Paper Conference

Proceedings of eSim 2020: 11th Conference of IBPSA-Canada


Modelling and Optimization of Battery Capacity for Resiliency in a Building-level Microgrid

Jeremy Lytle 1, Alan Fung 1, Falon Attai 2, Livio Nichilo 2
1 Ryerson University, Canada
2 Internat Energy Solutions Canada

Abstract: The increasing frequency of extreme weather events and projections of future electricity demand pose substantial operational threat to aging electricity infrastructure. Microgrids are becoming an attractive method of providing energy independence and resilience in this environment of uncertainty. The present analysis evaluates a design-phase microgrid proposed for implementation in Toronto against the stipulated resiliency target; to provide 24 hours of critical load support in an extended outage. An energy reservoir battery model is developed in python with inputs from Helioscope. Hourly outage simulations are conducted to evaluate trends in duration of critical load support. An economically optimal battery range is identified by considering the incremental cost of storage capacity as a function of the probability of achieving the target. The model is then extrapolated to Calgary, Vancouver and Los Angeles to explore variability in the results according to consistency of photovoltaic yield. A sensitivity analysis identifies linear dependencies between the optimal storage capacity and mean daily production and consumption within the microgrid. A multiple linear regression predictive model is thus proposed to approximate the battery capacity corresponding to 95% probability of success as a function of these early stage design variables.