Article, 2024

Techno-economic Assessment and Optimization of a Solar-Driven Power and Hydrogen Co-generation Plant Retrofitted with Enhanced Energy Storage

Energy Conversion and Management, ISSN 1879-2227, 0196-8904, Volume 301, Page 118004, 10.1016/j.enconman.2023.118004

Contributors

Khodaei, Ehsan [1] Yari, Mortaza 0000-0001-7853-8175 (Corresponding author) [1] Nami, Hossein 0000-0002-0875-1752 [2] Goravanchi, Farinaz [3]

Affiliations

  1. [1] University of Tabriz
  2. [NORA names: Iran; Asia, Middle East];
  3. [2] University of Southern Denmark
  4. [NORA names: SDU University of Southern Denmark; University; Denmark; Europe, EU; Nordic; OECD];
  5. [3] Sahand University of Technology
  6. [NORA names: Iran; Asia, Middle East]

Abstract

Pioneering solar-driven power and co-generation facilities stands as a crucial stride toward decarbonizing energy systems. Moreover, the production of green hydrogen serves as the cornerstone of decarbonized energy systems. This study evaluates a solar-driven co-generation plant for power and hydrogen production employing the vanadium-chlorine cycle. The plant is integrated with a thermal storage system of solid materials as a packed bed to increase the capacity factor. Three cases are studied based on energy storage materials. The first case uses alumina, while the second and third cases utilize steel slag with varying compounds. Following an extensive sensitivity analysis, an artificial neural network is formulated to subject each case to three-objective optimization using a genetic algorithm. Moreover, Seville in Spain is selected as the designated case study, and real-world solar availability data is employed to enhance the authenticity and realism of the results. Results show using steel slag as an energy storage material instead of alumina reduces the levelized cost of energy and the cost of thermal energy storage units by 14 and 69%, respectively. From both economic and environmental perspectives, the second case emerges as the most favorable option. Through the implementation of a 36.3-hectare solar farm in Seville, the second case generates 38.5 GWh electricity and 2.1 kton hydrogen with a cost of 189 USD/MWh and 7.2 USD/kg, respectively, factoring in expenses for hydrogen compression and storage facilities. This case has the potential to reduce Spain's CO2 emissions by 51 kton per year.

Keywords

Available data, CO2 emissions, Seville, Spain, USD/MWh, algorithm, alumina, analysis, artificial neural network, assessment, authentication, bed, capacity, capacity factor, case study, cases, co-generation, co-generation facilities, co-generation plant, compounds, compression, cornerstone, cost, cost of energy, cycle, data, decarbonized energy system, electricity, emission, energy, energy storage, energy storage materials, energy storage unit, energy systems, enhanced energy storage, enhancement, environmental perspective, expense, facilities, factors, farms, favorable option, genetic algorithm, green hydrogen, hydrogen, hydrogen compression, hydrogen production, implementation, levelized cost, levelized cost of energy, materials, network, neural network, optimization, options, packed bed, perspective, plants, potential, power, production, production of green hydrogen, realism, results, sensitivity, sensitivity analysis, slag, solar farms, solar-driven, solid materials, steel, steel slag, storage, storage facilities, storage materials, storage system, storage unit, stride, study, system, techno-economic assessment, thermal energy storage unit, thermal storage system, units, years

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