Decentralized Passivity-Based Control Design for Voltage Regulation and Current Sharing in DC Microgrids

المفاهيم الأساسية

A decentralized passivity-based control approach is proposed to simultaneously achieve voltage restoration and current sharing in DC microgrids, by designing the local controllers and the communication topology in a coordinated manner.

الملخص

The paper presents a decentralized passivity-based control (PBC) approach for DC microgrids (MGs) that addresses both voltage restoration and current sharing objectives. The key aspects are:

Modeling the DC MG as a networked system, with each distributed generator (DG) and transmission line represented as a subsystem.

Designing local controllers for the DG subsystems to ensure they are input-output passive (IOP) or input-feedforward output-feedback passive (IF-OFP). This is done by solving decentralized LMI problems.

Synthesizing the communication topology (interconnection matrix) between the DG subsystems using an LMI-based optimization problem. This ensures the overall networked system is L2-stable from disturbances to performance outputs.

The proposed approach maintains the plug-and-play capability, where new DGs can be added without the need to redesign the existing controllers.

The stability and performance analysis is carried out by exploiting the dissipativity properties of the subsystems and the networked system.

The effectiveness of the proposed method is demonstrated through simulation results.

الإحصائيات

None.

اقتباسات

None.

الرؤى الأساسية المستخلصة من

Decentralized Synthesis of Passivity-Based Distributed Controllers for DC Microgrids

by Mohammad Jav... في arxiv.org 04-30-2024

https://arxiv.org/pdf/2404.18210.pdf

استفسارات أعمق

How can the proposed decentralized PBC approach be extended to handle uncertainties or time-varying parameters in the DC microgrid model

To extend the proposed decentralized Passivity-Based Control (PBC) approach to handle uncertainties or time-varying parameters in the DC microgrid model, one can incorporate robust control techniques. Robust control methods, such as H-infinity control or sliding mode control, can be utilized to account for uncertainties in the system dynamics or variations in parameters. By designing controllers that are robust to uncertainties, the decentralized PBC approach can maintain stability and performance even in the presence of unpredictable changes. Additionally, adaptive control strategies can be implemented to adjust the controller parameters in real-time based on the varying conditions of the microgrid. This adaptive approach allows the controller to continuously adapt to changes in the system, ensuring robust and reliable operation in the face of uncertainties.

What are the potential challenges and limitations in implementing the decentralized control architecture in a real-world DC microgrid system

Implementing a decentralized control architecture in a real-world DC microgrid system may pose several challenges and limitations. One potential challenge is the communication and coordination among the decentralized controllers. Ensuring seamless information exchange and synchronization between the controllers distributed across the microgrid can be complex, especially in large-scale systems with numerous distributed generators and loads. Additionally, the scalability of the decentralized control architecture could be a limitation, as the system may become more challenging to manage as the number of components increases. Another limitation could be the computational complexity of the decentralized control algorithms, especially in real-time applications where fast response times are crucial. Ensuring the stability and performance of the decentralized control system under various operating conditions and disturbances is also a significant challenge that needs to be addressed in real-world implementations.

Can the design framework be adapted to consider additional objectives, such as optimal power flow or economic dispatch, in the control synthesis

The design framework can be adapted to consider additional objectives, such as optimal power flow or economic dispatch, in the control synthesis by incorporating multi-objective optimization techniques. By formulating the control synthesis problem as a multi-objective optimization problem, the framework can simultaneously optimize multiple objectives, such as voltage regulation, current sharing, optimal power flow, and economic dispatch. This approach allows for the trade-off between different objectives to be explicitly considered during the controller design process. Additionally, advanced optimization algorithms, such as genetic algorithms or particle swarm optimization, can be employed to search for the optimal controller parameters that satisfy all the specified objectives. By integrating multiple objectives into the control synthesis framework, the decentralized control system can achieve enhanced performance, efficiency, and reliability in managing the DC microgrid.