Title: Bayesian optimisation for enhanced energy and exergy efficiency in solar multi-generation plants

Authors: Seyed Saeid Razavian; Mojtaba Babaelahi

Addresses: Department of Mechanical Engineering, University of Qom, Qom, Iran ' Department of Mechanical Engineering, University of Qom, Qom, Iran

Abstract: This paper examines a novel concentrated solar multi-generation plant producing electricity, heating, cooling, drying, and hot water. The system employs molten salts (60% NaNO₃, 40% KNO₃) for thermal storage, enabling continuous operation through a solar tower, Rankine cycle, organic Rankine cycle, and air-based cycle. Exergy analysis revealed the solar tower and ORC evaporator contribute 47% of system losses. Using Bayesian multi-objective optimisation with Gaussian process models and expected hypervolume improvement achieved significant enhancements: 10.28% in energy efficiency, 7.50% in exergy efficiency, and 8.85% in net power output.

Keywords: concentrated solar power; CSP; multi-generation system; energy efficiency; exergy analysis; Bayesian optimisation; Gaussian process models; molten salts.

DOI: 10.1504/IJEX.2025.147652

International Journal of Exergy, 2025 Vol.47 No.3, pp.212 - 232

Received: 25 Jan 2025
Accepted: 03 Mar 2025
Published online: 24 Jul 2025 *

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