Microgrid Control

Microgrid control refers to the methods and technologies used to manage and regulate the operation of a microgrid. In contrast to conventional power systems, microgrids exhibit greater sensitivity to fluctuations in demand due to their reduced rotating inertia and predominant reliance on inverter-based resources. Furthermore, the integration of distributed generation and the presence of bidirectional power flows contribute to increased operational complexity.

As a result, optimal microgrid control is essential to ensure that microgrids operate in accordance with applicable grid codes. Effective microgrid control enables stable and efficient power generation and distribution within a localized area by coordinating a variety of energy sources—both renewable and conventional—along with energy storage systems to maintain a balanced and dependable power supply.

Microgrids are designed to operate in two distinct modes, each offering unique advantages and control challenges:

• Grid-connected mode: In this configuration, the microgrid remains connected to the main utility grid, which allows the microgrid to draw electricity from the utility during periods of high demand or low local generation or to export excess power back to the grid when local generation exceeds consumption.
• Islanded mode: In this configuration, the microgrid disconnects from the utility grid and operates autonomously. Here, the microgrid control system takes on the critical role of regulating the voltage and frequency of its generation units. This capability ensures a stable and reliable power supply to local loads, even in the absence of support from the main grid, making it invaluable during grid outages or in remote locations.

Microgrid Control Modes

Microgrid control relies on several specialized modes, each designed to address specific operational requirements and challenges. Implementing these control modes is essential for ensuring the safe, stable, and efficient performance of a microgrid:

• Grid synchronization: This mode ensures the microgrid voltage matches the utility voltage in magnitude, frequency, and phase before connecting. Mismatched voltages can cause electrical disturbances (such as voltage transient), leading to instability and potential equipment damage.
• Grid forming: In this mode, certain generation units within the microgrid actively control the system’s voltage and frequency (in AC systems) or voltage (in DC systems). Grid-forming control is vital when the microgrid operates in islanded mode, as it provides the foundational stability required for independent operation.
• Grid following: In this mode, microgrid systems do not set the voltage or frequency themselves. Instead, they adjust their output of active and reactive power (in AC systems) or power (in DC systems) to follow the conditions present at their connection points. This mode is used when the microgrid is synchronized with the utility grid.
• Curtailment: During periods of unexpected events or operational stress, curtailment strategies are employed to reduce either generation or load. This approach helps maintain system stability and security, preventing overloads and ensuring the continued safe operation of the microgrid.

Designing Microgrid Control Systems with MATLAB and Simulink

You can use MATLAB^® and Simulink^® to design, simulate, and analyze microgrid control systems. This modeling environment enables you to model and simulate a wide range of energy sources—including conventional generators, wind and solar energy systems, and energy storage units in a unified microgrid framework.

You can adjust the level of model fidelity to suit different phases of the engineering life cycle. For example, during early-stage feasibility studies, you can use low-fidelity models with simplified dynamics to quickly explore system behavior and evaluate high-level control strategies. As the design progresses, you can use medium- and high-fidelity models to capture more detailed electrical and control dynamics, allowing for accurate performance analysis, hardware-in-the-loop testing, and real-time implementation. High-fidelity models are especially valuable for simulating inverter-based resources under various operating conditions. 

With MATLAB and Simulink, you can develop control algorithms and energy management systems, allowing for optimized energy distribution, enhanced system stability, and improved operational efficiency

In addition to system modeling and control design, you can evaluate the interoperability of microgrid with utility grid, perform load forecasting to reduce uncertainty in demand planning, and implement control strategies across embedded systems and real-time simulators.

To learn more about microgrid control, see power electronics simulation, real-time simulation, droop control, and grid-forming inverter.