A new study published on arXiv explores the hidden costs of battery degradation in home energy management systems (HEMS) that solely optimize for energy costs. Researchers used a mixed-integer linear programming model with data from the REFIT dataset to analyze the sensitivity of degradation costs across various battery and photovoltaic (PV) sizes. The findings indicate that degradation costs can significantly exceed energy cost savings, by up to 1,060% in some scenarios, highlighting the need for degradation-aware control formulations in HEMS. AI
RANK_REASON Academic paper published on arXiv detailing a new study and its findings. [lever_c_demoted from research: ic=1 ai=0.4]
- battery storage power station
- Hems
- Mixed Integer Linear Programming
- model predictive control
- Naumann
- photovoltaics
- rEFIt
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