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The improvements in signal-to-noise ratio (SNR) are indispensable to obtain the desired output signal of partial discharge (PD) under square wave pulsewidth modulation (PWM) voltage. In this article, the effect of complex PWM voltage parameters (rise time, fall time, frequency, duty cycle) on the SNR of PD tests is investigated. The results revealed that the sensor's high-frequency gain should be increased to improve the SNR under faster switching. PD impulses are more likely to be submerged in the residual interference under high-frequency voltage. The SNR can be improved by only detecting the PD at the rising front because the PD signal overlaps with commutation noise at the falling front of short duty cycle voltage, such as 0.03% duty cycle. The above results can reference the PWM parameters and improve the SNR in PD tests for rotating machines controlled by power electronics. [ABSTRACT FROM AUTHOR]

The stability of dual active bridge converter (DAB) is threatened when feeding the constant power loads (CPLs). This article proposes a deep reinforcement learning-based backstepping control strategy to solve this problem. First, a nonlinear disturbance observer is adopted to estimate the large-signal nonlinear disturbance. Then, a backstepping controller is used to stabilize the voltage response of the DAB under the large-signal disturbance. Finally, a compensation method based on deep reinforcement learning is developed to intelligently minimize output voltage tracking error and improve the operating efficiency of the system. The proposed controller can guarantee system stability under the large-signal disturbance of the CPL and achieve a fast dynamic response with accurate voltage tracking; it is more adaptive by using the deep reinforcement learning technique through the learning of its neural networks. The effectiveness of the proposed controller is verified by experiments. [ABSTRACT FROM AUTHOR]

Although smart home has received wide attention in recent years, numerous scholars focus more on energy optimization strategy than energy dispatch hardware device (named energy router). Meanwhile, this energy router should have several features, i.e., high renewable energy utilization, energy multi-port and low volume. Thus, this paper designs a nine-port energy router regarding smart home and proposes a multimode hierarchical management strategy for this energy router. First, for the multi-port demand of wind, solar, storage and utilization, this paper presents a nine-port energy router to improve the renewable energy consumption and power supply flexibility. In addition, to reduce the volume of the energy router, a non-isolated AC/DC hybrid topology is constructed through embedding the integrated power electronic converters, which achieves the miniaturization of the energy router. In order to improve the renewable energy utilization rate, the decentralized module control is proposed for the components of energy router to provide the voltage and frequency support for system, and realizes the power sharing of distributed generations (DGs). Furthermore, the power exchange control with three-mode switching is proposed to guarantee the global energy flow balance under complex conditions. Eventually, the feasibility of the energy router is verified by the simulation and experiments. [ABSTRACT FROM AUTHOR]

Distributed renewable energy source is an advisable solution for dc microgrids to reduce fuel consumption and CO2 emission. In such microgrids, the installation of two or more battery energy storage (BES) units is utilized to compensate the power imbalance between the sources and loads. Nevertheless, energy management with numerous BES units does not simultaneously consider the impacts of distributed generators (DGs) and constant power loads (CPLs). Since the inaccurate current sharing will shorten the lifetime of the batteries and cause instability problem, this article proposes a distributed secondary $H_{\infty }$ consensus approach based on the dynamic event-triggered communication method to realize accurate current sharing and efficient operation in the presence of numerous DGs and CPLs. First, the whole state-space function model of the dc microgrid consisting of DGs, batteries, resistive loads, and CPLs, is first built in detail. This model is further transformed into standard linear heterogeneous multiagent systems, which provides an indispensable preprocessing for advanced control strategy application. Then, the distributed secondary $H_{\infty }$ consensus approach based on the foresaid systems is designed to achieve accurate current sharing. For reducing the communication among batteries and the controller updating frequency, the dynamic event-triggered communication method is proposed. Compared with existing event-triggered methods, the communication and controller updating frequency of the proposed dynamic event-triggered method have been reduced a lot. Additionally, the proposed method can not only avoid the Zeno behavior, but also obtain the lowest bound of the sampled time interval. Finally, the numerical simulation results and experimental results verify the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

State-of-charge (SoC) imbalance and bus voltage deviation are two of the main problems in autonomous dc microgrids. Based on this concern, this paper presents an improved dual-quadrant SoC weighted control strategy and a distributed optimization control method to achieve SoC balance, ensuring accurate power-sharing and bus voltage recovery. Firstly, this paper couples the injected/released power with the current SoC and observed average SoC value to weight the droop coefficient, which is based on the charge/discharge mode for the energy storage system. Then a secondary controller is designed based on distributed optimal control to eliminate the bus voltage deviation caused by the line impedance difference. The proposed optimal control method optimizes the average bus voltage to the nominal value and achieve accurate power-sharing by constructing the correlated variables and voltage independent intermediate variables exchanged among bulk energy storage units (ESUs). Since the voltage observer cannot accurately observe the true average bus voltage under the communication delay, the proposed distributed optimal control method without the voltage observer can ensure that the average bus voltage is optimized to the nominal value, thus improving the robustness of the control system. Finally, the correctness and effectiveness of the proposed method are verified in Simulink/MATLAB. [ABSTRACT FROM AUTHOR]

Renewable energy is an advisable choice to reduce fuel consumption and $\rm CO_{2}$ emission. Therein, wind energy and solar energy are the most promising contributors to reach this goal. Although the hybrid wind/solar system has been widely studied, the real-time current sharing based on their maximum capacities is rarely achieved in terms of seconds. Based on this, this paper proposes an accurate current sharing and voltage regulation approach in hybrid wind/solar systems, which is based on distributed adaptive dynamic programming approach. Firstly, the equivalent wind/solar model is built, which is an indispensable preprocessing to achieve the complementary between wind energy and solar energy. Therein, the wind energy and solar energy can output relative current according to their respective capacity ratio, which ensure the maximum utilization ratio of renewable energy source. Furthermore, current sharing and voltage regulation problem is switched into optimal control problem. Under this effect, each source agent aims to obtain the optimal control variable and achieve accurate current sharing/voltage regulation. Moreover, an adaptive dynamic programming approach based on Bellman principle is proposed. It can achieve accurate current sharing and voltage regulation. Finally, the simulation results are provided to illustrate the performance of the proposed adaptive dynamic programming approach. [ABSTRACT FROM AUTHOR]

Modular multilevel converters (MMCs) in high-voltage dc applications usually adopt a distributed control architecture to manage a large number of submodules (SMs) through a communication network. The communication congestion and network disconnection might lead to communication interruption (CI) and eventually cause the system to malfunction. In this article, a resilient operation strategy is proposed and studied to ride-through the CI fault, in order to prevent frequent fault SM bypassing, replacement, or even system shutdown. The analysis of the MMC distributed control system with the presence of CI indicates that the insertion index of the faulted SM might become constant, which distorts the output current and results in overvoltage of the communication interrupted SM (CI-SM). The CI-SM capacitor voltage prediction can be used to determine the MMC safe operation period after CI occurs. During the safe operation period, the CI-SM power balance is sustained by utilizing prestored phase signals to generate a sinusoidal insertion index according to its capacitor voltage tracking error. Two operation modes are proposed and analyzed to ensure the MMC stable operation under various conditions. The system protection is sensibly used only if the CI duration exceeds a safe operation period, which avoids frequent SM cut-off. Good agreement of the CI-SM capacitor voltage is achieved between the theoretical and simulation results. The effectiveness and robustness of the proposed MMC resilient operation are experimentally confirmed. [ABSTRACT FROM AUTHOR]

This article proposes a circulating current and second harmonic current (SHC) suppression method by introducing virtual impedance into the circulating current and output current feedback control loops of the dc solid-state transformer (DCSST). The virtual impedance is employed to adjust impedance in the circulating current feedback control loop to decrease the circulating current when the transmission efficiency of each dual active bridge is different. And a SHC suppression method, which introduces the virtual impedance containing a bandpass filter, is adopted to reduce the SHC and improve the dynamic performance of the DCSST. Moreover, a relatively independent modular control method, which is conducive to the modular expansion of the DCSST, is proposed. Compared with traditional DCSST control methods, the proposed method can simultaneously realize the output current sharing and effectively reduce the SHC with modular control. Finally, a DCSST prototype is built and the results of the experiment verify the validity and effectiveness of the proposed control strategy and solutions. [ABSTRACT FROM AUTHOR]

A decentralized improved I-V droop control strategy for battery-supercapacitor (SC) hybrid energy storage system (HESS) is proposed in this paper. The dynamic power sharing between battery and SC is realized by replacing the constant droop coefficient in I-V droop control with virtual impedance, i.e. virtual inductance for battery side converter and virtual resistance for SC side converter. Besides, by injecting the virtual inductance in the battery side converter, negligible DC bus voltage deviation can be achieved without extra voltage compensator. Moreover, the state-of-charge (SoC) recovery is also considered to extend the service life of the HESS. Furthermore, in the proposed regulated power system, since the power allocation, DC bus stability and SoC recovery are decoupled from each other, the design of control parameters is simple. The corresponding design guideline is demonstrated in this paper. Finally, to verify the accuracy and feasibility of the theoretical analyses, hardware in the loop simulations have been conducted. [ABSTRACT FROM AUTHOR]