Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary Algorithms
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 th...
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MDPI AG
2025-04-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/9/2189 |
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| author | Chenxiao Ji Xueying Nie Shichao Chen Maosong Cheng Zhimin Dai |
| author_facet | Chenxiao Ji Xueying Nie Shichao Chen Maosong Cheng Zhimin Dai |
| author_sort | Chenxiao Ji |
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| description | 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. |
| format | Article |
| id | doaj-art-eab657b1330e4255a3007f71667fde13 |
| institution | DOAJ |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-eab657b1330e4255a3007f71667fde132025-08-20T02:59:11ZengMDPI AGEnergies1996-10732025-04-01189218910.3390/en18092189Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary AlgorithmsChenxiao Ji0Xueying Nie1Shichao Chen2Maosong Cheng3Zhimin Dai4Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, ChinaShanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, ChinaShanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, ChinaShanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, ChinaShanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, ChinaCombining 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.https://www.mdpi.com/1996-1073/18/9/2189nuclear and solar hybrid energy systemmulti-objective optimizationconcentrating solar powerthermal energy storagelevelized cost of electricitysolar multiple |
| spellingShingle | Chenxiao Ji Xueying Nie Shichao Chen Maosong Cheng Zhimin Dai Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary Algorithms Energies nuclear and solar hybrid energy system multi-objective optimization concentrating solar power thermal energy storage levelized cost of electricity solar multiple |
| title | Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary Algorithms |
| title_full | Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary Algorithms |
| title_fullStr | Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary Algorithms |
| title_full_unstemmed | Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary Algorithms |
| title_short | Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary Algorithms |
| title_sort | optimization of a nuclear csp hybrid energy system through multi objective evolutionary algorithms |
| topic | nuclear and solar hybrid energy system multi-objective optimization concentrating solar power thermal energy storage levelized cost of electricity solar multiple |
| url | https://www.mdpi.com/1996-1073/18/9/2189 |
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