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Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary Algorithms

Author

Listed:
  • Chenxiao Ji

    (Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Xueying Nie

    (Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Shichao Chen

    (Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China)

  • Maosong Cheng

    (Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Zhimin Dai

    (Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Combining energy storage with base-load power sources offers an effective way to cover the fluctuation of renewable energy. This study proposes a nuclear–solar hybrid energy system (NSHES), which integrates a small modular thorium molten salt reactor (smTMSR), concentrating solar power (CSP), and thermal energy storage (TES). Two operation modes are designed and analyzed: constant nuclear power (mode 1) and adjusted nuclear power (mode 2). The nondominated sorting genetic algorithm II (NSGA-II) is applied to minimize both the deficiency of power supply probability (DPSP) and the levelized cost of energy (LCOE). The decision variables used are the solar multiple (SM) of CSP and the theoretical storage duration (TSD) of TES. The criteria importance through inter-criteria correlation (CRITIC) method and the technique for order preference by similarity to ideal solution (TOPSIS) are utilized to derive the optimal compromise solution. The electricity curtailment probability (ECP) is calculated, and the results show that mode 2 has a lower ECP compared with mode 1. Furthermore, the configuration with an installed capacity of nuclear and CSP (100:100) has the lowest LCOE and ECP when the DPSP is satisfied with certain conditions. Optimizing the NSHES offers an effective approach to mitigating the mismatch between energy supply and demand.

Suggested Citation

  • Chenxiao Ji & Xueying Nie & Shichao Chen & Maosong Cheng & Zhimin Dai, 2025. "Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary Algorithms," Energies, MDPI, vol. 18(9), pages 1-22, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:9:p:2189-:d:1642100
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    References listed on IDEAS

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