Integrated Optimization of Microgrid Design, Dispatch, and Technology Selection

Access to affordable, reliable electricity is critical for commercial–industrial facilities, where interruptions impose significant costs. Microgrids can lower utility bills while reducing dependence on grid power, but feasibility studies are complex and difficult for non-specialists. We develop a functionality-based taxonomy of microgrid design software and, based on it, select the System Advisor Model (SAM) and HOMER Grid for a comparative case study. The analysis shows that these tools provide limited support for selecting photovoltaic (PV) module and battery chemistry, leaving stakeholders without adequate guidance for early-stage microgrid design. These results motivate targeted enhancements and the development of an optimization engine that natively co-optimizes technology choice and hourly energy dispatch.

To address these gaps, we develop a mixed-integer program (MIP) that co-optimizes technology choice, system sizing, and hourly dispatch. The model embeds utility tariffs, interconnection limits, and net-metering rules and is applied to a credit-free base case and scenarios with Investment Tax Credit (ITC) and emissions-abatement incentives. Microgrids reduce total energy cost relative to the grid-only baseline across all area levels. Under ITC scenarios, credits expand PV capacity toward the interconnection cap and shift selection from low-cost, low-efficiency modules to higher-efficiency panels as per-watt costs fall. Under emissions-abatement credits, larger PV–battery systems and higher battery power levels emerge to chase high-emissions hours, indicating that right-sized incentives can accelerate deployment while avoiding over-subsidization of largely unchanged designs.