Only about half of the amount of the subsidy — as expected according to normative forecast models — is reflected in an increased willingness to invest. Furthermore, farmers who have previously invested in bioenergy plants show lower investment thresholds and have stronger reactions to the subsidy. Regarding the expansion of renewable energies these findings are meaningful for policy impact analysis.

Investment risks of utility-scale PV systems may arise from a wide range of sources: political stability in a region, interest rate levels and currency exchange rates or future energy price. However, the presence of stable political and economic conditions and feed-in tariffs or power purchase agreements may limit interest and price risks to acceptable levels. The technical risk of deviations between expected and actual life-time energy yield of a PV power plant is mostly influenced by the quality of energy yield predictions in case that system components correspond to their datasheet and guaranteed values and the maintenance concept is applied as expected. Recent publications estimate the standard uncertainty of life-time energy yield predictions to about 8%, which directly contributes to overall investment risk. In this paper we analyze two different strategies to reduce the influence of uncertainties of energy yield predictions on investment risks. The first strategy is diversification of risk, i.e. investing in a portfolio of systems. The second strategy is related to adjusted investment periods. It is concluded, that both strategies as well as the combination of these strategies are able to significantly reduce uncertainties. The resulting uncertainty of the lifetime energy yield for the combination of both approaches is estimated to about 3%.

Satellite derived irradiance maps with a high temporal and spatial resolution are a valuable data source for the analysis of large scale grid intergrated solar energy systems. For an appropriate use of this huge data base convenient methods for the characterization of the spatial and temporal structures of the satellite derived irradiance field are necessary. In this paper we introduce the application of a multiresolution decomposition for the structure analysis of irradiance maps. Using this tool the maps are decomposed into local averages (context) and gradients (detail) on various spatial scales. The information on the context and the detail may be directly interpreted in terms that are of interest, e.g. for the anlaysis of PV-systems implemented on a very large scale.

The main purpose of PV system performance monitoring is to determine whether the system is operating as expected. This requires measuring the actual output of the system as well as the conditions under which it is operating. Solar radiation intensity in the plane of the array (POA) is by far the most important operating condition and is the basis for calculating performance ratios (PR). However, differences in spectral and directional response between pyranometers and PV modules lead to intraday as well as seasonal fluctuations in the performance ratio, even though the system may be operating without faults or degradation.

International audience; Accurate solar irradiance data are not only of particular importance for the assessment of the radiative forcing of the climate system, but also absolutely necessary for efficient planning and operation of solar energy systems. Within the European project Heliosat-3, a new type of solar irradiance scheme is developed. This new type will be based on radiative transfer models (RTM) using atmospheric parameter information retrieved from the Meteosat Second Generation (MSG) satellite (clouds, ozone, water vapour) and the ERS-2/ENVISAT satellites (aerosols, ozone). This paper focuses on the description of the clear-sky module of the new scheme, especially on the integrated use of a radiative transfer model. The linkage of the clear-sky module with the cloud module is also briefly described in order to point out the benefits of the integrated RTM use for the all-sky situations. The integrated use of an RTM within the new Solar Irradiance Scheme SOLIS is applied by introducing a new fitting function called the modified Lambert–Beer (MLB) relation. Consequently, the modified Lambert–Beer relation and its role for an integrated RTM use are discussed. Comparisons of the calculated clear-sky irradiances with ground-based measurements and the current clear-sky module demonstrate the advantages and benefits of SOLIS. Since SOLIS can provide spectrally resolved irradiance data, it can be used for different applications. Beside improved information for the planning of solar energy systems, the calculation of photosynthetic active radiation, UV index, and illuminance is possible.

Accurate solar irradiance data are not only of particular importance for the assessment of the radiative forcing of the climate system, but also absolutely necessary for efficient planning and operation of solar energy systems. Within the European project Heliosat-3, a new type of solar irradiance scheme is developed. This new type will be based on radiative transfer models (RTM) using atmospheric parameter information retrieved from the Meteosat Second Generation (MSG) satellite (clouds, ozone, water vapour) and the ERS-2/ENVISAT satellites (aerosols, ozone). This paper focuses on the description of the clear-sky module of the new scheme, especially on the integrated use of a radiative transfer model. The linkage of the clear-sky module with the cloud module is also briefly described in order to point out the benefits of the integrated RTM use for the all-sky situations. The integrated use of an RTM within the new Solar Irradiance Scheme SOLIS is applied by introducing a new fitting function called the modified Lambert–Beer (MLB) relation. Consequently, the modified Lambert–Beer relation and its role for an integrated RTM use are discussed. Comparisons of the calculated clear-sky irradiances with ground-based measurements and the current clear-sky module demonstrate the advantages and benefits of SOLIS. Since SOLIS can provide spectrally resolved irradiance data, it can be used for different applications. Beside improved information for the planning of solar energy systems, the calculation of photosynthetic active radiation, UV index, and illuminance is possible.

International audience; A successful integration of solar energy into the existing energy structure highly depends on a detailed knowledge of the solar resource. The recently started European project HELIOSAT-3 will supply high-quality solar radiation data and taking advantage of the enhanced capabilities of the new Meteosat Second Generation (MSG) satellites. The expected quality represents a substantial improvement with respect to the available methods and will better match the needs of the solar energy community. These goals will be achieved by an improvement of the current semi-empirical Heliosat calculation schemes (see section 2) as well as by the development and establishment of a new type of calculation scheme. This new type will be based on radiative transfer models (RTM) using the information of atmospheric parameters retrieved from the MSG satellite (clouds, ozone, water vapor) and the GOME/ATSR-2 satellites (aerosols). Within this paper, the new type of the solar irradiance calculation scheme, including the functional treatment of the diurnal variation of the solar irradiance, is described.

International audience; The project SoDa (solar data) answers the needs of industry and research for information on solar radiation parameters with a satisfactory quality. The methodology is user-driven with a large involvement of users in the project, who gauge the progresses and achievements. A prototype service has been developed, using Internet technology, that integrates and efficiently exploits diverse networked information sources to supply value-added information. Access to data and applications has been greatly improved; efforts were made on interpolation methods and satellite data processing to achieve better quality and increase time and space coverage of the information. Applications were developed or networked to supply information actually needed by customers, and not only raw data.

International audience; Satellight was a 3 year-European research program (Jan. 1996-March 1999) with the objective of making available on Internet a database of solar radiation and daylight for Western and Central Europe. The data was obtained by processing the information provided by the Meteosat satellite every 30 minutes. We first developed and validated models to derive radiation and daylight data on ground from the satellite measurements. Then, we produced two years of data: 1996 and 1997, and made it accessible via a web server (its address is www.satel-light.com). The server provides statistics on the direct, diffuse and global illuminances or irradiances, on horizontal or tilted plane, for various zones in Europe or for specific locations. The information is presented as maps, figures or tables. In 2001, thanks to a new European project called SODA (see http://www-helioserve.cma.fr/soda/), three more years will be added to the database to make it more relevant of long term climatic trends

International audience; The estimation of the downward surface shortwave irradiance from satellite observations has been subject to numerous investigations in the past. Different methods from simple transmittance-reflectance correlations to the extensive use of radiative transfer calculations have been applied leading to generally satisfying results with an accuracy almost independent of the chosen method. In the framework of the European Community research project SATELLIGHT an attempt is made to use satellite methods to derive daylight and solar irradiance data with a continuous spatial coverage forWestern and Central Europe from Meteosat images. For potential end users these data will be placed in a data base in the Internet (Fontoynont et al., 1998). In daylighting applications, knowledge of the luminance distribution of the sky is of primary concern. Thus, beyond the retrieval of surface global irradiance, the separation of diffuse and direct components as well as a better representation of these quantities for low sun elevations had to be derived in the scope of this project. We present improvements and additions to an existing method for the derivation of the global irradiance. This includes new correction schemes for the influence of atmospheric extinction processes. These have been partly developed by simulating the satellite signal for a cloudless atmosphere using the radiative transfer code MODTRAN. In addition, the derivation of the diffuse irradiance is briefly outlined.

International audience

International audience

International audience