We present an energy management system (EMS) which demonstrates a model predictive control technique to ensure energy balance within district energy systems (DES). The technologies included are: combined heat and power plant, boilers, absorption chillers, solar panels, solar water heaters, electric chillers, and energy storage. The EMS solves for the DES’s optimal resource dispatch strategy depending on operating mode: baseline or emergency. In a U.S. Department of Energy-funded project, the EMS is applied to The George Washington University DES and a representative urban energy system to report system cost, reliability, vulnerability, and resiliency metrics as well as quantify the impact of incorporating distributed generation and storage.
Benedict Vergara,Doctoral Research Assistant,The George Washington University
Rachel Gray,Graduate Research Assistant,The George Washington University