Advancing Self-Healing Capabilities in Interconnected Microgrids via Dynamic Data Driven Applications System with Relational Database Management

Abstract

A microgrid is an interdependent electrical distribution system containing renewable energy sources, local demand and a coupled connection to the main grid. A very appealing feature of a microgrid is its capability to self-heal from disruptions, which is made even more viable with the emergence of interconnected collaborative microgrids. In this study, we present a dynamic data driven application system framework that integrates a relational database management system (RDBMS) to advance self-healing capabilities among interconnected microgrids. A RDBMS facilitates access to various sensors in the microgrid for fast abnormality detection and for determining the optimal self-healing action to implement. We build an agent-based simulation model (ABM) for three self-healing interconnected microgrids. Using the ABM, we compare self-healing operations of microgrids with and without an RDBMS. Simulation results show that an RDBMS may lead to faster response time and thus advance self-healing capabilities of interconnected microgrids.