Abstract Battery degradation cost is one of the major concerns when designing energy management strategies of DC microgrids. However, many battery degradation models used in the previous works are over-simplified and the effectiveness of which has not been verified. As a result, this paper presents a comparative study of the impact of battery aging models on energy management of the microgrid. Four popular single factor-based semi-empirical models are investigated while a combined factor-based Combined Arrhenius-Peukert-NREL (CAPN) model is proposed with the best fitting performance compared with the experimental data. The five degradation models are considered as part of the objective function in the particle swarm optimization-based energy management structure of a grid-connect microgrid. The optimized power scheduling and state of charge trajectory of the battery under different single factor-based models exhibit enormous deviations, so as the calculated total costs, which have the maximum error of 63.9% compared with the CAPN model. The application of the studied single factor-based models will also result in 3.5%–12.5% additional actual operating cost under non-optimal conditions. This paper first reveals the significant and unneglectable influence of the simplified degradation models on the microgrid energy management, the abandon of the single factor-based models is also recommended.

中文翻译：

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电池退化模型对并网直流微电网能量管理的影响

摘要 在设计直流微电网能量管理策略时，电池退化成本是主要关注的问题之一。然而，之前工作中使用的许多电池退化模型过于简化，其有效性尚未得到验证。因此，本文对电池老化模型对微电网能量管理的影响进行了比较研究。研究了四种流行的基于单因子的半经验模型，同时提出了一种基于组合因子的组合 Arrhenius-Peukert-NREL (CAPN) 模型，与实验数据相比，该模型具有最佳拟合性能。这五个退化模型被视为并网微电网基于粒子群优化的能源管理结构中目标函数的一部分。不同单因素模型下优化的电池功率调度和充电状态轨迹表现出极大的偏差，因此计算的总成本与CAPN模型相比最大误差为63.9%。在非最佳条件下，所研究的基于单因素的模型的应用还将导致 3.5%–12.5% 的额外实际运营成本。本文首先揭示了简化退化模型对微电网能源管理的重大且不可忽视的影响，同时建议放弃基于单因素的模型。在非最佳条件下，所研究的基于单因素的模型的应用还将导致 3.5%–12.5% 的额外实际运营成本。本文首先揭示了简化退化模型对微电网能源管理的重大且不可忽视的影响，同时建议放弃基于单因素的模型。在非最佳条件下，所研究的基于单因素的模型的应用还将导致 3.5%–12.5% 的额外实际运营成本。本文首先揭示了简化退化模型对微电网能源管理的重大且不可忽视的影响，同时建议放弃基于单因素的模型。