A Grid-Forming Energy Storage System Capacity Planning Method Considering Device Lifetime.
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| Title: | A Grid-Forming Energy Storage System Capacity Planning Method Considering Device Lifetime. |
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| Authors: | Ye, Guisen1 (AUTHOR), Fang, Jingyang1,2 (AUTHOR) jingyangfang@sdu.edu.cn, Wang, Nan1,2 (AUTHOR), Gaogao, Yinan2 (AUTHOR), Sun, Kangyuan2 (AUTHOR) |
| Source: | Energies (19961073). Feb2026, Vol. 19 Issue 3, p639. 22p. |
| Subject Terms: | *Service life, *Energy storage, *Clean energy, *Cost control, *Optimization algorithms, *Grid energy storage, Planning techniques |
| Abstract: | As the use of renewable energy increases, the inertia and frequency stability of the power system continuously decrease, which seriously threatens the stable operation of the power grid. To address the problem of frequency instability, grid-forming energy storage systems (ESS) and associated microgrids have arisen as promising solutions, and their scheduling and capacity planning have become critical issues directly affecting operational costs. However, existing research often ignores battery aging, which may lead to excessive degradation and higher equipment replacement costs. To solve this problem, this paper proposes a grid-forming battery energy storage system capacity planning method that explicitly considers device lifetime, incorporating battery aging into the optimization objective through the rain-flow counting algorithm. Furthermore, an optimization framework combining the genetic algorithm, rain-flow counting method, and branch-and-cut algorithm is developed. To verify the effectiveness of the proposed method, simulations of 12 typical days are conducted on the Gurobi platform to compare the overall cost in five different cases. The results prove that the proposed method can reduce the overall cost by 1.51–6.82% compared to cases where the device lifetime and workload flexibility are not considered, and a good frequency-support performance is achieved. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Abstract: | As the use of renewable energy increases, the inertia and frequency stability of the power system continuously decrease, which seriously threatens the stable operation of the power grid. To address the problem of frequency instability, grid-forming energy storage systems (ESS) and associated microgrids have arisen as promising solutions, and their scheduling and capacity planning have become critical issues directly affecting operational costs. However, existing research often ignores battery aging, which may lead to excessive degradation and higher equipment replacement costs. To solve this problem, this paper proposes a grid-forming battery energy storage system capacity planning method that explicitly considers device lifetime, incorporating battery aging into the optimization objective through the rain-flow counting algorithm. Furthermore, an optimization framework combining the genetic algorithm, rain-flow counting method, and branch-and-cut algorithm is developed. To verify the effectiveness of the proposed method, simulations of 12 typical days are conducted on the Gurobi platform to compare the overall cost in five different cases. The results prove that the proposed method can reduce the overall cost by 1.51–6.82% compared to cases where the device lifetime and workload flexibility are not considered, and a good frequency-support performance is achieved. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 19961073 |
| DOI: | 10.3390/en19030639 |
