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High renewable energy penetration increases the electricity seasonal imbalance in the long-term timescale. Power system planning needs to consider the optimal configuration of various flexibility resources and electricity balance in different timescales. The coupling of multiple timescales largely increases the computation complexity of the power system planning problem. Thus, this paper presents an efficient source-grid-storage co-planning model which incorporates a year-round hourly operation simulation. To improve the computation efficiency of the planning model, from the temporal scale, a self-adaptive compact panorama time series (CPTS) model is applied, which greatly reduces the number of variables related to short-term decisions. From the spatial scale, a network-constrained relaxed clustered unit commitment (NC-RCUC) model is introduced, which significantly reduces the number of variables related to unit commitment decisions. Case studies on the modified Garver’s 6-node system and HRP-38 system prove the validation and efficiency of the proposed model (“HRP” stands for high renewable penetration). The studies on the China power grid in 2035 demonstrate the future planning results of generation, transmission and storage in China power systems based on the proposed model. [ABSTRACT FROM AUTHOR]

In this paper, we investigate security and energy efficiency of multicast communication in cognitive satellite terrestrial networks. To achieve high spectrum efficiency and low interference power transmissions in the cognitive terrestrial network, the rate splitting multiple access scheme (RSMA) is employed to prompt the massive access of the secondary users. In particular, we derive analytical and asymptotic closed-form expressions for secrecy outage probability of the satellite terrestrial network with eavesdropping, interfering, and imperfect channel state information. Hence, a beamforming (BF) scheme based on RSMA for secondary network is proposed to suppress eavesdropping, mitigate interference, and enhance energy efficiency of the proposed system model. Then, we transform non-convex optimization constraints into resoluble problems utilizing Taylor series expansion and successive convex approximation. Finally, simulation results corroborate the above theoretical analysis and highlight the superiority of the designed BF scheme on security and energy efficiency. [ABSTRACT FROM AUTHOR]

Battery fault diagnosis is crucial for stable, reliable, and safe operation of electric vehicles, especially the thermal runaway early warning. Developing methods for early failure detection and reducing safety risks from failing high energy lithium-ion batteries has become a major challenge for industry. In this article, a real-time early fault diagnosis scheme for lithium-ion batteries is proposed. By applying both the discrete Fréchet distance and local outlier factor to the voltage and temperature data of the battery cell/module that measured in real time, the battery cell that will have thermal runaway is detected before thermal runaway happens. Compared with the widely used single parameter based diagnosis approach, the proposed one considerably improve the reliability of the fault diagnosis and reduce the false diagnosis rate. The effectiveness of the proposed method is validated with the operational data from electric vehicles with/without thermal runaway in daily use. [ABSTRACT FROM AUTHOR]

This paper is concerned with the channel estimation problem in millimeter wave (mmWave) wireless systems with large antenna arrays. By exploiting the inherent sparse nature of the mmWave channel, we first propose a fast channel estimation (FCE) algorithm based on a novel overlapped beam pattern design, which can increase the amount of information carried by each channel measurement compared to the existing nonoverlapped designs and thus reduce the required channel estimation time. We develop a maximum likelihood estimator to optimally extract the path information from the channel measurements. Then, we propose a novel rate-adaptive channel estimation (RACE) algorithm, which can dynamically adjust the number of channel measurements based on the expected probability of estimation error (PEE). The performance of both proposed algorithms is analyzed. For the FCE algorithm, an approximate closed-form expression for the PEE is derived. For the RACE algorithm, a lower bound for the minimum signal energy-to-noise ratio required for a given number of channel measurements is developed based on the Shannon–Hartley theorem. Simulation results show that the FCE algorithm significantly reduces the number of channel estimation measurements compared to the existing algorithms using nonoverlapped beam patterns. By adopting the RACE algorithm, we can achieve up to a 6 dB gain in signal energy-to-noise ratio for the same PEE compared to the existing algorithms. [ABSTRACT FROM AUTHOR]

Lithium batteries have the characteristics of high energy density and charge–discharge rate, but exhibit high chemical activity. State-of-charge (SOC) estimation is critical to the lithium battery electric vehicle (EV) operation safety. In this paper, a novel SOC estimation method is proposed based on Gaussian process regression. A mixture Gaussian process is used in this model to strengthen the reliability of data description and to increase the estimation accuracy. Optimal number of Gaussian processes is obtained by a revolutionary expectation maximum method. A nonlinear correlation feature selection method is introduced to improve the model efficiency. The effectiveness of the proposed method is verified by an EV field test. Compared with other data-based approaches, this method exhibits higher estimation accuracy and computational efficiency. [ABSTRACT FROM PUBLISHER]

Nowadays, with the rapid development of hydrogen powered vehicles, the demand for hydrogen refueling stations (HRSs) in the transportation field is growing. The renewable energy, e.g., wind energy, is used to produce and store hydrogen on site for HRSs, which may be a relatively cheap and clean solution. Considering the wind farm (WF) and HRSs belong to different entities, a new cooperative operation model of the WF-HRSs combined system is proposed. Specifically, the robust optimization methods are implemented to characterize the uncertainties of wind power and market electricity price, respectively, to alleviate risk. To ensure the fairness of profit allocation, the bargaining power is measured by various contribution levels of each stakeholder based on the Nash–Harsanyi bargaining game theory. Furthermore, the model is transformed into two sequential subproblems: energy trading problem (SP1) and the payment bargaining problem (SP2). Accordingly, a solving technique adopting column and constraint generation algorithm is provided to solve the SP1. In addition, for the sake of privacy protection, a distributed approach based on data-centric mode is developed to solve SP2. Finally, the numerical results can validate the effectiveness and scalability for the proposed scheme and algorithms. [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]

In the electrical engineering field, there are two types of system which can potentially generate resonance under excitation, one is the electrical system with inductor and capacitor, the other is the mechanical system with spring-mass characteristic. A lot of research on active damping control algorithms for grid-connected inverters with LCL filter and inverter-driven machine with multirotating masses have been demonstrated. However, research works for these two systems were carried out independently and there is a lack of systematic comparison for modelling and control between these two systems. This article will unify the mathematical models and active damping control algorithms for these two systems. It is found that the mathematical models and control structures are fundamentally the same. The existing or future potential active damping control algorithms used in electrical system can be applied in mechanical system and vice versa to avoid reinventing the wheel. Parameter sensitivity analysis for controller and feedback gains was performed for electrical systems in the discrete z-domain. For mechanical systems, it is found that a substantial electromagnetic torque overshoot was introduced when applying the active damping control and it was analyzed quantitatively with various damping coefficients to guide the inverter design. Finally, experimental tests were done to verify the findings. [ABSTRACT FROM AUTHOR]

Vehicle-to-everything communication (V2X) and mobile edge computing (MEC) have introduced significant technological innovations for autonomous ground vehicles (AGVs), enabling most driving task computations to be performed with edge servers with higher quality and effectively reducing computational power consumption for AGVs. For reducing more computational power consumption which can reach hundreds of watts, sending more offloading tasks to edge servers can result in high latency and congestion when the network resources are finite and even cause serious traffic accidents. Besides, in V2X network, multiple transmission paths, including vehicle-to-vehicle (V2V) links and vehicle-to-infrastructure (V2I) links, can provide more valuable resources for sending offloading tasks, but they increase the complexity of resource management. To improve the utilization efficiency of network resources and ensure low power consumption for AGVs, first, this paper analyzes mathematical models of bandwidth, delay and power consumption based on different computing modes and transmission paths. Second, we propose an allocation algorithm for network resource allocation, transmission paths and computing modes to minimize power consumption according to the states of the V2X-MEC network measured and predicted by the navigation and positioning system. Third, a traversal approach simplified by a road segmentation method is adopted to solve for the optimal parameters. Through simulations, we compare our solution against an allocation approach based on the shortest path method, minimum average delay method and game theory method to illustrate the effectiveness of our proposed method in reducing the power consumption and transmission delay of uplinks. [ABSTRACT FROM AUTHOR]

In this study, a nano-displacement measurement system is proposed and demonstrated both theoretically and experimentally, which was based on a modified Mach-Zehnder (M-Z) interferometer using two conjugated orbital angular momentum (OAM) beams. In contrast to the previous M-Z-based OAM interferometer, a reflection module is inserted into the reference arm instead of a simple mirror. As a result, the effect of the transverse position-dependence phase-shift caused by the dove prism can be clearly eliminated and a stable and robust (off-axis insensitive) petal-like interference pattern can be obtained successfully. More importantly, a significant rotation angle of the petal-like pattern vs. the tiny displacement of the tested object can be clearly observed. In accordance with the modified measurement setup, a novel phase-demodulation method enabling to quickly and accurately characterize the rotation angle of the petal-like interference-patterns is proposed and demonstrated also. A tiny displacement ranging from 50 to 800 nm with resolution of $\sim 50$ pm has been measured successfully. The proposed approach may find applications in not only the ultra-high precision displacement sensor, but also the temperature, strain, and refractive index sensors. [ABSTRACT FROM AUTHOR]

In this paper, we propose an approach to realize substrate integrated waveguide (SIW)-based leaky-wave antennas (LWAs) supporting continuous beam scanning from backward to forward above the cutoff frequency. First, through phase delay analysis, it was found that SIWs with straight transverse slots support backward and forward radiation of the $-1$-order mode with an open-stopband (OSB) in between. Subsequently, by introducing additional longitudinal slots as parallel components, the OSB can be suppressed, leading to continuous beam scanning at least from $-40^\circ$ through broadside to 35°. The proposed method only requires a planar structure and obtains less dispersive beam scanning compared with a composite right/left-handed (CRLH) LWA. Both simulations and measurements verify the intended beam scanning operation while verifying the underlying theory. [ABSTRACT FROM PUBLISHER]

This paper presents two linear power sharing schemes for distributed generators (DGs). The purpose is to reduce the total generation cost (TGC) of the considered autonomous microgrid. The saving in cost is realized by tuning the DG droop gradients in accordance to their respective maximum or mean generation costs. Compared with the existing nonlinear cost-based schemes, the proposed schemes use linear droop functions, which are easier to tune and implement in practice for a greater reduction in TGC. The proposed schemes have been tested experimentally with an example microgrid powered first by dispatchable DGs only, and then by a combination of dispatchable and nondispatchable DGs. Experimental results obtained have demonstrated the anticipated outcomes under different operating conditions. [ABSTRACT FROM AUTHOR]

This paper investigates the crystallinity, microstructure, surface morphology, stress characteristics, and Young’s Modulus of ultrahigh vacuum (UHV) electron-beam (E-beam) evaporated silicon films with a low thermal budget. The films are evaporated at various substrate temperatures ranging from 200 °C–625 °C, deposition rates ranging from 50 to 400 nm/min, and annealed at 600 °C for various durations. Some of the preliminary results were reported by Michael and Kwok. The results indicate that the film characteristics of the evaporated silicon films are significantly different from and better suited for microelectromechanical systems (MEMS) applications than low pressure chemical vapor deposition silicon films, commonly used for MEMS devices. The very attractive properties of UHV E-beam deposited silicon films are remarkably low residual stress (both average and gradient), very smooth surface morphology, and thick layers at a low thermal budget with reasonably large deposition rates. Two different mechanisms have been identified as responsible for initiating the formation of crystal grains in these films: 1) kinetic energy of evaporated silicon atoms; and 2) thermal energy from the substrate heating. The first mechanism leads to fine columnar grains responsible for the smooth surface morphology and easily controllable low stress characteristics. The second mechanism results in coarse grain formation with a relatively higher proportion of (111) oriented grains. Cantilever beams of 30- \mu \textm thickness have been fabricated from such films with rms roughness of <5 nm, residual stress of 20 MPa, and stress gradient of <1.1 MPa/ \mu \textm with Young’s Modulus of 169 GPa. [2015-0096] [ABSTRACT FROM AUTHOR]

Multiple-voltage-region control, in which the bus-voltage range is divided into several regions, is usually implemented for dc microgrid operation in distributed manner. Voltage/power droop relationships are imposed for active power sharing among slack terminals. Conventionally, threshold voltages for voltage region partition are determined with fixed percentage of variation around the nominal value, which may result in unevenness of droop coefficients in different regions. If system droop coefficient is too high, significant bus-voltage step change due to load variation will occur. On the other hand, significant power sharing error among slack terminals will be induced if the droop coefficient is too low. In this paper, a compromised solution with power-capacity-based bus-voltage region partition is proposed to equalize the droop coefficients in different regions. However, the droop coefficients are determined based on the rated power capacity of system units. Bus-voltage discontinuity appears when the power capacity reduces in actual implementation. To eliminate the voltage discontinuity, online droop coefficient tuning according to the real-time power capacity is implemented. Algorithms for local power capacity estimation of solar photovoltaic (PV) and battery energy storage have been proposed. A lab-scale dc microgrid has been developed for verification of the proposed methods. [ABSTRACT FROM AUTHOR]

It has been shown that the Universum data, which do not belong to either class of the classification problem of interest, may contain useful prior domain knowledge for training a classifier [1], [2]. In this work, we design a novel boosting algorithm that takes advantage of the available Universum data, hence the name \cal UBoost. \cal UBoost is a boosting implementation of Vapnik's alternative capacity concept to the large margin approach. In addition to the standard regularization term, \cal UBoost also controls the learned model's capacity by maximizing the number of observed contradictions. Our experiments demonstrate that \cal UBoost can deliver improved classification accuracy over standard boosting algorithms that use labeled data alone. [ABSTRACT FROM AUTHOR]

To enhance the resilience of power systems toward the temporal and spatial impacts caused by extreme weather events, e.g., hurricanes, the flexibility of cloud data centers (CDCs) is treated as a kind of efficient demand response. Since the workloads of CDCs have the shifting capacity between different locations and time slots, a day-ahead unit commitment problem including data centers is proposed to explore the integrated spatial and temporal flexibility of the workloads to its full extent through task migration. Considering the uncertainty of probability density functions, the line failure rates, workload arrival rates, power loads are integrated into an ambiguity set. The scheduling process of generators and CDCs is modeled as a two-stage distributionally robust optimization problem, which is reformulated as a large-scale deterministic mixed-integer linear programming problem and solved by the multicuts Benders decomposition method. The performance of the proposed scheduling strategy is tested in both the IEEE 24-bus RTS system and the three-area RTS-96 system. The results reveal that the method could mitigate the adverse impacts of hurricanes by enhancing the resilience of power systems and decreasing the dropping workloads of CDCs. [ABSTRACT FROM AUTHOR]

Ensemble learning is a common tool for data stream classification, mainly because of its inherent advantages of handling large volumes of stream data and concept drifting. Previous studies, to date, have been primarily focused on building accurate ensemble models from stream data. However, a linear scan of a large number of base classifiers in the ensemble during prediction incurs significant costs in response time, preventing ensemble learning from being practical for many real-world time-critical data stream applications, such as Web traffic stream monitoring, spam detection, and intrusion detection. In these applications, data streams usually arrive at a speed of GB/second, and it is necessary to classify each stream record in a timely manner. To address this problem, we propose a novel Ensemble-tree (E-tree for short) indexing structure to organize all base classifiers in an ensemble for fast prediction. On one hand, E-trees treat ensembles as spatial databases and employ an R-tree like height-balanced structure to reduce the expected prediction time from linear to sub-linear complexity. On the other hand, E-trees can be automatically updated by continuously integrating new classifiers and discarding outdated ones, well adapting to new trends and patterns underneath data streams. Theoretical analysis and empirical studies on both synthetic and real-world data streams demonstrate the performance of our approach. [ABSTRACT FROM AUTHOR]

Accurate electromagnetic (EM) analysis for conductive media requires to consider the finite conductivity of the media. Although the problems can be formulated by surface integral equations (SIEs) with an approximate surface impedance, we treat the conductive media as penetrable objects and use volume integral equations (VIEs) to exactly describe their EM features. The VIEs are solved by a point-matching scheme which does not rely on any basis and testing functions and allows the use of nonconforming meshes. Since the VIEs are well-conditioned in general and the integral kernels are free of material parameters, the scheme is flexible to accommodate a wide range of skin depth. Moreover, when the skin depth is small, we can only discretize the skin domain with a current distribution to reduce the cost. For large conductive media, we also incorporate the scheme with the multilevel fast multipole algorithm (MLFMA) to accelerate the solution. Typical numerical examples are presented to illustrate the scheme and its effectiveness has been validated. [ABSTRACT FROM PUBLISHER]

Droop schemes have traditionally been applied to the control of parallel synchronous generators in power systems. It has subsequently been brought over to the control of distributed generators (DGs) in microgrids with the same retained objective of proportional power sharing based on ratings. This objective might, however, not suit microgrids well since DGs are usually of different types, unlike synchronous generators. Other factors like cost, efficiency, and emission penalty of each DG at different loading must be considered since they contribute directly to the total generation cost (TGC) of the microgrid. To reduce this TGC without relying on fast communication links, an autonomous droop scheme is proposed here, whose resulting power sharing is decided by the individual DG generation costs. Comparing it with the traditional scheme, the proposed scheme retains its simplicity and it is hence more likely to be accepted by the industry. The reduction in TGC has been verified by experiment. [ABSTRACT FROM PUBLISHER]

A compact interlinking converter modular (ICM) for hybrid ac/dc microgrids with a distributed storage (DS) bus for storage integration is proposed in this article. The advanced ICM for hybrid ac/dc/ds microgrids involves the nine-switch topology with compact configuration and decreased number of active operating switches, which structurally equivalents to afford a dc interconnection port for dc subgrid, an ac interconnection port for ac subgrid, a ds interconnection port for ds subgrid, and two dc–dc converters for the interconnection ports for parallel DSs. In addition to the popular advantage of component elements saving, the suggested ICM, aggregating various interlinking converter cells (ICCs) into an ICM, is also proficient of participating computations from all ICC sensors to enhance the overall modular performance without building extra communication connection links between ICCs. With this in mind, a decentralized power management control strategy is realized by employing a coordination power control methodology to systematically handle various distributed generations (DGs), DSs, and ICM in a decentralized manner with improved communication fault ride-through capability. The controller hardware-in-the-loop experiments on a real-time digital simulator platform validates the achievement of the advanced ICM application in hybrid ac/dc/ds microgrids and the effectiveness of the associated decentralized power management scheme. [ABSTRACT FROM AUTHOR]

Recently, convolutional neural networks (CNNs) have been successfully developed and used in the classification of polarimetric synthetic aperture radar (PolSAR) images. However, they often suffer from some problems, such as time-consuming, unsatisfactory detail-preservation, and bad effectiveness given limited training samples. Focusing on these problems, we propose a complex-valued CNN (CV-CNN)-based algorithm for PolSAR image classification in this article. On the one hand, a superpixel-oriented (SPO) scheme is employed to reduce the computational cost of the algorithm and preserve image details simultaneously, which takes superpixels instead of single pixels as classification units. In particular, to meet the input requirement of CV-CNN, three alternative methods of superpixel regularization are designed and compared. On the other hand, considering that both measured data (MD) and manually designed polarimetric features (PFs) have their own advantages, the hybrid data (HD) combining them is employed to drive CV-CNN, which is helpful to improve the effectiveness of the algorithm. We perform experiments on three actual PolSAR image data sets acquired by AIRSAR and Radarsat-2 systems as well as a semisimulated data set. The experimental results demonstrate that, compared to conventional pixel-oriented methods, the proposed SPO scheme is much more time-efficient and is also beneficial to detail preservation. Moreover, the CV-CNN driven by HD generally obtains consistently better classification results than that driven by pure MD or manually designed PFs. [ABSTRACT FROM AUTHOR]

To achieve an individual and continuous power distribution for multireceiver wireless power transfer (WPT) systems, a novel multifrequency modulation method has been proposed. In the proposed method, a look-up table and delta-sigma modulation scheme are introduced to generate a mixed-frequency driving voltage pulse by synthesizing it from the given voltage pulses. The components of synthesized driving voltage pulse have continuously and individually varying amplitudes of multiple specific frequencies. With the proposed modulation method, only a standard full-bridge inverter is employed in the transmitting side to achieve power distribution among receivers, leading to a simple configuration of the transmitting source. Moreover, the proposed method has a small calculation burden and can be easily extended to the system with more receivers. When compared with the existing multifrequency modulation method, a lower switching frequency is obtained in the proposed method. Finally, the effectiveness of the proposed modulation method is verified theoretically and experimentally. [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]

In this paper, the dependence of XLPE electrical breakdown on carrier mobility controlled by both electric field and temperature is evaluated by simulations and experiments. The molecular chain displacement model incorporating the thermoelectric effect of carrier mobility is examined to elucidate the experimental results. Trapping and de-trapping characteristics of space charge and mobility dynamics are modeled using hopping and Poole-Frenkel mechanisms. The experimental outcomes reveal that the DC electrical breakdown reduces with corresponding increment in temperature and thickness. Trapping parameters are estimated from experiments for simulations. The DC breakdown strength from experiments represents an inverse power relation with both the insulation thickness and temperature. The simulation results of molecular chain model with hopping mobility express more permanence with experimental results in comparison with Poole-Frenkel mobility. [ABSTRACT FROM AUTHOR]

The allocation of fault current limiters (FCLs) is increasingly challenging in transmission systems these days. Specifically, the utilized deterministic expected short-circuit fault (SCF) scenarios are prone to cause over-configuration of FCLs. Moreover, the well-established local switching framework (LSF) renders inappropriate FCL switching and may further harm the system safe operation. Aiming at the above deficiencies, a novel 5G-based centralized switch FCL (CSF) framework as well as a method to allocate such flexible FCLs optimally is proposed in this paper. In the proposed CSF, the FCLs are switched by a FCL dispatching (FD) model considering system security constraints of both fault current and voltage sags. By exploiting the fast communication capability of 5G network as well as an off-line fault scanning strategy, the FD model is enabled to give online FCL switching schemes to meet the fast requirement of power system protection. Moreover, considering the probabilistic characteristic of SCFs, a bi-level FCL allocation model is established, in which the upper-level model sites and sizes FCLs considering the installation and expected switching costs while the lower-level model determines the optimal switched FCLs under each specific SCF scenario. Finally, numerical results are provided to verify the proposed allocation model, including its defending effect against SCFs in terms of fault current limiting, voltage sags relieving, as well as its cost-effectiveness. [ABSTRACT FROM AUTHOR]

The electric vehicle technology is one of the most promising candidates to reduce fuel consumption and $\rm CO_2$ emission. Although electric vehicles have been widely promoted by governments around the world, their development is seriously hampered due to charger unavailability and range anxiety. Based on this, this paper designs an energy interaction converter between two electric vehicles, which is controlled through disturbance observer based sliding mode control algorithm. For this converter, three main demands should be satisfied, i.e., high power density, weak source and constant power load. Therein, weak source whose minimum short circuit ratio (SCR) belongs to Jia et al., 2020 and Wang et al., 2020, is always called weak grid. Firstly, the equivalent impedance switching process is introduced to eliminate the impact of weak source. Meanwhile, the equivalent six channel interleaved floating dual boost converter is chosen to satisfy the high power density demand, whose generalized state-space function is further built to provide an indispensable preprocessing for following controller design. Moreover, in order to solve the problem regarding low frequency/sub-synchronous oscillation caused through constant power load feature regarding the energy consumption vehicle and weak source feature regarding the energy supply vehicle, a disturbance observer based sliding mode control algorithm is proposed through using generalized state-space function to provide standard DC power with both constant voltage and power. Furthermore, the proportional-resonant controller is proposed to solve the current sharing problem among six parallel channels, which reduces the heat loss and improves the service life of the device. Finally, simulation and experimental results verify the high performance of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a multiple-input versatile matrix converter (VMC) for integrating hybrid ac/dc energy resources and storages to the power grid. The VMC is developed from the traditional indirect matrix converter but operates in the reverse-boost mode rather than in the forward-buck mode. The reverse-boost mode is more relevant here since most renewable sources and energy storages have lower voltages than the grid. The eventual VMC developed uses an alternative nine-switch converter, rather than usual six-switch voltage-source converter, for providing six input terminals in total. One three-phase ac source and three dc sources, or other source combinations, can therefore be connected to the VMC. Powers from these sources are channeled to the three-phase utility grid through the VMC's current-source inverter. Their proper dispatches are guaranteed by the proposed control and modulation schemes, which also help maintain near-sinusoidal input and output current waveforms. Mathematical proofs, simulation, and experimental results have shown that the VMC can indeed operate as intended. [ABSTRACT FROM PUBLISHER]

With high wind-power penetration, power-system operators require accurate wind-power output from wind farms for system operation. A more accurate four-dimension wind speed model is proposed in this paper to simulate the effects of terrain and time delay of wind speed. Two coordinate transformation matrices are proposed to easily incorporate wind direction in wind-speed simulation. The effects of random failures and wake of wind turbine generators on wind-speed distribution in a wind farm are also considered in the proposed model. A sequential Monte Carlo simulation technique is developed to evaluate adequacy of power systems with wind farms using the proposed model. The modified IEEE RTS is analyzed to illustrate the models and technique. The simulation results show that those factors have significant impact on power output of a wind farm and system reliability. [ABSTRACT FROM PUBLISHER]

In practical microgrids, the inhomogeneous initial values are widely appeared due to soft-starting operation. If traditional model order reduction approaches are applied, the input-output maps error between the original system and reduced-order system is large. To address this problem, this paper proposes a reduced-order aggregate model based on balanced truncation approach to provide the preprocessing approach for the real-time simulation of large-scale converters with inhomogeneous initial conditions in DC microgrid. Firstly, the standard linear time-invariant model with inhomogeneous initial conditions is established through non-leader multiagents concept. To end this, it is convenient for scholars to build complex system modeling with switched topology. Furthermore, the full system is divided into two components, i.e., the unforced component with nontrivial initial conditions and forced component with null initial conditions. Moreover, this paper presents an aggregated approach that involves independent reducing component responses and combining reducing component responses. Based on this, the input-output maps error is reduced. Then, the approximated error estimate of the reduced-order aggregate model regarding large-scale converters in DC microgrid is first provided, which provides prior knowledge and theoretical basis for DC microgrid designers. Finally, the simulation results illustrate the accuracy of the proposed approach. [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]

Due to global climate change, the effect of extreme weather on power systems has attracted extensive attention. In the prior-art grid resilience studies, the hurricanes or wildfires are mainly defended in terms of expected line damages, while they are prone to trigger short-circuit fault (SCF) evolved with dynamic influence in reality. In this paper, a fragile model is developed to evaluate the nodal SCF probability considering the insulation aging of equipment and extreme weather condition. Then, a response framework for extreme weather events is developed for a transmission system to defend the cascading impacts of expected SCFs. Specifically, switches are shifted to restrain the out-of-range short-circuit currents (SCCs) so that to ensure the SCFs can be removed by circuit breakers, generation rescheduling and load shedding are arranged to maintain the post-fault system transient stability. The above measures are optimized simultaneously by an integrated Mixed-Integer Nonlinear Programming (MINLP). Considering the error or uncertainty of weather event forecasts, a multi-state model is established to provide the most cost-effective grid resilience enhancement scheme, in which the expected urgent adaptions of the initial scheme subject to weather state transition is included in the overall cost. The proposed model and techniques are validated using the IEEE 39-bus New-England test system and realistic meteorological data. [ABSTRACT FROM AUTHOR]

The Jiangmen Underground Neutrino Observatory (JUNO) is a medium-baseline neutrino experiment under construction in China, with the goal to determine the neutrino mass hierarchy. The JUNO electronics readout system consists of an underwater front-end electronics system and an outside-water back-end electronics system. These two parts are connected by 100-m Ethernet cables and power cables. The back-end card (BEC) is the part of the JUNO electronics readout system used to link the underwater boxes to the trigger system and transmit the system clock and triggered signals. Each BEC is connected to 48 underwater boxes, and in total around 150 BECs are needed. It is essential to verify the physical layer links of the BEC before applying a real connection with the underwater system. Therefore, our goal is to build an automatic test system to check the physical link performance. The test system is based on a custom-designed field-programmable gate array (FPGA) board. In order to make the design general, only joint test action group (JTAG) is used as the interface to the PC. The system can generate and check different data patterns at different speeds for 96 channels simultaneously. The test results of 1024 continuously clock cycles are automatically uploaded to PC periodically. We describe the setup of the automatic test system of the BEC and present the latest test results. [ABSTRACT FROM AUTHOR]

The droop control is an advantageous approach for stand-alone supply systems consisting of multiple batteries, allowing among various inverters without intercommunication. The droop coefficients of batteries always vary with their state-of-charge (SoC) and charge/discharge mode, resulting in small-signal instability. Nevertheless, the existing impedance-based approaches can only assess the droop coefficients stability point, but not the stability region. Therefore, this article proposes a droop coefficients stability region analysis approach. First, the charge/discharge SoC-based droop controlled battery, the P&Q controlled distributed generator and the constant power load are separately discussed. Meanwhile, the state matrix and return-ratio matrix are established, respectively. Furthermore, the novel forbidden region criterion based on the return-ratio matrix is constructed, which reduces conservatism compared with norm-based impedance criteria and partial forbidden region criteria. Such a forbidden region criterion is first switched to the Hurwitz identification problem regarding the equivalent return-ratio matrix. Combined the state matrix and the equivalent return-ratio matrix, the generalized incidence matrix is constructed to simultaneously identify subsystem stability and interactive stability. Based on the generalized incidence matrix, an adaptive step search strategy is proposed to obtain the droop coefficients coordinated stability region. Finally, the simulation and experimental results illustrate the validity of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, a novel bidirectional dc–dc converter (BDC) consisting of an active switched-inductor (A-SL) cell, a zero current ripple cell and an auxiliary capacitor cell is proposed for the battery energy storage system. The proposed BDC integrates with the advantages of high voltage conversion ratio, low power switch voltage stresses, zero ripple current on the low voltage side (LVS), and constant potential difference between the grounds of LVS and high voltage side. Thanks to the use of synchronous rectification technology, the efficiency of the proposed BDC is increased. The operating principles, the characteristics analysis and the parameter design of the proposed BDC are given. In addition, to show the merits of the proposed BDC, a comparison study involves the proposed converter and other BDCs is demonstrated. Finally, some experimental results obtained using a 1000 W prototype are presented to valid the effectiveness of the proposed BDC. 96.43% and 96.67% maximum conversion efficiencies can be achieved in the step-up and step-down modes, respectively. [ABSTRACT FROM AUTHOR]

This article presents a loosely coupled visual/inertial hybrid system for relative attitude determination on a moving platform. The inertial measurements are accomplished by two gyroscopes, of which the slave gyroscope removes the redundant motion of the platform from the total motion sensed by the master gyroscope. To correct integration drift error and compensate for the gyroscope biases, we fuse the inertial and visual measurements fused together through the error-state Kalman filter (ESKF). Furthermore, an improved ESKF is proposed by utilizing the variational Bayesian (VB) inference to adaptively estimate the process and measurement noise covariance. To realize direct estimation of the process noise covariance, a latent variable is introduced and inferred together with the noise covariances and error-state. The practical experimental setup is built up and experiments of two different motion trajectories are conducted. The ESKF, the cubature Kalman filter (CKF), the extended Kalman filter (EKF), the proposed filter, and the other two adaptive filters are implemented for comparison to verify the effectiveness of the proposed filter. The results demonstrate the proposed filter show superiority in reducing both the root mean square error (RMSE) and maximum error (ME) and improving the filter consistency. [ABSTRACT FROM AUTHOR]

Multiple ship tracking (MST) is an important task in marine surveillance and ship situational awareness systems. Considerable work has been conducted on multiple object tracking in recent years, but it has focused primarily on pedestrians and automobiles, leaving a gap in studies on MST due to the particularities of complex marine scenes, such as ship scale variations, the long-tailed distribution of ships, and long-term occlusions caused by ship movements. In this article, we present a robust deep affinity network (RoDAN) for MST. To overcome the above difficulties in MST, we start with the basic deep affinity network (DAN) and improve it in three aspects: scale, region, and motion. For the scale dimension, we integrate an atrous spatial pyramid pooling (ASPP) module to improve the modeling ability for multiscale ships. For the region dimension, we propose the joint global region modeling (JGRM) module, which further strengthens the modeling ability of DAN and exploit it to overcome the long-tailed distribution property of ships. For the motion dimension, we propose the motion-matching optimization (MMO) module to fine-tune the tracking results and make our tracker more robust, less reliant on the front-end detector, and ameliorate long-term occlusions. The experimental results demonstrate that our MST method outperforms the state-of-the-art methods. In particular, it reduces the number of ID switches (IDSs) and trajectory fragmentations (FMs), achieving holistically preferable performance. Meanwhile, our method achieves a comparable speed. [ABSTRACT FROM AUTHOR]

Multipass cell (MPC), with a long effective optical path length (OPL), is an effective method to improve measurement sensitivity in laser absorption spectroscopy for trace gas sensing. We present a space equation (SE) method to design MPC, which can solve inaccuracy caused by using paraxial-matrix (PM) method. The location and dimension of light spot pattern can be calculated accurately and intuitively through SE method. Meanwhile, actual effective OPL can be accurately calculated, SE method can reduce the interference effect, the direction of each ray can be obtained accurately, and, hence, designing the angle of outgoing ray is simple. By adjusting the mirror curvature, mirror space, incident angle, and incident position, we realized four dense spot patterns with different multiple reflections in MATLAB simulation. We calculated the shape changes of light spot after multiple reflection and its influence on the design of outgoing ray hole size accurately. We also considered the evolution of dense pattern and found a method easy to obtain multiple ring pattern. We verified the validity of the proposed model and built a compact MPC with seven rings dense spot pattern. Such MPC offers an effective OPL of 36.48 m with 198 times of reflection. We verified the tunable diode laser absorption spectroscopy (TDLAS) technology to measure 610-ppmv standard methane. In contrast to PM method, the improvement of the signal-to-noise ratio (SNR) of 1.36 times is achieved when the volume of MPC is reduced by 3 times. In addition, the SNR can be improved to 6.6 times, while the volume of MPC is the same. Results validated the ability of the SE method to design MPC. [ABSTRACT FROM AUTHOR]

A novel broadband planar antenna is developed for mobile communication base stations. The antenna is composed of a pair of folded dipoles which are coupling fed by an L-shaped microstrip line. Both the dipoles and the coupling microstrip line are etched on the same substrate. The planar antenna achieves a bandwidth of 53% for return\ loss > 15 dB, covering the frequency range 1.65–2.85 GHz for 2G/3G/LTE applications. The antenna gain of the broadband antenna element is about 9 dBi. A \pm45^\circ dual-polarized planar antenna consisting of two broadband antenna elements is proposed, which achieves a bandwidth of about 50% and an isolation of 30 dB. Two 8-element antenna arrays are developed respectively for the broadband antenna and for the \pm45^\circ dual-polarized antenna. Both antenna arrays achieve a bandwidth of more than 58% (1.6–2.9 GHz). The antenna gains achieved for the both antenna arrays are higher than 15.5 dBi. The half-power beam widths in the horizontal plane for the antenna arrays are approximately 65\pm 10^\circ, suitable for base station applications. [ABSTRACT FROM PUBLISHER]

A novel dual-broadband planar antenna is proposed for 2G/3G/LTE (4G) mobile communications. The proposed dual-broadband antenna consists of one element for the lower band and two elements for the upper band, making it possible to be arrayed without appearance of grating lobes in the upper band. The lower-band element comprises a pair of printed dipoles with a pair of parasitic elements for bandwidth enhancement. Two upper-band elements composed of two pairs of folded dipoles are nested inside the lower-band element, forming a compact arrayable antenna unit. The dual-broadband antenna achieves a bandwidth of 20% (800–980 MHz) for the lower band and a bandwidth of 60% (1540–2860 MHz) for the upper band. A dual-broadband antenna array that consists of 4 elements for the lower band and 8 elements for the upper band is developed for base station applications. The dual-broadband array achieves a bandwidth of 22% (780–980 MHz) for the lower band and a bandwidth of 68% (1470–3000 MHz) for the upper band, covering all the frequency bands for 2G/3G/LTE (4G) systems. Measured antenna gains for the array are \sim 12 dBi for the lower band and \sim 13.5 dBi for the upper band, suitable for potential applications in mobile communication base stations. [ABSTRACT FROM PUBLISHER]

Indirect matrix converter (IMC) is an alternative for ac/ac energy conversion, usually operated with a voltage stepped-down gain of only 0.866. For applications like distribution generation where voltage-boost functionality is required, the traditional style of operating the IMC is therefore not appropriate. Like most power converters, the operation of the IMC can surely be reversed to produce a boosted gain, but so far its relevant control principles have not been discussed. These challenges are now addressed in this paper with distributed generation suggested as a potential application. Simulation and experimental results for validating various performance aspects of the proposed control schemes can be found in a later section of this paper. [ABSTRACT FROM AUTHOR]

In dc microgrid, energy storage system (ESS) plays a crucial role to provide short-or-long term and high-quality electric energy. The different control strategies for bidirectional dc-dc converter (BDC) of ESS in grid-tied and islanded modes pose challenges to the coordination control of the dc microgrid. This paper proposes an autonomous control scheme for the BDC in dc microgrid. The proposed control scheme is based on $V^2-P$ droop control and unifies bus voltage regulation and power regulation in a single control structure. Thus, global smooth transition between various operation modes can be achieved without any control strategy changes, which avoids various mode switch detection mechanisms and improves system stability. Furthermore, the proposed control scheme is fully decentralized which reduces the reliance on communication, and enhances the reliability of the microgrid. On the other hand, $V^2-P$ droop approach eliminates the negative effect of widespread constant power loads (CPLs) in dc microgrid. The stability of the proposed control method is illustrated, and the design guideline of some critical control gains is addressed. Finally, the effectiveness of the proposed control scheme is validated by the real-time hardware-in-loop (HIL) platform. [ABSTRACT FROM AUTHOR]

Total-ionizing-dose (TID) effects and low-frequency noise are evaluated in advanced bulk nMOS and pMOS FinFETs with SiO2/HfO2 gate dielectrics. Otherwise identical devices built with and without through-silicon via (TSV) integration exhibit threshold voltage shifts of less than 25 mV and changes in maximum transconductance of less than 1% up to 2 Mrad(SiO2). TSV integration negligibly impacts threshold shifts and degradation of subthreshold swing and $I_{\mathrm{\scriptscriptstyle ON}}/I_{\mathrm{\scriptscriptstyle OFF}}$ ratios. Similar low-frequency noise magnitudes and frequency dependencies are observed before and after TID irradiation for each device type. Effective densities of the near-interfacial electron traps responsible for the noise in the nMOS devices increase as the surface potential moves toward midgap, while effective densities of the hole traps that cause the noise in the pMOS devices increase as the surface potential moves toward the valence band edge. [ABSTRACT FROM AUTHOR]

Total-ionizing-dose (TID) effects are investigated for 22-nm fully-depleted silicon-on-insulator (FDSOI) and 14-nm bulk FinFET charge-trap memory transistors. Electron trapping in the gate dielectric establishes the programmed memory state for both silicon on insulator (SOI) and bulk devices. To first order, ionizing radiation does not interact strongly with programing-induced charges in the gate dielectric for either device type. Hole trapping in the buried oxide dominates the TID response of the 22-nm FDSOI devices. The 14-nm bulk devices with two fins and total effective fin widths of 150 nm are minimally affected by TID, but the subthreshold leakage of devices with 40 fins and total effective fin widths of $3~\mu \text{m}$ increases with increasing TID. When devices are programmed or reprogrammed after irradiation, significant increases in subthreshold slope are observed due to the generation of interface traps, border traps, and/or charge lateral nonuniformities. [ABSTRACT FROM AUTHOR]

Statistical analysis is performed on the totalionizing-dose (TID) response of fourth-generation silicon–germanium heterojunction bipolar transistors, revealing an increasing variance in base current with increasing dose. A 10-fold increase is observed after 2 Mrad(SiO2) of radiation exposure. The postirradiation performance is shown to be poorly correlated with initial performance, revealing potential difficulties for radiation hardness assurance testing. Simple analytical theory is used to demonstrate how TID exacerbates performance variations due to preexisting process-induced variations. Then, technology computer-aided design (TCAD) simulations are used to investigate the fundamental mechanisms driving these statistical changes, particularly process variations associated with the doping profiles. Simulation results reveal potential methods to both predict TID response and mitigate it at the process level. Finally, implications for hardness assurance testing and radiation-tolerant device and circuit design are discussed, especially the need to consider postirradiation variability in the design process for radiation-intense applications. [ABSTRACT FROM AUTHOR]

This paper presents the surface modification and charge transportation mechanism of thin polyimide films. Here, we demonstrate that the surface modification of these films, by using the fluorine gas-phase, improves the charges mitigation and, thereafter, suppress the space charges. The experimental results indicate that the thermal step current for fluorine coated films reduce significantly in comparison to pure polyimide films. The thin layer of fluorine coating helps to release the surface charge, reduce the charge injection from the electrode, provide hindrance for charges to penetrate into the bulk of the films and the higher degree of charge disappearing helps to reduce the space charge growth. [ABSTRACT FROM AUTHOR]

The high penetration of renewable energy sources always leads to the fluctuation of the droop coefficients which are designed in inverse proportion to their rated capacity, and power electronics devices are prone to static instability. Although the impedance-based approaches have been widely studied to deal with this problem, the stability-oriented droop coefficients region identification due to the fluctuation of renewable energy sources is not provided. Thus, this article proposes an impedance-based approach to assess the droop coefficients stability region in the power system consisting of numerous distributed generators (DGs). First, the modified phase margin and opposing argument (MPMOA) forbidden criterion is constituted to acquire the complementary space of the droop coefficients stability region. The MPMOA forbidden criterion is first transformed into the condition that the generalized return-ratio matrix is Hurwitz through mirror, rotation, and translation mapping. In comparison with the previous simplified stability criteria, the conservatism of the proposed criterion is reduced a lot. Thereafter, the droop coefficients stability region is directly calculated by the generalized return-ratio matrix and guardian map theory. Eventually, the simulation and experimental results are provided to validate the conservatism and effectiveness of the impedance-based stability region identification approach. Therein, the simulation results illustrate that the proposed droop coefficients stability operation criterion has lower conservatism than these of the previous simplified stability criteria. Furthermore, the simulation and experimental results illustrate that the proposed stability-oriented droop coefficients region identification approach can provide an effective parameter stability region. [ABSTRACT FROM AUTHOR]