Distributed Management Systems and Performance Analysis Methods for Smart Microgrids

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Microgrids consist of distributed power generators such as wind and photovoltaic and local loads at the distribution level, with a possibility to be connected to the main grid. Using a microgrid is a promising solution to improve the energy efficiency, sustainability, flexibility, reliability and resiliency of vulnerable power grids. Deployment of microgrids with smart management systems are among current research priorities to reduce greenhouse gas (GHG) emissions and environmental impacts in Canada.Conventionally, a three-level hierarchical control scheme including local controllers, and centralized supervisory control and energy management, is used for microgrids. In the development of the next-generation of smart microgrids in this project, management units are integrated in local controllers adding flexibility to manage distributed resources by an aggregator. This architecture provides a more resilient configuration for a microgrid as it can continue operating in case of network failures and/or cyber attacks. The proposed platform will be based on artificial intelligence (AI) that enables energy-efficient and reliable control of emerging smart microgrids. The second part of this research develops computationally efficient mathematical algorithms for performance analysis of microgrids including its power converters. Appropriate models for wind/solar parks will be developed which allow accurate but fast simulation of large-scale modular renewables while providing a key components for improving the design and performance of microgrids.The result of this project will equip the next-generation of microgrids with distributed management architecture. This facilitate the use of artificial intelligence for managing and controlling microgrids in a more reliable and resilient manner and will contribute to create opportunities in this research area in academia and in the emerging green energy economy in industry sectors in Canada.