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The traditional power grid in the United States is often regarded as one of the largest machines in the world. Also referred to as the conventional grid—or simply, the grid— it is a vast network of interconnected power plants, transmission and distribution lines, substations, transformers, sensors, and other power electronics that work together to deliver electricity. This research targets a subset of electrical infrastructure known as a microgrid. Microgrids are commonly thought of as smaller sites that utilize distributed energy resources (DER) as a means to satisfy energy requirements. Microgrids are typically connected to the traditional grid using point of connection (POC) but retain the ability to operate independently. This trait is known as operating in islanded mode. Examples of microgrids are small islands, military bases, research facilities, and more.
The goal of this research is to demonstrate a holistic optimization model that recommends a combination of DER components with sizing configurations to meet energy, resiliency, and financial requirements for grid-connected microgrids. The model must make improvements on existing industry accepted software or prior established research through the customization of features, increased functionality, or addressing gaps in knowledge. To accomplish this, the Natural Energy Laboratory of Hawaiʻi Authority (NELHA) was used as a case study site due to being a microgrid native to Hawaiʻi, access to high quality gross load and PV data, and unique scenario utilizing an electrolyzer to refill hybrid fuel cell electric busses (FCEB). Through the use of a hybrid Mixed-Integer Linear Programming-Particle Swarm Optimization (MILP-PSO) approach, various normal and resiliency scenarios were simulated demonstrating sizing configurations that met all normal and critical load, hydrogen demands, and financial constraints. The model also made improves on academic research providing a greater focus on the role of hydrogen infrastructure within grid-connected and islanded microgrids.