Dynamic Distributed Collaborative Control for Equitable Current Distribution and Voltage Recovery in DC Microgrids

Abstract

In a stand-alone DC microgrid featuring several distributed energy resources (DERs), droop control is adopted to achieve a proportional distribution of current among the DERs within the microgrid. The operation of the droop control mechanism leads to a variation in bus voltage, which is further amplified by the line impedance between the DC bus and DERs. This paper proposes an enhanced distributed secondary control technique aimed at achieving equitable current sharing and voltage regulation simultaneously within a DC microgrid. The proposed distributed secondary control is incorporated into the cyber layer of the microgrid, facilitating the exchange of information among the controllers. In the event of a communication link breakdown, this technique upholds the reliability of the entire system. The control loop utilizes a type-II fuzzy logic control framework for the adaptive selection of the control parameters to improve the control response. Furthermore, the proposed technique can handle both resistive and constant power loads without any particular prerequisites. Utilizing the Lyapunov method, appropriate stability criteria for the proposed controller have been formulated. Various tests were performed across a range of operational scenarios to assess the robustness of the proposed control technique through MATLAB/Simulink® models, which have been validated with real-time experiments. The outcomes revealed that the proposed control effectively achieves its control objectives within a DC microgrid, showcasing rapid responsiveness and minimal oscillation.

Design and Implementation of an Energy Management System with Event-Triggered Distributed Secondary Control in DC Microgrids

“…Fuzzy logic control (FLC) is a control system designed to transform nonlinear functions into simple rules by incorporating measurements, human knowledge, and extensive experience [52]. Unlike other nonlinear controllers, FLC operates without the necessity of a mathematical model, making it more adaptable to nonlinear functions [53]. Moreover, FLC can facilitate control without relying on previous data, distinguishing it from other smart controllers [54].…”

“…Moreover, FLC can facilitate control without relying on previous data, distinguishing it from other smart controllers [54]. Notably, this control system is easily designed with minimal knowledge about the system model [55] and exhibits resilience in handling noisy sensor data and input signals, avoiding abrupt changes in control outputs [53]. FLC is employed as an alternative control approach to offer a more robust solution to control challenges in microgrids [55].…”

“…Additionally, Small (S), Normal (N), and Large (Lg) input parameters were created for the output current percentage of the sources. Triangular membership functions were chosen in this study for their simplicity, adaptability, stability, and ease of interpretation [53].…”

“…Additionally, Small (S), Normal (N), and Large (Lg) input parameters were created for the output current percentage of the sources. Triangular membership functions were chosen in this study for their simplicity, adaptability, stability, and ease of interpretation [53]. As depicted in Figure 5, an output triangular membership function has been defined to encompass the output current percentage data that provides the participation information of the sources.…”

Coordinated Hybrid Approach Based on Firefly Algorithm and Particle Swarm Optimization for Distributed Secondary Control and Stability Analysis of Direct Current Microgrids

“…Consequently, the traditional droop technique presents several limitations: it faces an inherent load-sharing and voltage control management trade-off, exhibits slow transient response, delivers suboptimal performance with distributed energy resources (DERs), and experiences impedance misalignment among parallel converters, affecting active power distribution. As a result, incorporating a secondary control loop alongside droop control can serve as an additional control layer for DC microgrids [14,18,24]. There are three primary categories of secondary control: decentralized, centralized, and distributed control.…”