Case Studies on the Use of Solar Irradiance Forecast for Optimized Operation Strategies of Solar Thermal Power Plants

Wittmann, Michael; Breitkreuz, Hanne-Katarin; Schroedter-Homscheidt, Marion; Eck, Markus

doi:10.1109/jstars.2008.2001152

Cited by 90 publications

(47 citation statements)

References 9 publications

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“…Best results were achieved by both the ECMWF model and our method in mainland Spain (35%-45% of rRMSE if the total AOD from MACC is used). The scores shown here are consistent with the results presented by Wittmann et al (2008) using the method described in Breitkreuz et al (2009), and also with the verification of ECMWF in Schroedter-Homscheidt et al (2017). Using the 1-day persistence gave worse results for all the sites.…”

Section: B Annual Scoressupporting

confidence: 92%

A Postprocessing Methodology for Direct Normal Irradiance Forecasting Using Cloud Information and Aerosol Load Forecasts

Casado-Rubio

Revuelta

Postigo

et al. 2017

Journal of Applied Meteorology and Climatology

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A method for direct normal irradiance (DNI) forecasting for specific sites is proposed. It is based on the combination of a numerical weather prediction (NWP) model, which provides cloud information, with radiative transfer simulations fed with external aerosol forecasts. The NWP model used is the ECMWF Integrated Forecast System, and the radiative transfer information has been obtained from the Library of Radiative Transfer (libRadtran). Two types of aerosol forecasts have been tested: the global Monitoring Atmospheric Composition and Climate (MACC) model, which predicts five major components of aerosols, and the Dust Regional Atmospheric Model (BSC-DREAM8b) added to a fixed background calculated as the 20th percentile of the monthly mean of AERONET 2.0 observations from a different year. The methodology employed is valid for all meteorological situations, providing a stable and continuous DNI curve. The performance of the combined method has been evaluated against DNI observations and compared with the pure ECMWF forecasts at eight locations in the southern half of mainland Spain and the Canary Islands, which received high loadings of African dust for 2013 and 2014. Results for 1-day forecasts are presented. Although clouds play a major role, aerosols have a significant effect, but at shorter time scales. The combination of ECMWF and MACC forecasts gives the best global results, improving the DNI forecasts in events with high aerosol content. The regional BSC-DREAM8b yields good results for some extremely high dust conditions, although more reliable predictions, valid for any aerosol conditions, are provided by the MACC model.

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Section: B Annual Scoressupporting

confidence: 92%

A Postprocessing Methodology for Direct Normal Irradiance Forecasting Using Cloud Information and Aerosol Load Forecasts

Casado-Rubio

Revuelta

Postigo

et al. 2017

Journal of Applied Meteorology and Climatology

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“…Some of them use statistical approaches to simulate the forecast uncertainty [4], but these usually do not represent well the real statistical distribution of the error observed between forecast and observation. Others use real forecasted DNI time series for few sample days, analyzing in detail specific plant behavior and optimization strategies [3,5]. This work tries to fill the gap by implementing weather observation measured with ground stations along with weather forecast data produced for the same location from a forecast provider.…”

Section: Introductionmentioning

confidence: 99%

Addressing forecast uncertainty impact on CSP annual performance

Ferretti

Hogendijk

Aga

et al. 2017

AIP Conference Proceedings

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Abstract. This work analyzes the impact of weather forecast uncertainty on the annual performance of a Concentrated Solar Power (CSP) plant. Forecast time series has been produced by a commercial forecast provider using the technique of hindcasting for the full year 2011 in hourly resolution for Ouarzazate, Morocco. Impact of forecast uncertainty has been measured on three case studies, representing typical tariff schemes observed in recent CSP projects plus a spot market price scenario. The analysis has been carried out using an annual performance model and a standard dispatch optimization algorithm based on dynamic programming. The dispatch optimizer has been demonstrated to be a key requisite to maximize the annual revenues depending on the price scenario, harvesting the maximum potential out of the CSP plant. Forecasting uncertainty affects the revenue enhancement outcome of a dispatch optimizer depending on the error level and the price function. Results show that forecasting accuracy of direct solar irradiance (DNI) is important to make best use of an optimized dispatch but also that a higher number of calculation updates can partially compensate this uncertainty. Improvement in revenues can be significant depending on the price profile and the optimal operation strategy. Pathways to achieve better performance are presented by having more updates both by repeatedly generating new optimized trajectories but also more often updating weather forecasts. This study shows the importance of working on DNI weather forecasting for revenue enhancement as well as selecting weather services that can provide multiple updates a day and probabilistic forecast information.

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“…Regarding CSP and direct normal irradiance (DNI), Wittmann et al (2008) and Kraas, Schroedter-Homscheidt, and Madlener et al (2013) use case studies to show the economic benefit of supplying DNI forecasts for optimized operation strategies of CSP plants. Schroedter-Homscheidt et al (2013) evaluated the aerosol forecasting requirements for forecasts of concentrating solar electricity production.…”

Section: Introductionmentioning

confidence: 99%

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Second Edition

2017

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Designing, financing, and operating successful solar heating, concentrating solar power, and photovoltaic systems requires reliable information about the solar resource available and its variability over time. In the past, seasonal and daily variability has been studied and understood; however, with new solar technologies becoming more important in energy supply grids, small time-scale effects are critical to successful deployment of these important low carbon technologies. A vital part of the bankability of solar projects is to understand the variability of the solar resource so that supply and storage technologies can be optimized.This handbook is the result of 10 years of international collaboration carried out by experts from the International Energy Agency's (IEA's) Solar Heating and Cooling (SHC), Solar PACES, and Photovoltaic Power Systems Technology Collaboration Programmes. Under IEA SHC Task 46: Solar Resource Assessment and Forecasting, experts from 11 countries produced information products and best practices on solar energy resources that will greatly benefit project developers and system operators as well as assist policymakers in advancing renewable energy programs worldwide.Meteorologists, mathematicians, solar technology specialists, and other key solar resource experts from around the world joined forces to further our understanding of the sun's temporal and spatial variability through benchmarking satellite-derived solar resource data and solar forecasts, developing best practices for measuring the solar resource, and conducting research to improve satellite-based algorithms. The results of IEA SHC Task 46 are useful to a wide range of users of solar heating and cooling, photovoltaics, and concentrating solar power systems and of building developers and owners as well as anyone else who needs to understand and predict sunlight for agricultural or other purposes.The earlier edition of the handbook, which was published in 2015, is used worldwide as a reference for each stage of a solar energy project. Since that time, there has been substantial growth in the interest in high-quality "bankable" solar resource data. This revision adds significant new methods so it will be even more useful.This publication is a summary that details the fundamentals of solar resources as well as captures the state of the art. For those wanting more depth, it also provides the references where more detailed information can be found.I would like to acknowledge the leadership of the National Renewable Energy Laboratory and express appreciation to the U.S. Department of Energy for producing the handbook and incorporating results from IEA SHC Task 46. Ken Guthrie Chair, IEA Solar Heating and Cooling Technology Collaboration Programme June 2017This report is available at no cost from the National Renewable Energy Laboratory at www.nrel.gov/publications. Preface Dave Renné Dave Renné Renewables, LLCAs the world looks for carbon-free sources to meet final energy demand associated with heat, electrical power, and transport, ...

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Case Studies on the Use of Solar Irradiance Forecast for Optimized Operation Strategies of Solar Thermal Power Plants

Cited by 90 publications

References 9 publications

A Postprocessing Methodology for Direct Normal Irradiance Forecasting Using Cloud Information and Aerosol Load Forecasts

A Postprocessing Methodology for Direct Normal Irradiance Forecasting Using Cloud Information and Aerosol Load Forecasts

Addressing forecast uncertainty impact on CSP annual performance

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Second Edition

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