Accurate and economical sizing of stand-alone power system components, including batteries, has been an active area of microgrid research, but current control methods do not make them economically feasible.¹ Typically, batteries are treated as a black box that does not account for their internal states in current microgrid simulation and control algorithms.² This might lead to under-utilization and over-stacking of batteries. In contrast, detailed physics-based battery models, accounting for internal states, can save a significant amount of energy and cost, utilizing batteries with maximized life and usability.

We have previously shown the implementation of the optimization and benefits of using the MPPT controller algorithm and physics-based battery model along with other microgrid components.³ In this talk, we will discuss some simple examples for microgrids as well as consider the model of battery as a pack, i.e. a set of cells in series and parallel with slight inherent variation in SoC and SoH. The results of the proposed approach are compared with the conventional control strategies and improvements in performance and speed are reported.

Acknowledgements

This work was supported by the Clean Energy Institute located in University of Washington, Seattle and Washington Research Foundation. The battery modeling work has been supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the U. S. Department of Energy through the Advanced Battery Material Research (BMR) Program (Battery500 Consortium).

References

1. B. Subudhi and R. Pradhan, Sustainable Energy, IEEE transactions on, 4 (1), 89-98 (2013).

2. D. A. Beck, J. M. Carothers, V. Subramanian, and J. Pfaendtner, AIChE Journal, 62 (5), 1402-1416 (2016).

3. S. B. Lee, C. Pathak, V. Ramadesigan, W. Gao, and V. R. Subramanian, Journal of The Electrochemical Society, 164 (11), E3026-E3034 (2017).