Abstract
Estimation strategies and hierarchical control measures are required for the successful operations of microgrids. These strategies and measures monitor the processes within the control variables and coordinate the system dynamics. State-of-the-art frameworks and tools are built into innovative grid technologies to model different structures and forms of microgrids and their dynamic behaviors. Smart grids’ dynamic models were developed by reviewing different estimation strategies and control technologies. A Microgrid control system is made up of primary, secondary, and tertiary hierarchical layers. These architectures are measured and monitored by real-time system parameters. Different estimation schemes and control strategies manage microgrid control layers’ dynamic performances. The control strategies in the developed technologies dynamics were accessed in the grid environment. The control strategies were modeled for microgrids using six design layers: adaptive, intelligent, robust, predictive, linear, and non-linear. The estimation schemes were assessed using microgrid controllers’ modeling efficiency. Hierarchical control strategies were also developed to optimize the operation of microgrids. Hence, this research will inform policy-making decisions for monitoring, controlling, and safeguarding the optimal design strategies for modeling microgrids.
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