In Canada, more than 1.11 TWh of energy per year is generated by diesel generators in off-grid remote areas. Delivering energy to these territories always has a high cost for the local and federal governments both financially and environmentally. Substituting fossil fuels with clean energies is the solution. However, the unreliability and intermittency of renewable energies (RE) are always challenging issues that need to be solved. Zinc air flow battery (ZAFB) with decoupled power and energy capacity can bring sustainability and reliability for microgrids. In this study, an efficient model was developed for ZAFB, which is applicable for large-scale modeling, and incorporated in microgrid modeling. A bilevel optimization approach was implemented in the microgrid model to find the optimal size and control of the microgrid simultaneously over the project lifetime. Using model predictive control (MPC) and based on user-defined foresight horizon and known information like energy demand and RE resources, the control model decides the future changes in microgrid components. This tool is used to propose the best microgrid design for these communities to reduce or eliminate their dependency on fossil fuels. The functionality of this tool was evaluated by three case studies in British Columbia: Blind Channel, Hot Springs Cove and Moresby Island. Zero CO2 emission and zero fuel consumption were achieved by a 100% RE microgrid consisting of wind and tidal turbines and large ZAFB. The net present cost (NPC) of this system and cost of energy are 39 – 46 % and 55 – 60 % less than the base case costs in which diesel is the main energy source. ZAFB with a longer storage duration (50 – 60 hours) satisfies 17 – 23% of annual energy demand in these case studies. / Graduate