Design of A Simplified Hierarchical Bayesian Network for Residential Energy Storage Degradation

Khan K., Hossen T., Savasci A., Gauchia L., Paudyal S.

2019 IEEE Power and Energy Society General Meeting, PESGM 2019, Georgia, United States Of America, 4 - 08 August 2019, vol.2019-August identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 2019-August
  • Doi Number: 10.1109/pesgm40551.2019.8973603
  • City: Georgia
  • Country: United States Of America
  • Keywords: Batteries, Bayesian Networks, Probabilistic aging model, Residential, Smart Home
  • Abdullah Gül University Affiliated: No


In this paper a simplified hierarchical Bayesian network (BN) is developed to estimate residential energy storage degradation in terms of capacity fade. The BN is trained using experimental results of lithium iron phosphate batteries. Residential energy storage capacity fade was estimated for multiple cases. These cases originated from a smart home energy management system (SHEMS). The cases reflect that capacity fade of the residential energy storage depends on SHEMS architecture, power consumption limits and electric vehicle schedule.