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Energies
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Solar-Powered Combined Cooling, Heating, and Power Energy System with Phase-Change Material and Water Electrolysis: Thermo-Economic Assessment and Optimization

Authors: Koorosh Aieneh; orcid Sadegh Mehranfar;
Sadegh Mehranfar
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Harvested from ORCID Public Data File

Sadegh Mehranfar in OpenAIRE
Mohammad Yazdi Sotoude; Shayan Sadeghi; orcid Amin Mahmoudzadeh Andwari;
Amin Mahmoudzadeh Andwari
ORCID
Harvested from ORCID Public Data File

Amin Mahmoudzadeh Andwari in OpenAIRE

Solar-Powered Combined Cooling, Heating, and Power Energy System with Phase-Change Material and Water Electrolysis: Thermo-Economic Assessment and Optimization

Abstract

A solar-powered combined cooling, heating, and power (CCHP) plant integrated with a water electrolysis unit is investigated in terms of energy, exergy, and exergo-economic (3E) assessments. A comprehensive parametric study and optimization is conducted following the thermodynamic and exergo-economic assessment of the proposed system to evaluate the key performance parameters of the system for efficiency and economic factors. This system employs a heliostat field and a receiver tower by taking advantage of thermal energy from the sun and produces a continuous energy supply with an integrated phase-change material (PCM) tank to store the heat. In addition, a supercritical CO2 Rankine cycle (RC), an ejector refrigeration cooling (ERC) system, and a PEM water electrolyzer are coupled to produce cooling, heating, power, and hydrogen. Thermodynamic analysis indicates that the system exergy efficiency and energy efficiency are improved to 33.50% and 40.61%, respectively, while the total cost rate is 2875.74 USD/h and the total product cost per exergy unit is 25.65 USD/GJ. Additionally, the system produces a net generated power, heating load, and cooling load of 11.70, 13.92, and 2.60 MW, respectively, and a hydrogen production rate of 12.95 g/s. A two-objective optimization approach utilizing a non-dominated sorting genetic algorithm (NSGA) was performed, demonstrating that the system’s ideal design point offers a cost rate of 1263.35 USD/h and an exergetic efficiency of 34.17%.

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