Rethinking solar resource assessments in the context of global dimming and brightening

Müller, Björn; Wild, Martin; Driesse, Anton; Behrens, Klaus

doi:10.1016/j.solener.2013.11.013

Cited by 73 publications

(39 citation statements)

References 31 publications

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“…On the other hand, changes in the solar resource are often neglected or considered to be negligible . Recent publications show, however, that this factor does need to be considered .…”

Section: Introductionmentioning

confidence: 99%

Yield predictions for photovoltaic power plants: empirical validation, recent advances and remaining uncertainties

Müller

Hardt

Armbruster

et al. 2015

Progress in Photovoltaics

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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.

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“…On the other hand, changes in the solar resource are often neglected or considered to be negligible . Recent publications show, however, that this factor does need to be considered .…”

Section: Introductionmentioning

confidence: 99%

Yield predictions for photovoltaic power plants: empirical validation, recent advances and remaining uncertainties

Müller

Hardt

Armbruster

et al. 2015

Progress in Photovoltaics

Self Cite

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“…The relative change in SSI over a period of 10 years can be computed by taking the difference between the SSI of the last and first years, and dividing this difference by the mean value of the SSI over the 10 years (Mueller et al, 2014). This operation cannot be performed in our case with reliable results because the period of measurements is too short: 17 years only.…”

Section: Resultsmentioning

confidence: 99%

Yearly changes in surface solar radiation in New Caledonia

2015

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“…In the 1980s and 90s climate modelers began to distinguish a trend of decreasing surface solar radiation in available surface solar radiation records dating back to the 1950s. The rates of the decrease differed by location but were mostly seen as occurring from the 1950s up to the 1980s Muller, 2014). Later studies, focusing on the period from the 1980s to 2000s, identified an apparent shift in the trend to a possible increase in solar irradiance.…”

Section: Acquisition Research Program Graduate School Of Business and Pmentioning

confidence: 98%

“…Morse (2014) found similar patterns for the other nine cities he studied. After further inquiry, he found this trend was a manifestation of a phenomenon known as "global dimming" (Muller, 2014). Global dimming is described as the "decadal decrease of surface solar radiation" (Wild, 2009).…”

Section: Figure 4 Monthly Direct Normal Irradiance (Dni) Interannualmentioning

confidence: 99%

A Robust Design Approach to Cost Estimation: Solar Energy for Marine Corps Expeditionary Operations

Sanchez¹,

Morse²,

Upton³

et al. 2014

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Naval Postgraduate SchoolApproved for public release; distribution is unlimited.Prepared for the Naval Postgraduate School, Monterey, CA 93943. Report Documentation PageForm Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Life Cycle Cost (LCC) assessments are of interest during the design phase for new systems. These often involve costs that must be estimated from a variety of different sub-models, including cost models constructed from historical data, forecast models that attempt to predict future economic conditions, and economy-of-scale models that impact production schedules, and more. When these disparate models are put together to obtain an overall cost model, many of these individual sources of uncertainty end up being aggregated or ignored. Consequently, the cost estimates may not provide program managers with appropriate assessments of the risk and overall variability of the new systems. We propose a structured approach for obtaining robust LCC estimates by taking into account a broad set of environmental noise conditions. This will enable program managers to better understand the uncertainty in their overall estimates, and to identify any decision factor combinations that result in both low costs and low cost variability. This may provide guidance on which of the many potential uncertainty sources require close monitoring, and which can safely be disregarded. We illustrate this approach with a model the USMC is evaluating for use in cost/benefit analysis of alternative energy systems. The research presented in this report was supported by the Acquisition Research Program of the Graduate School of Business & Public Policy at the Naval Postgraduate School.To request defense acquisition research, to become a research sponsor, or to print additional copies of reports, please contact any of the staff listed on the Acquisition Research Program website (www.acquisitionresearch.net) Acquisition Research Program Graduate School of Business & Public Policy-iNaval Postgraduate School AbstractLife Cycle Cost (LCC) assessments are of interest during the design phase for new systems. These often involve costs that must be estimated from a variety of different sub-models, including cost models constructed from historical data, forecast models that attempt to predict future economic conditions, and economy-of-scale models that impact production schedules, and more. When these disparate models are put together to obtain an overall cost model, many of these individual sources of uncertainty end up being aggregated or ignored. Consequently, the cost estimates may not provide program managers with appropriate assessments of the risk and overall variability of the new systems. We propose a structured approach for obtaining robust LCC estimates by taking into account a broad set of enviro...

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Rethinking solar resource assessments in the context of global dimming and brightening

Cited by 73 publications

References 31 publications

Yield predictions for photovoltaic power plants: empirical validation, recent advances and remaining uncertainties

Yield predictions for photovoltaic power plants: empirical validation, recent advances and remaining uncertainties

Yearly changes in surface solar radiation in New Caledonia

A Robust Design Approach to Cost Estimation: Solar Energy for Marine Corps Expeditionary Operations

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