Modelling of Solar Thermal Electricity Plants in the POSYTYF Research Project for an Extensive Integration of Renewable Energy Sources
DOI:
https://doi.org/10.52825/solarpaces.v1i.716Keywords:
Solar Thermal Electricity Plant Simulation Model, Parabolic Trough, Thermal Energy Storage, Renewable Energy Sources, Dynamic Virtual Power Plant, Grid IntegrationAbstract
This article presents a simplified simulation model of a concentrated solar thermal power plant developed in the framework of the European research project POSYTYF (POwering SYstem flexibiliTY in the Future through RES). Increasing the share of Renewable Energy Sources (RES) in modern power grids is of critical importance for the transformation of the energy markets worldwide. However, the stability of the grid and the limited participation in ancillary services of RES limit their use, especially when high penetration is expected from them. A solution to overcome these issues is to increase the share of so-called dispatchable RES (hydropower, biomass, concentrating solar thermal power). The main objective of the POSYTYF project is to group several renewable and non-renewable energy sources into a Dynamic Virtual Power Plant (DVPP). The simplified simulation model of a parabolic-trough solar thermal power plant developed consists of sub-models for the solar field, thermal energy storage system and power block and it has been validated with real DNI profiles and production data of a commercial STE plant in Spain. The differences between the simulation and real data of daily net production for the days analysed are lower than 1%.
Parts of this paper were published as journal article “Using time-windowed solar radiation profiles to assess the daily uncertainty of solar thermal electricity production forecasts”, Journal of Cleaner Production, Volume 379, Part 2, 2022. Mario Biencinto, Lourdes González, Loreto Valenzuela (https://doi.org/10.1016/j.jclepro.2022.134821).
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Copyright (c) 2024 Lourdes González , Mario Biencinto, Loreto Valenzuela, Luis Arribas, Jesús Polo
This work is licensed under a Creative Commons Attribution 4.0 International License.
Funding data
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Horizon 2020
Grant numbers 883985
