Optimization- and Rule-based Energy Management Systems at the Canadian Renewable Energy Laboratory microgrid facility.

This paper presents the development, implementation, and commissioning of two different Energy Management Systems (EMSs) for the Canadian Renewable Energy Laboratory (CANREL), a microgrid testbed located in Guelph, ON, Canada, for the existing hardware, software, and communication infrastructure, which constrained the implementation options. A Rule-based EMS (RBEMS), which is typically found in microgrid controllers nowadays, and an implementation of an Optimization-based EMS (OBEMS), which is not usual in today's controllers, are proposed, tested, and demonstrated in the microgrid testbed. The RBEMS consists of a state machine that represents the commitment of different genset units in the system and the curtailment of load and renewable generation. The OBEMS is based on a unit commitment model for microgrids that minimizes the generation and curtailment costs, while operating the microgrid equipment according to technical limits. Both EMS systems are integrated into a Python application which integrates various open-source packages and solvers, making it affordable, flexible and easy to replicate and upgrade. The successful implementation and performance of the EMS is discussed, showing that the components of the microgrid follow the dispatch commands, with the OBEMS yielding better overall results than the RBEMS, as expected, using the existing communications links and maintaining the stability of the microgrid. • Two EMS algorithms were implemented and tested in a microgrid testbed. • The algorithms were coded using open-source programming languages and solvers. • The optimization-based EMS showed a better performance in terms of unitary energy costs. • The EMS tests exhibited typical issues in microgrid operation. [ABSTRACT FROM AUTHOR]