A study on the impact of time resolution in solar data on the performance modelling of CSP plants

Mehdi Aghaei Meybodi, Lourdes Ramirez Santigosa and Andrew C. Beath

Renewable Energy, 2017, vol. 109, issue C, 551-563

Abstract: Availability of long term solar data and the quality of available data is usually an obstacle to the development of proposals for new concentrating solar power plants. Typical or representative meteorological years using hourly solar and weather data that has been selected to match long-term averages are often used to perform the preliminary design and performance assessment of solar power plants. Although the use of this data is convenient due to the reduced computational requirements in plant optimization, it may result in a simplistic prediction of plant operations that does not reflect the real plant performance by neglecting the impact of short-term variability in solar irradiance and the variations in weather and available solar energy for different years. This study conducts a systematic analysis of the influence of multi-year data sets with a range of different time step sizes (5, 15, 30 and 60 min) and thermal storage capacities (4, 8 and 12 h) using the physical parabolic trough with molten salt storage model in NREL’s System Advisor Model. Results indicate that the appropriateness of different step sizes is likely to vary depending on the purpose of the modelling; however, sensitivity to step size is reduced for larger storage capacities.

Keywords: Solar data time resolution; Parabolic trough solar plant; Stochastic analysis; Levelized cost of energy (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148117302057
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:109:y:2017:i:c:p:551-563

DOI: 10.1016/j.renene.2017.03.024

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().