This paper presents a distributed secondary control scheme for accurate power allocation and voltage restoration in islanded dc microgrids. Conventionally the droop control function is employed in the primary control layer to realize power sharing among the distributed generators (DGs) in a decentralized fashion. However, the dc bus voltage may deviate from its nominal value due to different load profiles. In order to restore the dc bus voltage to its nominal value while maintaining the power sharing accuracy, a distributed control scheme is proposed in the secondary control layer. By using limited information of dc bus voltage and the secondary control inputs of their neighboring controllers, a distributed secondary control input can be designed and then sent to its corresponding primary controller. Besides, compared to most existing methods, no global information is required and only dc bus voltage feedback is needed. In addition, by employing the idea of pinning control, our proposed secondary control can be further simplified by only sending the dc bus voltage to one DG. An islanded dc microgrid test system is built in the MATLAB Simulink environment to validate our proposed method. An experimental prototype consisting of two DGs is designed to demonstrate the newly proposed approach and verify the obtained theoretical results.

In this article, a cooperative resilient control method for dc microgrid (MG) is proposed to dispel the adverse influences of both communication delays and denial-of-service (DoS) attacks. To avoid that the sampling period is captured by intelligent attackers, a new time-varying sampling period, and an improved communication mechanism are first introduced under the sampling control framework. Based on the designed sampling period and communication mechanism, a resilient secondary controller is designed. It is theoretically shown that the developed method can achieve the goals of bus voltage restoration and current sharing even in the presence of both DoS attacks and heterogeneous communication delays. Finally, a dc MG test system is built in a controller-hardware-in-the-loop testing platform to illustrate and verify the effectiveness of our developed method against both communication delays and DoS attacks.

This article presents an intelligent fault diagnosis method for wind turbine (WT) gearbox by using wavelet packet decomposition (WPD) and deep learning. Specifically, the vibration signals from the gearbox are decomposed using WPD and the decomposed signal components are fed into a hierarchical convolutional neural network (CNN) to extract multiscale features adaptively and classify faults effectively. The presented method combines the multiscale characteristic of WPD with the strong classification capacity of CNNs, and it does not need complex manual feature extraction steps as usually adopted in existing results. The presented CNN with multiple characteristic scales based on WPD (WPD-MSCNN) has three advantages: 1) the added WPD layer can legitimately process the nonstationary vibration data to obtain components at multiple characteristic scales adaptively, it takes full advantage of WPD and, thus, enables the CNN to extract multiscale features; 2) the WPD layer directly sends multiscale components to the hierarchical CNN to extract rich fault information effectively, and it avoids the loss of useful information due to hand-crafted feature extraction; and 3) even if the scale changes, the lengths of components remain the same, which shows that the proposed method is robust to scale uncertainties in the vibration signals. Experiments with vibration data from a production wind farm provided by a company using condition monitoring system (CMS) show that the presented WPD-MSCNN method is superior to traditional CNN and multiscale CNN (MSCNN) for fault diagnosis.

This paper presents a new distributed control scheme to achieve both accurate voltage restoration and precise current sharing for islanded dc microgrid (MG) system only with limited noncontinuous communication among the distributed generators (DGs). A two-layer multiagent framework is employed for this MG system, which consists of a physical layer and a cyber layer. A distributed voltage restoration control scheme is proposed in the cyber layer, where no overall system information is required and only dc bus voltage feedback is needed. Furthermore, by employing the idea of event-triggered communication, our proposed approach only relies on limited aperiodic communication, which greatly reduces the communication cost in the cyber layer. The stability of proposed method is analyzed through a Lyapunov function based approach and we also demonstrate that the Zeno behavior can be excluded if a proper event-triggered condition is established. Our proposed method is validated in an islanded dc MG test system built in the Simulink environment and an experimental prototype consisting of three DGs simultaneously.

Direct current (DC) microgrid is being increasingly investigated in modern power grid. An important issue in DC microgrid operation is to ensure proper current sharing among converters. While this has been addressed through droop control, the resulting voltage deviation in DC bus has to be compensated. To solve this problem, a new distributed secondary control scheme is presented in this paper for both current sharing and voltage restoration. A key part of the presented scheme is the integration of a new parameter ‘virtual voltage drop’ defined from droop gain and line resistance. Since the DC bus voltage is not required as a feedback signal, the proposed secondary control is simple and easy to design and implement. In addition, as the proposed scheme has no requirement for the loads, it can handle both resistance loads and constant power loads (CPLs). Simulations as well as experimental studies are carried out to demonstrate the effectiveness of the proposed scheme.

In this paper, a priority sorting approach based on simplified model predictive control (MPC) is proposed for modular multilevel converter (MMC). It aims at reducing the computational burden of conventional MPC method while maintaining the system performance, especially under high voltage levels. The proposed approach mainly consists of three parts, i.e., grid-side current control (GCC), circulating current control (CCC), and capacitor voltage balancing control (CVBC). The GCC and CCC are separately designed with simplified MPCs, avoiding the weight factor. Meanwhile, the redundant calculations are eliminated in GCC by considering the desired predicted output voltage of equivalent MMC model. To further minimize the optional combinations of the switching states, the CCC is constructed by utilizing the output of GCC and the arm current. Besides, a novel priority sorting approach is proposed for the CVBC to alleviate the sorting operation. The submodules are divided into three groups according to the detected capacitor voltages. Moreover, the groups are assigned with different priorities based on the arm current, and only one group needs the sorting process. Additionally, a reduced frequency approach is introduced to decrease the power loss in the steady state. The effectiveness of the proposed approach is validated by both simulation and experimental results.