A dynamic coordination of microgrids

Abstract

Sustainable energy resource implementation has several advantages in terms of energy efficiency, reliability, and resilience. However, there are still challenges with the power quality in suitable energy balance and acceptable voltage levels in the electrical network. Therefore, this study presents novel energy coordination for implementing grid-tied microgrids, including photovoltaic and battery energy storage systems. Thus, multi-agent modelling based on system analysis is implemented to formulate the dynamic performance of independent, interconnected and autonomous microgrids. Three optimal control schemes, including open-loop, closed-loop and model predictive control, are combined with the optimal power flow algorithm to dynamically coordinate each independent agent and the entire microgrid. The system results demonstrate that, by combining these strategies with several smart homes, the dynamic coordination of microgrids brings various benefits, such as important economic, environmental and operation performance indicators, voltage stability, power loss minimisation and power-saving. The validation of the designed approaches is bench-marked within a 33-bus IEEE network in the residential sector. The developed intelligent coordination structures achieve significant energy savings ranging from 23.99% to 36.14% while maintaining suitable system voltage levels and minimising power loss. Besides, the developed dynamic coordination offers an adequate scalability framework for an effective microgrid implementation. • Implement a real-world demand management model for residential applications. • Formulate tertiary control strategies based on EMS and MAS for optimal coordination of microgrids. • Coordinate distributed energy resources, including solar PV and energy storage tied to the grid. • Employ a dynamic approach to ensure efficient utilisation of available energy resources within smart microgrids. • Provide a microgrid KPI framework based on techno-economic and environmental assessment.