The problem of voltage recovery and current balancing has been a hot research topic in the field of DC microgrids. How to build a model that reflects the circuit and component-level control (e.g., inner control loops) characteristics and design a secondary controller based on it to accomplish the above output regulations is the concern of this paper. Accordingly, in this paper, based on the large-signal model of microgrids, the corresponding high-order fully actuated model is developed for DC microgrids, which is not only simple in form but also able to capture the details of the actual power system, such as the relationship between voltage and current. Further, a distributed predictive fully actuated secondary control strategy is proposed based on the developed model to achieve voltage recovery and accurate current sharing. Allowing one to design the secondary controller free from the constraints of physical coupling in the microgrid is one feature of this control strategy, while the other is the arbitrarily assignable closed-loop poles. An analytical model of the closed-loop DC microgrid system with predictive fully actuated secondary control is developed, and the analysis of stability and output current consensus is presented therewith. Extensive tests on a hardware system of a DC microgrid with solar panels and an MPPT controller are performed to validate the performance of the designed controller.

This paper is concerned with the voltage tracking problem of DC microgrids subject to communication delays and packet losses, for which existing work commonly adopts passive fault-tolerant approaches. To accurately compensate for the above communication constraints experienced by DC microgrids, a coupled discrete microgrid model is developed on the basis of the physical laws of actual DC microgrids. Unlike the practice of passively tolerating communication delays, through the physical model established, this paper suggests a consensus-based proportional-integral predictive control strategy, which can actively compensate for communication delays and consecutive packet dropouts encountered by DC microgrids. Under the observer-based distributed networked predictive control framework, each distributed generation subsystem in the microgrid exchanges its own measurements over the network and integrates information from controllers of other units to achieve output voltage consensus in the presence of time delays and packet losses. Furthermore, to demonstrate the generality of the proposed method, the sufficient and necessary conditions for the DC microgrid system to accomplish voltage tracking are given. These conditions are rendered in the form of matrix eigenvalues associated with the physical connections and communication couplings between distributed generation units. Besides, the stability and convergence of the closed-loop microgrid system are given in the form of linear matrix inequality based on the Lyapunov function. Finally, the performance of the proposed control scheme is evaluated in terms of its convergence, robustness to load variations, and plug-and-play functionality through the built photovoltaic cell-based (with battery banks) DC microgrid hardware system.

This paper focuses on the consensus and tracking problem of nonlinear multi-agent systems under communication delays, and proposes a distributed predictive control scheme which is independent of the system model and able to actively compensate for communication delays. First, a consensus-related auxiliary variable and its corresponding estimator are innovatively designed to provide a globally consistent value. Then, the idea of dynamic linearization is adopted to obtain the equivalent linear dynamics of nonlinear agents. Furthermore, a distributed predictive controller is designed with the help of the auxiliary variables and the acquired time-varying linear system model. Compared with the existing schemes, the proposed controller compensates for the delayed signals in an active way, makes the traditional model-based predictive control method get rid of the dependence on the accurate system model, and carries out the rolling prediction in a distributed form. A stability analysis of the closed-loop system is given to illustrate the generality of the designed method. Finally, a numerical simulation verifies the effectiveness of the proposed method.

DC-DC converter-based multi-bus DC microgrids (MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

DC microgrids with distributed architectures inevitably encounter the threats of communication constraints and cyber attacks, and there is little research to address these two communication irregularities simultaneously. To provide DC microgrids with maximum resistance to communication constraints and cyber attacks, a distributed predictive secure control method based on blockchain protocol is proposed in this paper. The proposed control approach is the first attempt to address cyber attacks with a hybrid of data and models, improving the resilience and robustness of DC microgrids. With the help of practical Byzantine ideas, the proposed strategy preserves the resilience strengths of the blockchain against corruption and discards its shortcomings of low real-time performance, significantly enhancing the security without compromising the dynamic performance of the system by active intervention. Subsequently, a bound on the communication delay induced by the blockchain network under the expected security index is given based on the theoretical analysis. Unlike the existing practice of passively tolerating communication delays and packet dropouts, the predictive control method proposed in this paper actively compensates for them experienced by DC microgrids. Then, an analytical model of the closed-loop DC microgrid system is developed, and stability analysis is presented accordingly. Finally, several experimental tests performed on a PV-based DC microgrid hardware system are presented to demonstrate the effectiveness of the proposed control strategy.

With the ongoing development of renewable energy sources, information technologies and physical energy systems are further integrated, which leads to challenges in ensuring the secure and stable operation of renewable energy power systems in the face of potential cyber threats. The strengths of blockchain in cybersecurity make it a promising solution to these challenges. However, existing blockchains are not well-suited for control tasks due to their low real-time performance. Here, we present a consensus mechanism that enables real-time security control of systems, called Proof of Task. Instead of solving meaningless hash puzzles in Proof of Work, Proof of Task addresses problems closely related to the stable operation and control performance of these systems. With the proposed verification mechanism, Proof of Task significantly enhances the real-time performance of blockchain while mines its computational resources for tasks of interest. To demonstrate the effectiveness and necessity of Proof of Task, it is deployed across three renewable energy power systems. The results show that Proof of Task markedly fortifies the security and computing capability of these systems, ensuring their reliable and stable operation. This work highlights the promise of blockchain to facilitate security control and trusted computing of large-scale, complex-dynamic systems.