A real-time control framework for smart grids that integrates sensing, decision-making, and actuation to optimize grid performance and reliability. Suitable for smart distribution networks, microgrids, and advanced energy systems.
- Real-time monitoring of voltage, current, frequency, and power quality
- Control algorithms for load balancing, demand response, and voltage regulation
- Event-driven responses for faults or grid disturbances
- Easily extensible for integration with DERs (solar panels, batteries) and HIL platforms
- Language: Python, C/C++, or MATLAB/Simulink
- Communication Protocols: Modbus, IEC 61850
- Hardware Modules: Raspberry Pi / STM32 / PLC + DAQ cards
- Control Algorithms: PID, fuzzy logic, rule-based, or machine learning
- Tools: Matplotlib (Typhoon HIL), (Python), STM32CubeMX (microcontroller), or Simulink real-time
- Voltage and frequency stabilization in microgrids
- Load management and peak shaving using demand response
- Fault detection and adaptive response to grid events
- Educational demonstration for smart grid control systems
- Collect real-time measurements from sensors, DAQs, or grid nodes.
- Process signals and execute control logic (PID, ML, etc.).
- Dispatch actuation commands to inverters, switches, or relays.
- Log data for monitoring, diagnostics, and future tuning.
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