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Battery degradation is a complex physicochemical process that strongly depends on operating conditions and environment. We present a model-based analysis of lithium-ion battery degradation in smart microgrids, in particular, a single-family house and an office tract with photovoltaics generator. We use a multi-scale multi-physics model of a graphite/lithium iron phosphate (LiFePO4, LFP) cell including SEI formation as ageing mechanism. The cell-level model is dynamically coupled to a system-level model consisting of photovoltaics, inverter, power consumption profiles, grid interaction, and energy management system, fed with historic weather data. The behavior of the cell in terms of degradation propensity, performance, state of charge and other internal states is predicted over an annual operation cycle. As result, we have identified a peak in degradation rate during the battery charging process, caused by charging overpotentials. Ageing strongly depends on the load situation, where the predicted annual capacity fade is 1.9 % for the single-family house and only 1.3 % for the office tract.
Battery degradation is a complex physicochemical process that strongly depends on operating conditions. We present a model-based analysis of lithium-ion battery degradation in a stationary photovoltaic battery system. We use a multi-scale multi-physics model of a graphite/lithium iron phosphate (LiFePO4, LFP) cell including solid electrolyte interphase (SEI) formation. The cell-level model is dynamically coupled to a system-level model consisting of photovoltaics (PV), inverter, load, grid interaction, and energy management system, fed with historic weather data. Simulations are carried out for two load scenarios, a single-family house and an office tract, over annual operation cycles with one-minute time resolution. As key result, we show that the charging process causes a peak in degradation rate due to electrochemical charge overpotentials. The main drivers for cell ageing are therefore not only a high state of charge (SOC), but the charging process leading towards high SOC. We also show that the load situation not only influences system parameters like self-sufficiency and self-consumption, but also has a significant impact on battery ageing. We assess reduced charge cut-off voltage as ageing mitigation strategy.