Energy yields of concentrating solar thermal power plants depend strongly on the availability of ... more Energy yields of concentrating solar thermal power plants depend strongly on the availability of beam irradiance.
We present a method to derive the direct normal irradiance (DNI) from MSG data. For this, we appl... more We present a method to derive the direct normal irradiance (DNI) from MSG data. For this, we apply the Heliosat method and a new model for the direct fraction of the irradiance. The clear sky irradiance is mainly determined by the aerosol optical depth (AOD) and water vapour content, which are taken from suitable climatologies. The accuracy of satellite derived DNI data has been analyzed for Spanish sites, more sites will be evaluated within the project SESK (Standardisierung der Ertragsprognose Solarthermischer Kraftwerkestandardization of yield prognosis for solar thermal power plants). As for concentrating solar power (CSP) the frequency distribution of DNI is of special importance, special attention is given to correct modeling of this feature.
The paper gives recommendations to reach high quality, traceable and reproducible yield prognosis... more The paper gives recommendations to reach high quality, traceable and reproducible yield prognosis for solar thermal power plants. The whole process chain from solar resources to simulation is evaluated to identify main error sources. Three main fields are identified, which have significant impact on accuracy of potential electricity yields: Firstly, much care must be taken to create realistic site-specific meteorological time-series in high temporal resolution, which well match the long-term average solar radiation conditions. A set of rules is given, which allow estimation of the uncertainty of solar resource data. Secondly, ambiguity of the technical performance of the plant can have severe impact on yield prognosis. This must be overcome by realistic parameterization of major components of the plant in yield simulations and appropriate performance guarantees from suppliers. Thirdly, the model applied to calculate potential energy yields must be capable to simulate the processes in a plant under evaluation fine enough in respect to spatial and temporal discretization. The model must be capable of reproducing realistically the major processes which are relevant for energy yields. This includes the definition of appropriate rules for plant operation. A quasi-static model approach can be sufficient, if corrections terms are introduced, which are derived from case studies with a dynamic model capable of simulating the relevant transient processes. The focus of this paper is on parabolic trough plants, but most findings also help for yield prognosis of other concentration solar technologies.
Energy yields of concentrating solar thermal power plants depend strongly on the availability of ... more Energy yields of concentrating solar thermal power plants depend strongly on the availability of beam irradiance. Direct solar irradiance is highly variable in space and time and thus, requires in-depth analysis of measurements with high quality, well tracked calibrations and approved quality control to achieve reliable results. Strong vari-ability from year to year makes it necessary to combine precision data, available from limited measurement peri-ods with long-term data, which should cover at least 10 years. For most places this may only be reached by ap-plication of historic satellite data. For sites around the Mediterranean region, Africa and the Mideast solar prod-ucts based on data from the Meteosat First Generation so far have been used. Since mid 2006 this satellite gen-eration is out of service and replaced by Meteosat Second Generation. Therefore, recent measurements can not be inter-compared to the satellite-series, which is used to retrieve long-term time-series. In th...
The paper gives recommendations to reach high quality, traceable and reproducible yield prognosis... more The paper gives recommendations to reach high quality, traceable and reproducible yield prognosis for solar thermal power plants. The whole process chain from solar resources to simulation is evaluated to identify main error sources. Three main fields are identified, which have significant impact on accuracy of potential electricity yields: Firstly, much care must be taken to create realistic site-specific meteorological time-series in high temporal resolution, which well match the long-term average solar radiation conditions. A set of rules is given, which allow estimation of the uncertainty of solar resource data. Secondly, ambiguity of the technical performance of the plant can have severe impact on yield prognosis. This must be overcome by realistic parameterization of major components of the plant in yield simulations and appropriate performance guarantees from suppliers. Thirdly, the model applied to calculate potential energy yields must be capable to simulate the processes in a plant under evaluation fine enough in respect to spatial and temporal discretization. The model must be capable of reproducing realistically the major processes which are relevant for energy yields. This includes the definition of appropriate rules for plant operation. A quasi-static model approach can be sufficient, if corrections terms are introduced, which are derived from case studies with a dynamic model capable of simulating the relevant transient processes. The focus of this paper is on parabolic trough plants, but most findings also help for yield prognosis of other concentration solar technologies.
Solar radiation measurements as most time-series data suffer from interruptions. Gaps may occur d... more Solar radiation measurements as most time-series data suffer from interruptions. Gaps may occur due to loss of power, misalignment, failure of instruments, insufficient cleaning or other reasons. Quality check procedures identify such malfunctioning and mark untrustworthy data by flags. Even well maintained stations with good equipment usually show gaps. In the case of the Indian SRRA network with its 51 stations operating since 2011, typically around 7% of the data are flagged as potentially erroneous or missing. Duration of gaps ranges from few minutes to several days. However many applications such as solar energy performance simulations need continuous time-series. Therefore it is required to fill the measurement gaps with reasonable data. Depending on duration and type of missing parameters various procedures can be used to fill gaps. This paper describes a set of procedures called 'basic gap filling' for solar irradiance, which can be applied without having available additional data. From the over-determined set of global, diffuse and direct radiation a single missing parameter can be calculated from the other two. When two or more solar irradiance components are missing for short gaps, clearness indices are derived to calculate the missing irradiance components. Basic gap filling procedure is applied as part of the SRRA/SolMap projects. The accuracy of the applied basic gap filling methodology is tested and the results show a mean bias of ca. 3 % over GHI, DNI and DHI over all types of gaps.
In the Solar Radiation Resource Assessment (SRRA) project of the Ministry of New and Renewable En... more In the Solar Radiation Resource Assessment (SRRA) project of the Ministry of New and Renewable Energy, India a network of 51 automatic solar radiation monitoring stations have been set up across India. Such a large number of high-quality solar radiation stations with sensitive instruments require efficient procedures for regularly controlling proper operation of each station, the quality of the measured data, and its overall performance. Following best practices for quality assessment tests, such routines are implemented at the SRRA archiving and processing center. Various quality control tests are applied that check the plausibility of data, differentiate trustworthy data from likely erroneous data and flag them accordingly. A data flagging system is implemented to identify, differentiate and quantify different types of errors. These quality-checked, flagged data are then used by routines to create monthly reports and data products. This paper describes the automated quality check system implemented and evaluates the performance of stations since their erection in 2011. This paper also describes first experiments to validate the functionality of the applied quality checks. The quality flag statistics of all 51 stations reveals that some stations are performing very well and others need more attention to improve. In the period from January 2012 to March 2013 on an average over all 51 stations, 92 % of the solar radiation data are classified as correct. Around 4 % of solar radiation data do not pass the coherence test. Tracking errors are observed during 0.3 % of the time averaged over all 51 stations. This analysis helps to further improve the operation of this network and find ways for better-automatized quality checks.
Energy yields of concentrating solar thermal power plants depend strongly on the availability of ... more Energy yields of concentrating solar thermal power plants depend strongly on the availability of beam irradiance.
Energy yields of concentrating solar thermal power plants depend strongly on the availability of ... more Energy yields of concentrating solar thermal power plants depend strongly on the availability of beam irradiance.
We present a method to derive the direct normal irradiance (DNI) from MSG data. For this, we appl... more We present a method to derive the direct normal irradiance (DNI) from MSG data. For this, we apply the Heliosat method and a new model for the direct fraction of the irradiance. The clear sky irradiance is mainly determined by the aerosol optical depth (AOD) and water vapour content, which are taken from suitable climatologies. The accuracy of satellite derived DNI data has been analyzed for Spanish sites, more sites will be evaluated within the project SESK (Standardisierung der Ertragsprognose Solarthermischer Kraftwerkestandardization of yield prognosis for solar thermal power plants). As for concentrating solar power (CSP) the frequency distribution of DNI is of special importance, special attention is given to correct modeling of this feature.
The paper gives recommendations to reach high quality, traceable and reproducible yield prognosis... more The paper gives recommendations to reach high quality, traceable and reproducible yield prognosis for solar thermal power plants. The whole process chain from solar resources to simulation is evaluated to identify main error sources. Three main fields are identified, which have significant impact on accuracy of potential electricity yields: Firstly, much care must be taken to create realistic site-specific meteorological time-series in high temporal resolution, which well match the long-term average solar radiation conditions. A set of rules is given, which allow estimation of the uncertainty of solar resource data. Secondly, ambiguity of the technical performance of the plant can have severe impact on yield prognosis. This must be overcome by realistic parameterization of major components of the plant in yield simulations and appropriate performance guarantees from suppliers. Thirdly, the model applied to calculate potential energy yields must be capable to simulate the processes in a plant under evaluation fine enough in respect to spatial and temporal discretization. The model must be capable of reproducing realistically the major processes which are relevant for energy yields. This includes the definition of appropriate rules for plant operation. A quasi-static model approach can be sufficient, if corrections terms are introduced, which are derived from case studies with a dynamic model capable of simulating the relevant transient processes. The focus of this paper is on parabolic trough plants, but most findings also help for yield prognosis of other concentration solar technologies.
Energy yields of concentrating solar thermal power plants depend strongly on the availability of ... more Energy yields of concentrating solar thermal power plants depend strongly on the availability of beam irradiance. Direct solar irradiance is highly variable in space and time and thus, requires in-depth analysis of measurements with high quality, well tracked calibrations and approved quality control to achieve reliable results. Strong vari-ability from year to year makes it necessary to combine precision data, available from limited measurement peri-ods with long-term data, which should cover at least 10 years. For most places this may only be reached by ap-plication of historic satellite data. For sites around the Mediterranean region, Africa and the Mideast solar prod-ucts based on data from the Meteosat First Generation so far have been used. Since mid 2006 this satellite gen-eration is out of service and replaced by Meteosat Second Generation. Therefore, recent measurements can not be inter-compared to the satellite-series, which is used to retrieve long-term time-series. In th...
The paper gives recommendations to reach high quality, traceable and reproducible yield prognosis... more The paper gives recommendations to reach high quality, traceable and reproducible yield prognosis for solar thermal power plants. The whole process chain from solar resources to simulation is evaluated to identify main error sources. Three main fields are identified, which have significant impact on accuracy of potential electricity yields: Firstly, much care must be taken to create realistic site-specific meteorological time-series in high temporal resolution, which well match the long-term average solar radiation conditions. A set of rules is given, which allow estimation of the uncertainty of solar resource data. Secondly, ambiguity of the technical performance of the plant can have severe impact on yield prognosis. This must be overcome by realistic parameterization of major components of the plant in yield simulations and appropriate performance guarantees from suppliers. Thirdly, the model applied to calculate potential energy yields must be capable to simulate the processes in a plant under evaluation fine enough in respect to spatial and temporal discretization. The model must be capable of reproducing realistically the major processes which are relevant for energy yields. This includes the definition of appropriate rules for plant operation. A quasi-static model approach can be sufficient, if corrections terms are introduced, which are derived from case studies with a dynamic model capable of simulating the relevant transient processes. The focus of this paper is on parabolic trough plants, but most findings also help for yield prognosis of other concentration solar technologies.
Solar radiation measurements as most time-series data suffer from interruptions. Gaps may occur d... more Solar radiation measurements as most time-series data suffer from interruptions. Gaps may occur due to loss of power, misalignment, failure of instruments, insufficient cleaning or other reasons. Quality check procedures identify such malfunctioning and mark untrustworthy data by flags. Even well maintained stations with good equipment usually show gaps. In the case of the Indian SRRA network with its 51 stations operating since 2011, typically around 7% of the data are flagged as potentially erroneous or missing. Duration of gaps ranges from few minutes to several days. However many applications such as solar energy performance simulations need continuous time-series. Therefore it is required to fill the measurement gaps with reasonable data. Depending on duration and type of missing parameters various procedures can be used to fill gaps. This paper describes a set of procedures called 'basic gap filling' for solar irradiance, which can be applied without having available additional data. From the over-determined set of global, diffuse and direct radiation a single missing parameter can be calculated from the other two. When two or more solar irradiance components are missing for short gaps, clearness indices are derived to calculate the missing irradiance components. Basic gap filling procedure is applied as part of the SRRA/SolMap projects. The accuracy of the applied basic gap filling methodology is tested and the results show a mean bias of ca. 3 % over GHI, DNI and DHI over all types of gaps.
In the Solar Radiation Resource Assessment (SRRA) project of the Ministry of New and Renewable En... more In the Solar Radiation Resource Assessment (SRRA) project of the Ministry of New and Renewable Energy, India a network of 51 automatic solar radiation monitoring stations have been set up across India. Such a large number of high-quality solar radiation stations with sensitive instruments require efficient procedures for regularly controlling proper operation of each station, the quality of the measured data, and its overall performance. Following best practices for quality assessment tests, such routines are implemented at the SRRA archiving and processing center. Various quality control tests are applied that check the plausibility of data, differentiate trustworthy data from likely erroneous data and flag them accordingly. A data flagging system is implemented to identify, differentiate and quantify different types of errors. These quality-checked, flagged data are then used by routines to create monthly reports and data products. This paper describes the automated quality check system implemented and evaluates the performance of stations since their erection in 2011. This paper also describes first experiments to validate the functionality of the applied quality checks. The quality flag statistics of all 51 stations reveals that some stations are performing very well and others need more attention to improve. In the period from January 2012 to March 2013 on an average over all 51 stations, 92 % of the solar radiation data are classified as correct. Around 4 % of solar radiation data do not pass the coherence test. Tracking errors are observed during 0.3 % of the time averaged over all 51 stations. This analysis helps to further improve the operation of this network and find ways for better-automatized quality checks.
Energy yields of concentrating solar thermal power plants depend strongly on the availability of ... more Energy yields of concentrating solar thermal power plants depend strongly on the availability of beam irradiance.
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