Advanced Microgrid Design and Control Essentials Training by Tonex
This advanced course equips participants with state-of-the-art knowledge and tools for designing, analyzing, and controlling microgrids. The program emphasizes system architecture, control strategies, optimization algorithms, and resiliency design, blending theory with hands-on applications.
Participants will explore real-world case studies of advanced microgrid projects, learn how to handle grid-connected and islanded modes, and gain practical insights into developing adaptive and fault-tolerant control frameworks.
Learning Objectives
- Design scalable microgrid architectures (AC, DC, hybrid, and multi-bus).
- Apply hierarchical control (primary, secondary, tertiary) for distributed energy resources.
- Implement advanced strategies such as model predictive control (MPC) and multi-agent coordination.
- Perform optimization for energy efficiency, cost reduction, and resilience.
- Conduct simulation and stability analysis under various operating conditions.
- Integrate control design with hardware-in-the-loop (HIL) and real-time testing.
Audience
- Power systems engineers and designers
- Microgrid operators and system integrators
- R&D specialists in renewable and DER systems
- Government, defense, and utility professionals working on resilient grids
2-Day Agenda
Day 1 – Architecture and Control Frameworks
- Microgrid architectures: centralized vs decentralized designs
- AC, DC, and hybrid microgrids — advantages and tradeoffs
- Hierarchical control: droop control, secondary synchronization, tertiary optimization
- Advanced algorithms: VSM, adaptive droop, and distributed MPC
- Simulation workshop: Parallel inverter control with droop + secondary restoration
Day 2 – Optimization and Advanced Applications
- Economic dispatch and resilience-driven optimization
- Optimization under uncertainty: stochastic and robust methods
- Fault-tolerant control and adaptive reconfiguration strategies
- Hardware-in-the-loop testing and control prototyping
- Capstone exercise: Complete design and optimization of a resilient microgrid