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Multi-objective optimisation of a thermal-storage PV-CSP-wind hybrid power system in three operation modes.

Authors :
Liu, Hongtao
Zhai, Rongrong
Patchigolla, Kumar
Turner, Peter
Yu, Xiaohan
Wang, Peng
Source :
Energy. Dec2023, Vol. 284, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

The hybrid renewable energy system based on concentrated solar power (CSP) technology has been demonstrated as a promising approach to utilise renewable energy. To combine the configuration and operation with practical application scenarios, this study investigates three different operation modes of the hybrid system which consists of one or more components of a CSP power plant, a thermal energy storage system, photovoltaic (PV) panels, wind turbines, batteries and electric heaters. A multi-objective optimisation for the capacity parameters of subsystems is conducted for three operation modes and two typical locations, considering the actual power demand and electricity prices. Results show that cooperating with the given CSP plant, the simultaneous development of PV panels, wind turbines and batteries is recommended in Delingha, while in Lhasa, the improvement relies more on the expansion of PV panels and batteries. By providing 31.50%–38.72% of the total power, the CSP subsystem contributes significantly to providing reliable electricity in fluctuating weather conditions and at night. And 20.58–59.85 GWh of excess electricity is reused through electric heaters instead of being wasted. Furthermore, the operation in local consumption mode shows the best resilient to uncertainty of the meteorological conditions, with the deviation within 1% under forecast error of 5%–20%. • Optimal configurations are obtained for three operation modes in two locations. • Performance curves in local consumption mode show consistency across sites. • Similar trends but higher profit is obtained in VPP mode compared to sales mode. • Electric heaters enable 20.58–59.85 GWh of electricity reused instead of wasted. • A deviation of 1 % is seen in local consumption mode for forecast errors of 5%–20 %. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
284
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
173322127
Full Text :
https://doi.org/10.1016/j.energy.2023.129255