Session: 30-05 Solar Thermal Systems

Paper Number: 124083

124083 - Simultaneous Design Optimization of Binary CO2-Mixture-Based Power Cycles for Concentrated Solar Power Applications 

This paper introduces a novel approach for optimizing binary CO2-mixture-based both condensing and non-condensing power cycles for high-temperature CSP applications, featuring a simple recuperative layout. It synchronously optimizes cycle design parameters, dopant selection, and working fluid composition. The study investigates six scenarios, encompassing two maximum cycle temperatures: 550°C for conventional solar power towers and 700°C for advanced systems, across three design dry bulb temperatures: 30°C, 35°C, and 40°C. The investigated dopants include SO2, C6F6, TiCl4, a non-organic dopant (NOD), and C2H3N. Notably, SO2, TiCl4, and NOD are used exclusively for the 700°C scenarios, while all five dopants are used for the 550°C temperature level. The multi-objective optimization focuses on both thermal efficiency and specific work. The methodology allows for expanding the dopant list to include any interesting dopant, as long as their thermophysical properties are captured in 3D look-up tables using accurate Equation of State (EoS) and binary interaction parameters (BIP).

To ensure accurate modeling of the novel fluid properties, the Peng-Robinson Equation of State (EoS) is employed, alongside calibrated binary interaction parameters (BIP) sourced from existing literature. These properties are stored in 3-dimensional look-up tables and utilized in a steady-state in-house MATLAB code for simulating the power cycle's techno-economic performance, coupled with multi-objective optimization. Results show that including specific work as an optimization objective enhances cost effectiveness by minimizing power block costs, helping to select optimized designs while retaining high efficiencies. Additionally, the results indicate that considering ΔT could further reduce potential thermal energy storage (TES) costs, increasing the cost competitiveness of CO2-mixture-based cycles to improve their chances in market entry.

The novelty of this study lies in its methodology, which enables the simultaneous exploration of the best novel dopant selection, its composition, and the optimal cycle design parameters through the use of a multi-objective genetic algorithm. The optimization process results show distinct clustering of dopants in the Pareto fronts, with each mixture demonstrating unique performance characteristics across different temperature levels. The cost analysis of selected designs reveals the potential of blend-based CO2 cycles in reducing specific costs, contributing to more cost-effective and thermodynamically efficient CSP applications.

Presenting Author: Balkan Mutlu Teesside University - NET Zero Industry Innovation Centre

Presenting Author Biography: Balkan is a PhD student in Energy Department at Teesside University, Net Zero Industry Innovation Centre. His PhD focuses on the techno-economic optimization and integration of advanced CO2-blend power cycles for CSP applications within the DESOLINATION project. He holds a BSc and an MSc in Mechanical Engineering from Middle East Technical University, Türkiye. His other research interests include optimizing and modeling renewable energy systems, performing techno-economic studies, and hybridizing renewable energy sources, such as geothermal, solar thermal, biomass, and solar PV.

Authors:

Balkan Mutlu Teesside University - NET Zero Industry Innovation Centre
Kumar Patchigolla Teesside University - NET Zero Industry Innovation Centre
Dhinesh Thanganadar UK Atomic Energy Authority