Dynamic simulation model of a parabolic trough collector system with concrete thermal energy storage for process steam generation

Sattler, Johannes; Alexopoulos, Spiros; Caminos, Ricardo Alexander Chico; Mitchell, John B.; Ruiz, Victor; Kalogirou, Soteris A.; Ktistis, Panayiotis; Boura, Cristiano Teixeira; Herrmann, Ulf

doi:10.1063/1.5117663

Cited by 9 publications

(2 citation statements)

References 5 publications

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“…The used weather forecast data contains cloud cover data for the three altitudes low, medium and high. The relation between the calculated DNI and the described parameters is shown in equation (1).…”

Section: Forecast Tool Developmentmentioning

confidence: 99%

“…1 shows a photograph of the PTC plant with C-TES which is currently being upgraded with smart features in project S3. The PTC system provides solar generated process steam for KEAN Soft Drinks Ltd. More details on the PTC system and C-TES are described in [1], [2] and [3]. The DNI forecast data as well as other parameters will be used by a main control unit (MCU), which will be developed and realised in the S3 project by project partner Protarget AG, such that smarter decisions for an optimised control strategy of the PTC plant and C-TES for the next 24 hours can be made (the relevant forecast time is 6 a.m. local time in Cyprus until after sunset).…”

Section: Introductionmentioning

confidence: 99%

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DNI Forecast Tool for the Smart Operation of a Parabolic Trough Collector System With Concrete Thermal Energy Storage

Sattler,

Atti,

Alexopoulos

et al. 2024

SolarPACES Conf Proc

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This work presents a basic forecast tool for predicting direct normal irradiance (DNI) in hourly resolution, which the Solar-Institut Jülich (SIJ) is developing within a research project. The DNI forecast data shall be used for a parabolic trough collector (PTC) system with a concrete thermal energy storage (C-TES) located at the company KEAN Soft Drinks Ltd in Limassol, Cyprus. On a daily basis, 24-hour DNI prediction data in hourly resolution shall be automatically produced using free or very low-cost weather forecast data as input. The purpose of the DNI forecast tool is to automatically transfer the DNI forecast data on a daily basis to a main control unit (MCU). The MCU automatically makes a smart decision on the operation mode of the PTC system such as steam production mode and/or C-TES charging mode. The DNI forecast tool was evaluated using historical data of measured DNI from an on-site weather station, which was compared to the DNI forecast data. The DNI forecast tool was tested using data from 56 days between January and March 2022, which included days with a strong variation in DNI due to cloud passages. For the evaluation of the DNI forecast reliability, three categories were created and the forecast data was sorted accordingly. The result was that the DNI forecast tool has a reliability of 71.4 % based on the tested days. The result fulfils SIJ’s aim to achieve a reliability of around 70 %, but SIJ aims to still improve the DNI forecast quality.

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Section: Forecast Tool Developmentmentioning

confidence: 99%