Studying higher renewable energy penetrations during the electricity generation phase, the Future Renewable Electric Energy Delivery and Management (FREEDM) Systems Center has focused on supporting the battery degradation and cost analysis portion of a commercial 1 MW green energy hub (GEH). Cost analysis and battery degradation modeling will be used as part of a coupled approach and consist of the following software applications: NREL's System Advisor Model (SAM) - for identification of load requirement and summarization of PV productions; COMSOL Multiphysics - for determination of efficient electrochemical battery energy storage system (BESS); and MATLAB – for the implementation of state of charge (SOC), state of health (SOH), and peak shaving algorithms. The GEH will provide for various grid services using 20% renewable energy penetration and a Lithium ion based (Li-ion) BESS. Preliminary results using a LiFePO4 based BESS are presented below. Technical Approach with Preliminary Results The LiFePO4 battery was cycled to determine SOC and SOH using the Versastat 4 Potentiostat with the measured data being used as a baseline for the development of the COMSOL model. SAM The System Advisor Model (SAM) is a model developed by the U.S. Department of Energy and National Renewable Energy Laboratory to analyze sustainable energy systems. The SAM was used to determine the photovoltaic footprint capable of supporting 20% penetration. Fig 1. COMSOL COMSOL Multiphysics is a general-purpose software platform, based on advanced numerical methods, for modeling and simulating physics-based problems. COMSOL was used to model battery degradation and the affect of multiple cycling characteristics in a LiFePO4 cell. Fig 2. MATLAB MATLAB is matrix-based software that uses programming language for numerical computation. MATLAB was used for computation and data analysis of the peak shaving algorithm. Fig 3. Acknowledgement This work was supported by the FREEDM ERC program of the National Science Foundation under award number EEC-08212121. References Dubarry, Matthieu, Liaw, Bor Y. (2009). Identify capacity fading mechanism in a commercial LiFePO4 cell Journal of Power Sources Vol 194, pg 541-549.Kim, Jae-Hun, Woo, Sang C., Park, Min-Sik, Kim, Ki J., Yim, Taeeun, Kim, Jeom-Soo, Kim, Young-Jun. (2013). Capacity Fading Mechanism of LiFePO4 Based Lithium Secondary Batteries for Stationary Energy Storage, Journal of Power Sources Vol 229, pg 190-197.Yang, Ye, Li, Hui, Aichhorn, Andreas, Zheng, Jianping, Greenleaf, Michael. (2014). Sizing Strategy of Distributed Battery Storage System With High Penetration of Photovoltaic for Voltage Regulation and Peak Load Shaving. IEEE Transaction on Smart Grid, Vol 5, No2, pg 982 – 991. Figure 1