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Heterogeneous graph embedding aims at learning low-dimensional representations from a graph featuring nodes and edges of diverse natures, and meanwhile preserving the underlying topology. Existing approaches along this line have largely relied on meta-paths, which are by nature hand-crafted and pre-defined transition rules, so as to explore the semantics of a graph. Despite the promising results, defining meta-paths requires domain knowledge, and thus when the test distribution deviates from the priors, such methods are prone to errors. In this paper, we propose a self-learning scheme for heterogeneous graph embedding, termed as self-guided walk (SILK), that bypasses meta-paths and learns adaptive attentions for node walking. SILK assumes no prior knowledge or annotation is provided, and conducts a customized random walk to encode the contexts of the heterogeneous graph of interest. Specifically, this is achieved via maintaining a dynamically-updated guidance matrix that records the node-conditioned transition potentials. Experimental results on four real-world datasets demonstrate that SILK significantly outperforms state-of-the-art methods. [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]

Axial flux and radial flux cycloidal permanent magnetic gears are characterized by high gear ratios and high torque densities; however, their rotors experience large unbalanced forces, which stress the bearings used in the gear. This paper presents a new cycloidal magnetic gear topology that combines the radial and axial flux topologies. The paper analyzes the forces and torques contributed by the axial and radial magnets in this topology using 3D finite element analysis. It was found that the perpendicular force is necessary to transfer torque to the high-speed shaft and, thus, cannot be cancelled out, but the eccentric component of the magnetic forces can be largely cancelled out, potentially reducing bearing losses and increasing the lifespan of the bearings used in the gear. A proof-of-concept prototype was constructed. Experimental slip torque results matched 3D finite element analysis (FEA) simulations to within 15%, and testing showed that no-load losses were reduced and the slip torque was increased by combining both axial and radial topologies, compared to using an axial configuration alone. [ABSTRACT FROM AUTHOR]

In order to achieve the purpose of extending the speed range and reducing power electronics devices for the permanent-magnet linear motor drive system, a half-centralized open-end winding (OEW) topology is studied for rail transit applications in this paper. In this topology, compared with the traditional OEW topology, the number of voltage-source-inverters (VSIs) can be reduced from four to three to drive two OEW movers and all these VSIs share a common dc bus voltage. In order to improve the steady-state performances, a four-vector phase model predictive voltage control (FV-PMPVC) is proposed in this paper. Due to the spatial distribution of phase voltage vector (PVV), an orthometric synthesis principle (OSP) is proposed to calculated the duration time for the vector synthesis, which reduces the computation burden and enhances the robustness. Comparing the existing control method, FV-PMPVC can get similar dynamic performances but better steady-state performances. Additionally, the half-centralized topology using FV-PMPVC can have same speed range while less VSIs are required. The effectiveness of FV-PMPVC is verified by experimental results. [ABSTRACT FROM AUTHOR]

This paper presents a reconfigurable dc–dc converter for maximum thermoelectric generator (TEG) energy harvesting in a battery-powered duty-cycling wireless sensor node. The proposed dc–dc converter adopts discontinuous energy harvesting, which operates in single-input dual-output (SIDO) boost, battery-TEG pile-up buck (BTPB), dual-phase buck–boost (DPBB), and battery supplied buck modes with a single shared inductor. Fabricated in a 65-nm CMOS process, the converter adopts an adaptive dead-time controller for zero-voltage switching (ZVS) and an adaptive switch size (ASS) with maximum power point tracking (MPPT) to maximize efficiency in a wide TEG voltage range. The SIDO boost mode achieves 88.5% and 81.1% peak end-to-end efficiency with maximum and no-load conditions (only charging the battery), respectively. The combination of BTPB and DPBB modes to maximize the TEG power extraction during the battery-powered operation results in up to 44% saving in battery power. The battery-supplied buck mode achieves 93.3% peak efficiency. [ABSTRACT FROM AUTHOR]

Link prediction aims at inferring missing links or predicting future ones based on the currently observed network. This topic is important for many applications such as social media, bioinformatics and recommendation systems. Most existing methods focus on homogeneous settings and consider only low-order pairwise relations while ignoring either the heterogeneity or high-order complex relations among different types of nodes, which tends to lead to a sub-optimal embedding result. This paper presents a method named Heterogeneous Hypergraph Variational Autoencoder (HeteHG-VAE) for link prediction in heterogeneous information networks (HINs). It first maps a conventional HIN to a heterogeneous hypergraph with a certain kind of semantics to capture both the high-order semantics and complex relations among nodes, while preserving the low-order pairwise topology information of the original HIN. Then, deep latent representations of nodes and hyperedges are learned by a Bayesian deep generative framework from the heterogeneous hypergraph in an unsupervised manner. Moreover, a hyperedge attention module is designed to learn the importance of different types of nodes in each hyperedge. The major merit of HeteHG-VAE lies in its ability of modeling multi-level relations in heterogeneous settings. Extensive experiments on real-world datasets demonstrate the effectiveness and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

With the proliferation of online social networks, the identification or classification of real-life relationship between users has been very useful for many applications such as financial fraud detection. In real life, usually people with different relationships would present gifts with special meanings to each other on different dates. In many Asian cultures, especially in Chinese culture, the red packet is a traditional form of monetary gift. With the rapid development of the Internet, people gradually began to give electronic red packets instead of paper ones as the means of money gifting on social network platforms. As motivated, in this paper we advocate a novel approach that exploits users’ red packet interactions for users relationship identification on WeChat, one of the largest social platforms in China. Specifically, we analyze the WeChat red packets network, identify the real-life relationship types between users through mining the semantic information of the amount and sending time of each red packet. In order to better capture the red packet gifting behaviors between users for relationship identification, on one hand, we construct an Amount-Date Graph and apply the graph embedding method to learn embeddings of the amount and sending date of each red packet. On the other hand, we propose a novel sequential model, Cross & Attention Sequence Model (CASM), which explicitly learns the interactions between the latent semantic information of each red packet’s amount and sending date in the red packets sequence between two users. To validate our approach, we conduct comprehensive experiments on a real-world WeChat Users Red Packets dataset that involves 8 kinds of real-life relationships. The experiments show that our proposed approach performs significantly better than baselines and achieves 81.70 percent prediction accuracy. [ABSTRACT FROM AUTHOR]

In renewable energy micro-source applications, a wide range of voltage conversion of the step-up converter is an essential part to equalize the typical low voltage of micro-source with DC-bus voltage of Inverter or motor drives. In order to meet this purpose, an ultra-voltage gain step-up DC-DC converter is proposed in this paper. The proposed converter has made an arrangement of the regenerative-boost fed switched inductor and capacitor configurations. Thereby, due to such an organization of structure, the proposed converter can develop an extremely high voltage-gain even at lower duty ratios. In addition, it has the advantage of lower switching stress across all power semi-conductive diodes. Furthermore, this paper describes the steady-state analysis and comparative features of the converter with existing recent literature. Finally, to validate theoretical analysis and test the feasibility and suitability of the proposed ultra-gain converter, the experimental results were observed by a 500 W fabricated prototype. [ABSTRACT FROM AUTHOR]

Conventional half bridge modular multilevel converter (MMC) system will suffer great over-current when there is a dc side fault. Therefore, topology study in sub-modules with dc side fault blocking capability have become one of the hotspots in MMC field. However, fault blocking topologies using conventional IGBT devices must employ more semiconductors than half bridge topology. The extra semiconductor devices employed in the topology will lead to the increase of cost and conduction loss. To reduce the conduction loss of the fault blocking topology, a novel sub-module topology is proposed in this paper. The proposed topology employs reverse blocking devices to form the low conduction loss path. Conduction loss analysis is conducted in this paper to show the priority of the proposed topology. Simulation and experiment results verified the dc fault blocking capability of the proposed topology. [ABSTRACT FROM AUTHOR]

DC-DC converters are needed for the future development of high voltage direct current (HVDC) grids, as they allow to interconnect lines with different voltages and topologies. The dc-dc converters can increase the grid controllability adding power flow control, voltage regulation and/or fault blocking capability. The dc modular multilevel converter (dc-MMC) is a non-isolated solution proposed to interconnect HVDC systems with the same line topology. This paper proposes a new dc-MMC with a control strategy, which allows the converter to interconnect different line topologies (e.g., rigid bipole connected to a symmetric monopole). The paper presents the different line topologies in HVDC installations. Then, a mathematical model with a variable transformation is proposed for the new dc-dc converter. A control structure is proposed and implemented in Matlab/Simulink using an average arm model and simplified dc grids. The results validate the control in normal operation, fault blocking capability and post-fault scenario (degraded mode). [ABSTRACT FROM AUTHOR]

This paper proposes a cooperative optimal power split (COPS) method for a group of intelligent electric vehicles with battery/supercapacitor hybrid energy storage systems (HESSs). To achieve good performance, the proposed COPS method is made up of the upper and lower layers: the upper layer aims at obtaining the optimal power demand sequence and sending it to the lower layer; the lower layer attempts to optimize the power split for HESS. Firstly, to ensure the performance of the proposed method in practice, the resistance of the battery and supercapacitor packs as well as the DC/DC converter efficiency are not assumed to be constants, but modeled well in the paper. Secondly, to achieve the optimal power demand sequence, an upper power demand sequence optimization problem is formulated based on distributed model predictive control (DMPC), in which energy demand is incorporated into the cost function. Thirdly, after receiving the optimal power demand sequence, a hybrid power split optimization strategy is presented to obtain the optimal power split, in which the lower HESS power split optimization problem is formulated based on DMPC to decrease battery aging process and energy consumption. Finally, an improved particle swarm optimization algorithm with multiple dynamic populations is used to solve the formulated upper and lower optimization problems. Simulation results demonstrate that, compared with the benchmark, the proposed COPS method can significantly extend battery lifespan and slightly decrease energy consumption. [ABSTRACT FROM AUTHOR]

This paper proposes a traction unit that combines an interior permanent magnet motor and a PM-assisted synchronous reluctance motor for electric vehicles to improve traction performance, enhance energy efficiency, and reduce cost. The characteristics of three traction units are analyzed and compared, including (a) rear-wheel-drive configuration using one IPM motor; (b) all-wheel-drive configuration using two interior permanent magnet motors; and (c) all-wheel-drive with a combination of one interior permanent magnet motor and one PM-assisted synchronous reluctance as proposed in this paper. The operational characteristics of each motor to achieve a wide constant power speed range are first investigated. Then, the Urban Dynamometer Driving Schedule is utilized to compare and evaluate the operational characteristics, energy consumption, and most importantly, the efficiency of the traction units. Simulation results reveal that the overall efficiency of the proposed traction unit can be improved compared to the other configurations. The advantages and drawbacks of the proposed traction unit are also investigated. Finally, experiments are conducted to validate the analysis. [ABSTRACT FROM AUTHOR]

This paper presents a dual active bridge (DAB) converter with reactive power control capability (Q-capability) for a battery energy storage system (BESS) or an electric vehicle (EV) to deliver vehicle-to-home (V2H) and vehicle-to-grid (V2G) services. The DAB topology is preferable for EV charging systems due to its galvanic isolation and bidirectional power flow capabilities. However, this topology increases reactive current peak and loses zero voltage switching (ZVS) operation at light loads if it is not controlled with improved modulation strategies and proper Q control. This paper proposes a mixed modulation method and a reactive power optimization (RPO) algorithm based on power system load flow concepts. Due to the complexities associated with the analytical solution using time domain analysis, this paper develops detailed universal expressions of a DAB converter using the harmonic analysis method. Analytical identification of ZVS boundaries and DSP implementation of the RPO algorithm become easier with these universal expressions. Multiple modes analysis for different operational states is no longer required. Simulation results have been shown for different modulation strategies of the DAB converters. The theoretical analysis of modulation strategies, RPO algorithm and ZVS operation are validated by experimental results on a DAB prototype. Results show that the proposed control strategy reduces the reactive power and provide ZVS operation over a wide ranges of voltages. [ABSTRACT FROM AUTHOR]

This paper presents an optimization framework for sequential reconfiguration using an assortment of switching devices and repair process in distribution system restoration. Compared to existing studies, this paper considers types, capabilities and operational limits of different switching devices, making it applicable in practice. We develop a novel multi-phase method to find the optimal sequential operation of various switching devices and repair faulted areas. We consider circuit breakers, reclosers, sectionalizers, load breaker switches, and fuses. The switching operation problem is decomposed into two mixed-integer linear programming (MILP) subproblems. The first subproblem determines the optimal network topology and estimates the number of steps to reach that topology, while the second subproblem generates a sequence of switching operations to coordinate the switches. For repairing the faults, we design an MILP model that dispatches repair crews to clear faults and replace melted fuses. After clearing a fault, we update the topology of the network by generating a new sequence of switching operations, and the process continues until all faults are cleared. To improve the computational efficiency, a network reduction algorithm is developed to group line sections, such that only switchable sections are present in the reduced network. The proposed method is validated on the IEEE 123-bus and 8500-bus systems. [ABSTRACT FROM AUTHOR]

This paper proposes to replace controlled islanding, which is a defense mechanism against cascading failures, by tree partitioning whereby some of the tie-lines connecting the clusters are still connected in such a way that the cluster-level graph forms a tree. Tree-partitioning prevents line failures from spreading between clusters, similarly as for islanding, but keeps the clusters connected. That results in three main advantages. Power transfers between the clusters can still take place, helping to balance each cluster and limiting any necessary load shedding. Fewer lines are cut, which reduces the shock to the system. There is no need to re-synchronize the clusters after the emergency. This paper offers a simple graph-theoretic justification for tree-partitioning, rather than one based on the spectral analysis of network Laplacian proposed in the literature. It also proposes a two-stage methodology, which utilizes spectral clustering for splitting a network into tree-connected clusters. Test results performed on the 118 node IEEE test network have confirmed the usefulness of the methodology. [ABSTRACT FROM AUTHOR]

This paper presents a generalized restructured topology for boost, buck-boost and its derived dc/dc converters with rearranging branches to enhance the reliability of the converter. This paper instigates the derivation of state-of-the-art topologies with reduced capacitor voltage stress. Mainly in the restructured topology, the capacitor branch is rearranged in the converter and this redesign venture results in profuse advantages like a better choice of the capacitor with low voltage rating, low equivalent series resistance and reduced voltage stress of the converter. The investigation of the capacitor voltage stress and reliability test is carried out. No extra components are required in this method, the same component count as the conventional converter is maintained. In comparison with the conventional converters, the restructured topology shows the identical output voltage with decreased capacitor voltage stress. Besides reduced voltage stress, the capacitor losses are also less and this allows the capacitor to perform better. As a consequence, the efficiency and lifetime are improved and extended. A detailed illustration of the significance of this restructured concept is presented with a validating analysis. Experimental results from a 600 W prototype are presented with different duty cycles for validating and highlighting the special features of the restructured topology. [ABSTRACT FROM AUTHOR]

To improve the torque accuracy for open-end winding permanent magnet synchronous motor (OEW-PMSM) with common dc bus, it is necessary to eliminate the zero-sequence torque (ZST) caused by zero-sequence current (ZSC) and the third back electromotive force. But the third flux linkage mismatch can enlarge ZSC which causes torque ripple. To deal with the above problem, firstly, a q-axis current injection method combined with deadbeat predictive current control (DPCC) is adopted to inject an extra current into the reference q-axis current. The extra torque generated by this injected current can compensate for ZST. Secondly, to ensure the accuracy of the q-axis injected current, a parameter identification method based on recursive least square (RLS) algorithm with forgetting factor is presented to identify the third flux linkage accurately. The identification value can reduce ZSC and torque ripple under different working conditions. And the accurate q-axis injected current can be obtained to counteract ZST and output accurate torque. Finally, three methods are comparatively analyzed in this paper, namely the traditional DPCC method, the DPCC method with q-axis current injection and the proposed DPCC method based on RLS with forgetting factor. The simulation and experimental results verify the effectiveness of the proposed DPCC method. [ABSTRACT FROM AUTHOR]

This paper presents a control moment gyroscope (CMG) for small satellites, driven and controlled based on axial flux motor principle. The presented structure is coreless with Halbach array rotor and a stator to control the rotational speed/torque and effective gimbal rate/ angle. This topology allows a relatively simple mechanical structure with an equivalent dual gimbal control for limited angle. There are two sets of windings for torque generation along three orthogonal axes, one is 8 pole and other is 6 pole. The winding structure is novel in the sense of accommodating different number of poles $ (>\!4)$ using the same stator slots. Two 3 phase inverters are used to accurately control the torques by energising two sets of windings. Analytical formulation is provided to understand various torque generation mechanisms and 3D FEM simulations are performed to verify the operation and to get better quantitative torque generation capabilities of the CMG along different axes. Finally, a quick experiment prototype is developed to verify the operation with open loop speed control and closed loop tilt position control more qualitatively with off the shelf available components. Independent control of torque in 3 axes was achieved experimentally and the results are explained. [ABSTRACT FROM AUTHOR]

Battery energy storage system (BESS) plays an important role in solving problems in which the intermittency has to be considered while operating distribution network (DN) penetrated with renewable energy. Aiming at this problem, this paper proposes a global centralized dispatch model that applies BESS technology to DN with renewable energy source (RES). The method proposed in this paper aims to minimize the power purchase cost considering network active loss cost as well as voltage deviation penalty cost. Later, second-order cone programming (SOCP) method as well as big M method are applied to make the problem tractable. Last, the method illustrated in this paper is applied and validated on a modified IEEE 33-bus benchmark system to verify the effectiveness of the proposed scheduling model. [ABSTRACT FROM AUTHOR]

Data integration from heterogeneous data sources in low-voltage (LV) power distribution grids will be valuable to distribution system operators (DSOs). The power measurements from customer premises need to be processed with other data such as grid topology, line parameters etc., to deploy smart grid applications (SGA) such as real-time grid monitoring and voltage regulation. The most challenging task for DSOs is to collect and integrate data from several sources as several entities are involved in the data management and access to databases are restricted. This paper presents an opEn common information ${M}$ odel (CIM) BAsed sma ${R}$ t grid application framewor ${K}$ (EMBARK) to address the above-mentioned challenge. EMBARK is developed to be an efficient, modular and scalable architecture for extracting relevant grid related information from various asset management databases. A novel data management functionality is a part of EMBARK that enables data-driven update of settings and parameters of the algorithms behind smart grid applications. The proposed approach is demonstrated and numerically validated using grid data from a medium-sized distribution grid operator in Denmark. The architecture developed and presented in this paper can support all the phases from planning to the actual smart grid operation, i.e., automatically building the models to perform load flows, grid impact studies, planning, asset management etc. [ABSTRACT FROM AUTHOR]

The dc-dc converters with high step-up DC-voltage gain play a vital role in integrating low voltage DC sources. Though several converter topologies are reported in the recent past, attempts have been made to reduce the components, especially the switching devices, passive elements, converter losses, etc., of the converter. A novel DC-DC converter topology, viz., single switched impedance network (SSIN)-based converter with n-stage is proposed in this paper. The operation of the SSIN based converter in continuous and discontinuous conduction modes are discussed. The effect of parasitic elements on DC-voltage gain and efficiency of the SSIN is carried out. The small-signal model of the SSIN converter is derived. The performance of the SSIN converter is compared with the similar converter topologies. The 500 W prototypes of the SSIN with n = 1 and n = 2 are fabricated, and the experimental results are presented in this paper. To improve the converter performance, SiC-based semiconductor devices are used. The SSIN converter with two-stage has low switch loss at 500 W load, improved efficiency during high power and high output voltage operation, the switch stress of Vo/2, etc. [ABSTRACT FROM AUTHOR]

Negative-sequence current is required to be intentionally injected to support the power grid or compensate the imbalanced load in asymmetrical faults utilizing STATCOM. However, the extreme compensation range of negative-sequence current injection becomes complicated when grid voltage becomes asymmetrical. This article presents a novel off-line strategy for negative-sequence current compensation under two typical kinds of asymmetrical grid faults — single-phase voltage drop and double-phase voltage drop, with the following two benefits simultaneously: maximizing negative current compensation capacity; avoiding iterations and reducing computation burdens. In this paper, the mechanism of DC voltage balancing among three phases in STATCOM is analyzed and a new identification method of negative-sequence current compensation range is explored out. To simplify the calculation, this paper takes the ratio of negative-sequence reactive (Iq-) and active (Id-) current as a variable (s). In this way, the relationship between the extreme compensation range, asymmetrical voltage sag depth of power grid h is drawn with MATLAB. Different from the previous iterative method, the off-line identification method is applied to avoid huge iterations. By fitting the curve, the precise ranges of negative-sequence current compensation under different asymmetrical grid faults are approximated as simple polynomials, thus significantly reducing the computation burdens. Simulation and experimental results verify the practicability of the proposed compensation method. [ABSTRACT FROM AUTHOR]

In the future era of intelligent networks, communication technology and network architecture need to be further developed to provide users with high-quality services. The Space-Air-Ground Integrated Networks (SAGIN) is seen as a potential architecture to provide ubiquitous communication and drive the era of the intelligent global network. The space and air segments in SAGIN can assist in offloading traffic from the ground segment. However, in a highly dynamic and heterogeneous network like SAGIN, offloading decisions are easily affected by the incorporated/malicious nodes. How to ensure security and improve network performance becomes a critical problem. In this paper, we address the above problem by jointly using blockchain and federated reinforcement learning (FRL). Firstly, we propose a blockchain-based secure federated learning framework that combines topology information chain and model chain to assist traffic offloading. Then, we propose a node security evaluation and an enhanced practical byzantine fault tolerance (EPBFT) algorithm to secure the traffic offloading process. Furthermore, we describe the traffic offloading problem as a Markov decision problem (MDP) and employ the Blockchain-based Federated Asynchronous Advantage Actor-Critic (BFA3C) algorithm to solve this problem. Finally, the simulation results show that the BFA3C-based algorithm used in SAGIN with/without malicious nodes achieves superior performance in terms of latency and security. [ABSTRACT FROM AUTHOR]

With the widespread deployment of data centers, Internet service providers are expecting more efficient design strategies to build long-haul data center interconnect (DCI) networks. In this paper, we propose a heuristic-based optimization framework to design these networks. Through this framework, network designers can obtain a site-type design scheme that arranges customized site types such as in-line amplifiers, dynamic gain equalizers, optical terminal multiplexers, and electrical regenerators, and three strategies are provided for reference. Taking the quality of transmission as the main metric, and the overall cost of the network as the ancillary measurement, we compare the schemes obtained by the proposed framework against the baseline scheme obtained by a traditional periodic design strategy. Simulations are conducted on a topology of the Tencent DCI network. Under the condition that all schemes ensure that the minimum general signal-to-noise ratio (GSNR) remains above the given GSNR threshold, the schemes designed by our framework can achieve overall cost savings up to 25.73%. [ABSTRACT FROM AUTHOR]

When a fault occurs on the dc side of the voltage source converter based high voltage direct current (VSC-HVDC) transmission system, the fault current rises quickly due to the low damping of the dc system. Using a dc fault current limiter (DC-FCL) to limit the rise of the fault current can significantly reduce the breaking requirements of the DCCB. A topology of a bidirectional active dc fault current limiter (BA-FCL) based on coupled inductor is proposed in this paper. No expensive full-controlled power electronic devices are used in this topology. Only a few half-controlled power electronic devices are used to achieve active control of the current limiting unit. Compared with many topologies of current limiter at present, the fault current limiting effect of BA-FCL is improved significantly while the cost, volume, topology complexity, and control complexity are reduced. The stress analysis and parameter design of the proposed current limiter are carried out. Finally, the simulation case study and hardware experiment are implemented to verify the good economy and current limiting performance of the proposed topology. [ABSTRACT FROM AUTHOR]

As high-speed railways develop rapidly worldwide, the problems of neutral section and power quality are becoming increasingly prominent. These problems affect the normal operation of the power grid and the electric locomotives. The co-phase power supply schemes were proposed by researchers, which can solve these problems well. Among them, the MMC-based scheme (MMC-5 L) is a representative one. The existing scheme, when applied to the auto-transformer (AT)-fed system which is usually adopted by high-speed railways, needs to install an auto-transformer on the output side. To eliminate the auto-transformer and to obtain the more suitable and superior co-phase power supply schemes to AT-fed system, two improved schemes are proposed in this paper based on the novel MMC-based scheme (MMC-6 L) we proposed before. While establishing the mathematical model, creating the control system, and carrying out simulation verification of the proposed schemes, the proposed schemes are compared with MMC-6 L and MMC-5 L in terms of topological characteristics, control system complexity, power loss, and functionality. The results show that while the proposed schemes can fulfill the functions of the co-phase power supply scheme well like the MMC-5 L and MMC-6 L, they are more suitable and superior for the AT-fed system in terms of control system complexity and power loss. Among them, MMC-5L1CB performs best in power loss, and MMC-4L2CB performs best in control system complexity. [ABSTRACT FROM AUTHOR]

The safety of converters is key to the stable operation of AC/DC hybrid power grids after AC faults. Thyristor valve current is a direct manifestation of the converter observability, but there are no measuring elements inside the converter, so the thyristor valve current can be reflected only indirectly through external electrical quantities. This paper proposes a virtual measurement scheme based on the temporal features of the converter terminal current. First, under the action of the trigger pulse, the polarity characteristics of the AC current and temporal features between the valves are utilized to predictive estimate the valve state. Then, when commutation failures occur and the bypass paths form, the conduction state of valve is constructed based on the relationship between AC and DC current. Last, when the valve is to be shut-off in the bypass path, the blocking state of the valve is corrected based on the unidirectional conductance characteristics of the valve. According to the above analysis, combined with the topological current equation of the converter, the valve current can be calculated in the whole process. Through the simulation of the different valve states and bypass paths and analysis of the field record data, the results show that the valve current can still be accurately calculated based on the virtual measurement scheme. [ABSTRACT FROM AUTHOR]

This paper investigates a distributed competition behavior in multi-robot coordination under variable communication topology and switching one. In terms of multi-robot competition-based coordination, a winner-take-all (WTA) strategy is leveraged to address this issue with inevitable environmental barriers incorporated. Moreover, an innovative control theory stimulated gradient neural network (CTSGNN) algorithm is proposed to realize the WTA with prominent robustness and convergence over the traditional ones. Besides, to adapt to diversified local communication modes among multi-robot systems, fast variable and low switching topologies are constructed to establish two dynamic consensus estimators, accompanied by the proposed distributed control schemes. Traditional algorithms are introduced and served as a contrast. Afterward, the global convergence of the proposed algorithm in dealing with multi-robot competitive coordination, the universality of the application scenario, as well as the weaknesses of traditional methods are substantiated theoretically. The effectiveness and superiority of the proposed CTSGNN algorithm and the resultant distributed control schemes by integrating consensus estimators are further sustained via simulations. Note to Practitioners—The motivation of this paper is the coordination operation of multi-robot systems, but it is also applicable to other fields adopting multi-agent systems. Most of the existing researches on multi-robot coordination only exploit their collaborative behavior, which usually leads to the system redundancy and overflow of control costs. To this end, an innovative control algorithm is proposed for this competitive coordination and remains to be perfect in terms of stability and accuracy. Then, this paper establishes new distributed control schemes for multi-robot systems to compete for optimal dynamic task allocation. In this sense, under the premise of ensuring a successful task execution, only a few individuals with strong abilities and advantages are assigned. It is promising to maximize resource utilization, increase efficiency, and be extended to multi-objective scenarios. Note that the design of this scheme takes into account the environmental constraints and physical constraints of the robot itself. Theoretical analysis and preliminary simulation experiments prove the high efficiency of the control scheme. In ongoing research, the competitive coordination tasks of the mobile robot systems and communication delays or fault in control scheme design are explored to expand the operation scope and system extensibility. [ABSTRACT FROM AUTHOR]

This paper proposes a genetic algorithm (GA) combined with ray tracer to generate a cell-free topology of massive MIMO (mMIMO) for the optimal focusing performance serving multiple users. The realistic hardware impairment, for instance the non-ideal power amplifier, is taken into account of the system modeling and topology optimization. To the best of our knowledge, this is the first attempt to apply GA in optimizing the hardware-impaired multi-user cell-free mMIMO. Although the demonstrated numerical analysis is for indoor scenario, the proposed approach is transferable for generic scenarios. In GA, the base station (BS) antennas’ placement is encoded with an adjusted binary matrix representation, which is straightforward for the subsequent genetic operations. The explored candidates by GA can evolve beyond the parents, where the fitness of individuals is evaluated dynamically via a ray tracer radio channel simulator. Compared to the traditional GA, our proposed GA can find better solutions with a faster convergence speed. The algorithm provides near-optimal results in experiments, applicable to generic environment with multiple mobile users and different signal-to-interference-plus-noise ratios. [ABSTRACT FROM AUTHOR]

In this paper, an interior permanent magnet (IPM) machine is presented and optimized for heavy-duty vehicle direct-drive applications. Since efficiency decrease and serious heating come along with excessive core loss under flux weakening control, a rotor topology with the combination of the eccentricity structure and magnetic barriers is proposed. The key is to achieve the comprehensive optimization of the proposed rotor topology to satisfy the different requirements under diverse operating points. Then, a multi-objective automatic parallel optimization method is applied, which simultaneously analyzes multi-condition operation without weight coefficients defined artificially. The 3D Pareto solution set is generated by using nature inspired evolutionary algorithm based on the high-precision metal-modals of optimal prognosis, which reduce the needed computation cost significantly. Moreover, the back electromotive force total harmonic distortion, torque and core loss of the optimal machine are analyzed at corresponding operating points. Finally, the finite-element results are validated by experiments based on a prototype machine. [ABSTRACT FROM AUTHOR]

The electric drive power density and fault tolerance capability are of fundamental importance in many applications such as aerospace and traction applications. The modularization and the physical integration of the electric motor and the power converter components can lead to a high power density and a high fault tolerance drive system. The power density of a highly modular and integrated drive based on an axial flux permanent magnet synchronous machine and GaN converter is investigated in this paper. Several power density boosting techniques are provided and investigated using CFD simulations. These techniques incorporate optimization of the converter topology, the geometry of the shared cooling structure of the electric machine and the power converter and optimal selection of the materials in the path of heat transfer from the machine and the power converter to the cooling ambient. The power density of the reference integrated design is increased from 1.12 kW/ $l$ to 2.14 kW/ $l$. The CFD computations are validated by extensive measurements on a modular integrated setup. [ABSTRACT FROM AUTHOR]

The paper develops two computationally efficient models, namely a detailed equivalent model and an average-value model, with provisions for representation of the critical state of converter blocking, for modular multilevel converters with embedded storage. These models are indispensable in the simulation of dc faults. The developed detailed equivalent model provides accuracy that matches electromagnetic transient (EMT) simulations, with much reduced computational burden; the developed average-value model represents the averaged behavior of the converter by neglecting switching transients. Both models are extensively evaluated in the context of an HVDC system against benchmark results form a detailed switching model developed in PSCAD/EMTDC. The results confirm the validity and accuracy of the models for steady state, transient, and faulted operating conditions including when the converter is blocked in response to a dc fault. [ABSTRACT FROM AUTHOR]

With the widespread application of lithium-ion battery packs, it calls for efficient balancing methods to improve the performance of these battery systems. The relevant research has focused on the design of equalization circuits and control strategies while neglecting quantitative analysis and comparison of battery active equalization structures from the systematic level. In this paper, we propose an improved system-theoretic modeling approach for active equalization structures that takes into account the battery's constraints, including equalization current rate and SOC operation range. Accordingly, the mathematical models of various active equalization structures are derived that can describe their equalization dynamic behavior. Then, the analytical algorithms are developed to estimate the balancing time of active equalization structures online. Finally, extensive numerical simulations are conducted to evaluate and compare the average performance of these equalization systems in term of equalization time. It then comes up with a comprehensive comparison among them. Consequently, the Multicell-to-Multicell (MC2MC) balancing structure benefits the fast balancing speed and the lowest sensitive to initial batteries’ SOCs. The global structure has the lowest implementation cost and the series structure benefits the simplest control. Moreover, the module-based structures have faster balancing speed when each module contains about 4–6 batteries. [ABSTRACT FROM AUTHOR]

With the ability to acquire and process large-scale traffic big data, a cooperative intelligent transport system can be realized. Identifying important nodes in a traffic network contributes to better traffic control, which plays a more critical role in improving the traffic efficiency of a cooperative intelligent transport system. However, existing traffic node importance evaluation methods rely on manually designed metrics such as betweenness, degree, which may lead to biased results. Meanwhile, the traditional method of iteratively deleting nodes is unsuitable for a large-scale traffic network. In this paper, we propose a novel traffic node importance evaluation method based on clustering in represented transportation network. Specifically, the proposed method first construct a length-weighted network based on the geographic road network. Then, it learns the low-dimensional embeddings of nodes employing network representation learning. Finally, it clusters each nodes with a machine learning method and identifies the critical nodes through vehicle flow of different nodes. Experimental results on the real-word dataset show that our proposed method has excellent performance compared to baseline methods. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study on the impact of information flow topologies on the resilience of distributed algorithms that are widely used for estimation and control in vehicle platoons. In the state of the art, the influence of information flow topology on both internal and string stability of vehicle platoons has been well studied. However, understanding the impact of information flow topology on cyber-security tasks, e.g., attack detection, resilient estimation and formation algorithms, is largely open. By means of a general graph theory framework, we study connectivity measures of several platoon topologies and we reveal how these measures affect the ability of distributed algorithms to reject communication disturbances, to detect cyber-attacks, and to be resilient against them. We show that the traditional platoon topologies relying on interaction with the nearest neighbor are very fragile with respect to performance and security criteria. On the other hand, appropriate platoon topologies, namely $k$ -nearest neighbor topologies, are shown to fulfill desired security and performance levels. The framework we study covers undirected and directed topologies, ungrounded and grounded topologies, or topologies on a line and on a ring. We show that there is a trade-off in the network design between the robustness to disturbances and the resilience to adversarial actions. Theoretical results are validated via simulations. [ABSTRACT FROM AUTHOR]

In this paper, a data-driven event-triggered cooperative control (DD-ETCC) scheme is proposed for the multiple subway trains to realize speed tracking and dynamic headway adjustment under switching topologies. Firstly, a nonlinear subway train system is transformed into a linearization data model, and the complex nonlinear terms caused by mechanical and aerodynamic resistance and operating environment conditions are estimated by projection algorithm. Then, the DD-ETCC scheme based on the linearization data model and the asynchronous event-triggered condition for multiple subway trains with switching topologies is designed. Theoretical analysis shows that the speed tracking errors of multiple subway trains are bounded, and the headway distances of consecutive trains are stabilized in a safe range with the proposed scheme. Finally, the effectiveness of the proposed DD-ETCC scheme of multiple trains is illustrated by subway train simulations. [ABSTRACT FROM AUTHOR]

This paper focuses on the issue of network connectedness (NC) in security-constrained optimal transmission switching problems, which is complicated by branch contingencies and corrective line switching. Two criteria are firstly proposed with the principle of preserving NC as much as possible within reasonable limits. By extending the electrical flow based NC constraints, a proposition is derived to associate different cases of NC with the optimum of a linear program, yielding the mathematical formulation of the NC criteria. By Karush-Kuhn-Tucker conditions, this formulation is further transformed into a tractable version which can be incorporated with existing SCOTS models without affecting the applicability of original solution approaches. Finally, case studies on various networks and SCOTS models demonstrate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

DC circuit breakers (DCCBs) play a significant role in obtaining the reliability and stability of DC power systems. Selective and fast isolating of faults minimizes the power supply outages to end electricity users and protects the power converters implemented in the DC system. During the last decades, DCCBs have been deeply investigated in industry and academia. There has been impressive progress in terms of efficiency, response time, power-density, lifetime, and electrical operating ratings. Introducing wide bandgap (WBG) devices further has motivated researchers to propose more efficient and novel topologies. This paper provides a point of reference and a background review for DCCBs from novel aspects, fulfilling absent parts in the literature. The elaborated subjects include current commutation circuitry, DCCBs trip-curves developments, newly added functions to DCCBs, as well as marketing analysis. The advancements of DCCBs are surveyed and development needs are recognized. This paper aims to identify the future research needs of DCCBs for emerging DC power systems. [ABSTRACT FROM AUTHOR]

Emerging communication technologies allow to reconfigure the physical network topology at runtime, enabling demand-aware networks (DANs): networks whose topology is optimized toward the workload they serve. However, today, only little is known about the fundamental algorithmic problems underlying the design of such demand-aware networks. This paper presents the first bounded-degree, demand-aware network, $\textit {cl-DAN} $ , which minimizes both congestion and route lengths. The degree bound $\Delta $ is given as part of the input. The designed network is provably (asymptotically) optimal in each dimension individually: we show that there do not exist any bounded-degree networks providing shorter routes (independently of the load), nor do there exist networks providing lower loads (independently of the route lengths). The main building block of the designed $\textit {cl-DAN} $ networks are $\textit {ego-trees}$ : communication sources arrange their communication partners in an optimal tree, individually. While the union of these ego-trees forms the basic structure of $\textit {cl-DANs}$ , further techniques are presented to ensure bounded degrees (for scalability). [ABSTRACT FROM AUTHOR]

This paper is the first to investigate both communication and control in traffic channel (TCH) and control channel (CCH) respectively when considering leader-follower formation keeping in UAV communication networks. In this paper, we analyze the relationship between the mutual interference and information exchange cost, and then formulate the joint channel and link selection problem as a two-way consensus game between CCH and TCH. To characterize the two-way choice of link selection, we creatively propose the generalized two-way consensus equilibrium (GTCE) to capture the stable state. Then, we prove that the formulated game has at least one pure-strategy GTCE which can maximize the UAV communication network utility. A distributed better reply based joint channel and link selection (BRJCLS) algorithm as well as two-dimensional minimum spanning tree (MST) based initialization (TMSTI) algorithm is proposed to achieve the GTCE. Simulation results are presented to show the convergence and effectiveness of the formulated two-way consensus game and proposed algorithms. [ABSTRACT FROM AUTHOR]

Most microgrid protection schemes found in published literature suffer from a lack of generality in that they work well for the assumed topology, including type and placement of sources. Other generic protection schemes tend to be too complicated, too expensive, or both. To overcome these drawbacks, a topology-agnostic, scalable, and cost-aware protection based on fundamental principles that work in the presence of high penetration of inverter-based resources (IBRs) is developed and tested in this paper. The protection system also implements stable automatic reconfiguration of the healthy sections of the system after clearance of fault, thus increasing resilience by self-healing. To achieve this ambitious goal, stable inverter models are developed that operate in unbalanced networks in grid-connected and islanded modes, even with 100% IBRs, share power without conflicting controls, and can ride through faults while limiting fault currents. The scheme is tested for primary and backup protection and reconfiguration on the IEEE 123-node feeder in grid-connected and islanded modes with 15 IBRs connected to the system. [ABSTRACT FROM AUTHOR]

The advancements in smart grid technologies had brought forth the prospect of self-healing distribution grid through intentional islanding, aided by the steadily rising penetration of inverter-based distributed generations (IBDGs). Adaptive protection is the key enabler for this resilient grid architecture. For cost-effectiveness, overcurrent relays (OCRs) with adaptive features had been proposed, often with the sensitivity problem due to low short-circuit current magnitude from the IBDG taken into consideration and largely addressed. However, apart from this widely discussed sensitivity problem, there is an underlying issue on selectivity of the OCR which is frequently disregarded when designing an adaptive overcurrent protection scheme for IBDG dominated microgrid. This selectivity problem is mainly caused by the current diversion to load during fault, which is often disregarded when performing OCR grading for a conventional grid. In this paper, this selectivity problem of the OCR is discussed in depth through a comparative study of conventional grid and a modern IBDG dominated grid. The coordination time interval margin violations problems are demonstrated through theoretical calculations and real-time hardware-in-the-loop experiments. This research aims to provide better insights into the selectivity problem as a step towards achieving a cost-effective yet reliable overcurrent-based adaptive protection for IBDG dominated microgrid. [ABSTRACT FROM AUTHOR]