A multi-objective optimization algorithm-based capacity scheduling method for photovoltaic power hybrid energy storage systems
In this study, the combination of crossover algorithm and particle swarm optimization—crossover algorithm-particle swarm optimization (CS-PSO) algorithm—to optimize photovoltaic hybrid energy storage scheduling, improving global search and convergence speed, is discussed. The new method reduces ener...
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| Format: | Article |
| Language: | English |
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AIP Publishing LLC
2024-12-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0234096 |
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| author | Shuaijie Wang Xin Guan Shu Liu |
| author_facet | Shuaijie Wang Xin Guan Shu Liu |
| author_sort | Shuaijie Wang |
| collection | DOAJ |
| description | In this study, the combination of crossover algorithm and particle swarm optimization—crossover algorithm-particle swarm optimization (CS-PSO) algorithm—to optimize photovoltaic hybrid energy storage scheduling, improving global search and convergence speed, is discussed. The new method reduces energy storage costs and energy losses, ensures supply–demand balance and interaction power constraints, and maintains population diversity through cross-search. The CS-PSO algorithm introduces battery state of charge optimization for energy storage scheduling, improving global search and convergence speed, and obtaining accurate multi-objective scheduling results. The experiment shows that the optimal configuration for photovoltaic energy storage is 10 045 batteries + 687 244 supercapacitors, with a cost of 3.452 × 105 yuan and an energy loss of less than 5%. CS-PSO has similar costs but lower losses and faster convergence compared to traditional methods. |
| format | Article |
| id | doaj-art-8922dc0c221f48c38debb82bb77b879f |
| institution | Kabale University |
| issn | 2158-3226 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | AIP Advances |
| spelling | doaj-art-8922dc0c221f48c38debb82bb77b879f2025-01-02T17:23:45ZengAIP Publishing LLCAIP Advances2158-32262024-12-011412125308125308-910.1063/5.0234096A multi-objective optimization algorithm-based capacity scheduling method for photovoltaic power hybrid energy storage systemsShuaijie WangXin GuanShu LiuIn this study, the combination of crossover algorithm and particle swarm optimization—crossover algorithm-particle swarm optimization (CS-PSO) algorithm—to optimize photovoltaic hybrid energy storage scheduling, improving global search and convergence speed, is discussed. The new method reduces energy storage costs and energy losses, ensures supply–demand balance and interaction power constraints, and maintains population diversity through cross-search. The CS-PSO algorithm introduces battery state of charge optimization for energy storage scheduling, improving global search and convergence speed, and obtaining accurate multi-objective scheduling results. The experiment shows that the optimal configuration for photovoltaic energy storage is 10 045 batteries + 687 244 supercapacitors, with a cost of 3.452 × 105 yuan and an energy loss of less than 5%. CS-PSO has similar costs but lower losses and faster convergence compared to traditional methods.http://dx.doi.org/10.1063/5.0234096 |
| spellingShingle | Shuaijie Wang Xin Guan Shu Liu A multi-objective optimization algorithm-based capacity scheduling method for photovoltaic power hybrid energy storage systems AIP Advances |
| title | A multi-objective optimization algorithm-based capacity scheduling method for photovoltaic power hybrid energy storage systems |
| title_full | A multi-objective optimization algorithm-based capacity scheduling method for photovoltaic power hybrid energy storage systems |
| title_fullStr | A multi-objective optimization algorithm-based capacity scheduling method for photovoltaic power hybrid energy storage systems |
| title_full_unstemmed | A multi-objective optimization algorithm-based capacity scheduling method for photovoltaic power hybrid energy storage systems |
| title_short | A multi-objective optimization algorithm-based capacity scheduling method for photovoltaic power hybrid energy storage systems |
| title_sort | multi objective optimization algorithm based capacity scheduling method for photovoltaic power hybrid energy storage systems |
| url | http://dx.doi.org/10.1063/5.0234096 |
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