Comparison of Stationary and Dynamic Reference Frame Control Strategies for Microgrid Applications

Core Concepts

This paper presents a comparison of voltage and current control strategies in stationary (αβ) and dynamic (dq) reference frames for microgrid applications.

Abstract

The paper discusses the implementation of inner control loops for voltage and current regulation in microgrids, comparing the use of stationary (αβ) and dynamic (dq) reference frames.
In the stationary reference frame, the voltage and current controllers are based on Proportional-Resonant (PR) controllers, which provide zero steady-state error. The PR controllers are tuned to the fundamental microgrid frequency and can be supplemented with harmonic compensators.
In the dynamic reference frame, the voltage and current controllers are implemented using conventional PI controllers. The dynamic reference frame approach requires the use of positive and negative sequence controllers to handle unbalanced conditions, but it has a lower harmonic distortion compared to the stationary reference frame.
The paper presents simulation results to compare the performance of the two control strategies in terms of voltage and current tracking, active power, and total harmonic distortion (THD). The results show that both control strategies can effectively regulate the microgrid's voltage and current, with the dynamic reference frame approach exhibiting a lower THD.
The paper concludes that the choice between the stationary and dynamic reference frame control strategies depends on the specific requirements of the microgrid application, such as the need for harmonic compensation, unbalanced conditions, and the desired level of complexity.

Stats

The total harmonic distortion (THD) of the output voltage is 1.19% in the stationary reference frame and 0.41% in the dynamic reference frame.

Quotes

"The PR controller shows a high gain around the resonant frequency, which is tuned at the fundamental MG frequency."
"PI controllers remain helpless to give satisfactory performance under unbalanced conditions."

Key Insights Distilled From

Stationary and Dynamic Reference Frame Comparison Based Microgrid Application

by Ilyas Bennia... at arxiv.org 04-02-2024

https://arxiv.org/pdf/2404.00040.pdf

Deeper Inquiries

How would the control strategies perform under different microgrid operating conditions, such as varying loads or renewable energy sources?

The control strategies discussed in the context, whether based on stationary or dynamic reference frames, would exhibit different performances under varying microgrid operating conditions. In the case of varying loads, the control strategies would need to dynamically adjust the power output to meet the changing demand. The stationary reference frame control, utilizing PR controllers, may excel in scenarios where the load variations are predictable and can be effectively compensated for by tuning the controllers. On the other hand, the dynamic reference frame control with PI controllers might offer better adaptability to sudden load changes due to its ability to regulate direct signals without steady-state error. When it comes to integrating renewable energy sources, such as solar and wind, the control strategies would need to manage the intermittent nature of these sources. The dynamic reference frame control might have an edge in handling the stochastic behavior of renewable resources due to its capability to transform time-varying signals into DC signals, allowing for more precise control under varying renewable energy conditions.

What are the trade-offs between the complexity and performance of the stationary and dynamic reference frame control strategies?

The trade-offs between the complexity and performance of the stationary and dynamic reference frame control strategies are significant factors to consider in microgrid applications. In terms of complexity, the stationary reference frame control based on PR controllers might offer a simpler implementation due to its straightforward structure and reliance on frequency-tuned resonant controllers. This simplicity could lead to easier tuning and maintenance of the control system. However, the dynamic reference frame control using PI controllers, while potentially more complex to implement due to the need for separate controllers for positive and negative sequence currents, could offer higher performance in terms of adaptability to unbalanced conditions and better harmonic compensation. The dynamic reference frame control's ability to regulate direct signals without steady-state error might provide more robust performance under varying operating conditions. Therefore, the trade-off between complexity and performance would depend on the specific requirements of the microgrid application, with the stationary reference frame control offering simplicity and the dynamic reference frame control providing potentially higher performance.

How could the control strategies be further enhanced to improve microgrid stability, power quality, and resilience?

To further enhance the control strategies for improved microgrid stability, power quality, and resilience, several approaches could be considered:

Advanced Control Algorithms: Implementing advanced control algorithms, such as model predictive control or adaptive control, could enhance the control strategies' ability to adapt to changing operating conditions and disturbances.

Integration of Energy Storage: Incorporating energy storage systems into the control strategies can help in balancing supply and demand, improving stability, and enhancing resilience against fluctuations in renewable energy sources.

Fault Detection and Isolation: Introducing fault detection and isolation mechanisms within the control strategies can enhance the microgrid's resilience by quickly identifying and isolating faults to prevent cascading failures.

Cybersecurity Measures: Implementing robust cybersecurity measures to protect the control systems from cyber threats is crucial for ensuring the stability and resilience of the microgrid.

Real-Time Monitoring and Control: Utilizing real-time monitoring and control systems to continuously assess the microgrid's performance and make adjustments in response to changing conditions can further improve stability and power quality.

By incorporating these enhancements, the control strategies can be optimized to ensure better microgrid stability, power quality, and resilience in the face of varying operating conditions and challenges.