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This paper investigates the secrecy performance of a spectrum sharing network, where ${N}$ legitimate source-destination pairs orderly access the shared spectrum for communication, while an eavesdropper (E) attempts to tap the legitimate information transmission. To improve the physical layer security, we propose two jamming strategies that can intelligently switch between jamming and non-jamming, namely, suboptimal jammer selection (SJS) scheme and optimal jammer selection (OJS) scheme. Specifically, when a user pair is assigned to access the shared spectrum, another source is chosen as a friendly jammer in order to create intentional interference at E. For the purpose of comparison, we present the non-jammer selection (NJS) scheme as a benchmark. Analytical closed-form secrecy outage probability expressions of NJS, SJS and OJS schemes are derived over Nakagami- ${m}$ fading channels. We further present an asymptotic secrecy outage probability analysis to evaluate the secrecy diversity gain performance of NJS, SJS and OJS schemes. Numerical results show that the secrecy outage probability performance of OJS scheme is better than SJS and NJS schemes in the low average channel power gain ${\mathop \Omega \nolimits _{D} }$ region. Furthermore, the secrecy outage probabilities of NJS as well as SJS and OJS schemes converge to each other with the increase of ${\mathop \Omega \nolimits _{D} }$ , due to the fact that the OJS and SJS scheme will switch to NJS scheme when ${\mathop \Omega \nolimits _{D} }$ tends to infinity. [ABSTRACT FROM AUTHOR]

In subway systems, increasing attention has been paid to improve energy efficiency due to remarkable energy consumption for rail transportation operation. The optimization of single-train driving control and multi-train operation synergy are two critical and closely related aspects for energy saving, but they are rarely solved in an integrative manner. The comprehensive study on these two aspects is a complex, large-scale, multi-variable and constrained task, which involves nested, coupled and mutual-input optimization processes. This paper proposes an energy-efficient integrated model, which includes optimizing single-train operation control in an inner model and multi-train operation synergy, committing to the utilization of regenerative braking energy (RBE) in an outer model. A parallelized particle swarm optimization based on Map-Reduce (PPSO-MR) algorithm is proposed to solve the integrated model to reduce the execution time. Two concepts of temporal-spatial record and time shift are introduced to derive the movement of a train at inter-stations for the operation adjustment of multiple trains on a subway line. Experimental results show that the proposed control model solved by the holistic optimization approach can achieve lower energy consumption with fast execution time. This study provides the novel model and algorithm to obtain energy-saving schedules serving the multi-train operation coordination. [ABSTRACT FROM AUTHOR]

Two-stage AC-DC converters are considered as a prominent solution for DC-type electric vehicle (EV) chargers. However, this kind of architecture suffers from high switching losses with large heatsink and DC-link capacitor volume. To relieve this issue, this paper presents a new hybrid modulation for DC-type EV chargers, where a two-phase clamped discontinuous pulse-width-modulation (DPWM) in the front-end circuit is cooperated with the variable frequency triangular-current-mode (TCM) zero voltage switching (ZVS) or its simplified implementation, i.e., boundary-ZVS (B-ZVS) strategy, in the back-end circuit. The former can stop the switching actions in the front-end stage during two-thirds of the grid period, while the AC currents are at their highest values, which can yield to the best switching loss reduction and deliver high power factor operation. Besides, TCM-ZVS or B-ZVS modulations can achieve ZVS turn-on action for all semiconductors during all operating range in the DC-DC stage to further reduce the power losses on the semiconductors. With such characteristics, the proposed strategies can reduce the switching losses of the system to the best extent, and thus allow an enhancement of the system power density by improving the power conversion efficiency. The proposed strategy is described, analyzed, validated, and benchmarked in a 5 kW SMD SiC MOSFET-based two-stage AC-DC converter. A 99% power efficiency can be achieved with the solution implementing the TCM-ZVS strategy at an output voltage of 400 V and rated power. [ABSTRACT FROM AUTHOR]

In this paper, a switched multibeam multi-sector array antenna is proposed to provide 3-D coverage for vehicle to infrastructure (V2I) under 5G-IoT application framework. The multi-sector design is optimized using a quality-conscious communication area synthesis process to achieve $\mathbf {360}^\circ$ coverage in azimuth. Each sector of the design has two microstrip array antenna (MAA) to obtain coverage in the upper and lower halves of the elevation region. The proposed antenna is designed to enhance frequency-dependent beam squint phenomena exploited to achieve multibeam coverage in the elevation region. The simulation results of the proposed antenna having $\mathbf {3\times 2}$ size of MAA indicates the achieved desired radiation characteristics, and a prototype of the same operating in WLAN band ($\mathbf {5.15-5.825}$ GHz) is fabricated for verification. The experimental results show the maximum realized gain is $\mathbf {7.85}$ dBi and the beam tilt of $\mathbf {10.8}^\circ$ to $\mathbf {46.8}^\circ$ in elevation is achieved at central frequencies $\mathbf {5.15}$ GHz and $\mathbf {5.825}$ GHz, respectively. The coverage obtained is $\mathbf {360}^\circ$ in azimuth and $\mathbf {93.6}^\circ$ in elevation. The signal to interference ratio is measured around the antenna, which shows interference suppression of more than $\mathbf {10}$ dB achieved between the MAAs of alternate sectors. Moreover, the port isolation is better than $\mathbf {26}$ dB. Hence, sixteen simultaneous beams utilizing frequency re-use can be operated in the 3-D space around the access point to communicate with multiple drones/vehicles and IoT nodes to realize a smart vehicular application. [ABSTRACT FROM AUTHOR]

Improving the efficiency of traffic signal control is an effective way to alleviate traffic congestion at signalized intersections. To achieve effective management of the system-wide traffic flows, current research tends to focus on applying reinforcement learning (RL) techniques for collaborative traffic signal control in a traffic road network. However, the existing collaboration-based methods often ignore the impact of transmission delay for exchanging traffic flow information on the system. Most of the studies assume that the signal controllers can collect all instantaneous vehicular features without delay. To fill the gap, we propose an RL-based cooperative traffic signal control scheme considering the data transmission delay issue in a traffic road network. In this paper, we (1) design our new RL agents to cooperatively control the traffic signals by improving the reward and state representation based on the state-of-the-art max-pressure control theory; (2) propose a traffic state prediction method to address the data transmission delay issue by decreasing the discrepancy between the real-time and delayed traffic conditions; (3) evaluated the performance of our proposed work on both synthetic and real-world scenarios with a different range of data transmission delays. The results demonstrate that our method surpassed the performance of the previous max-pressure-based traffic signal control methods and addressed the data transmission delay issue. [ABSTRACT FROM AUTHOR]

On March 31, 2019, a 500 kV air-core, shunt reactor at a large generating station in BC Hydro was damaged shortly after four unit transformers were simultaneously energized from a 500 kV series and shunt compensated line source. Forensic investigations revealed that the controlled switching system, controlling the instant at which each breaker phase closes during energization to minimize inrush current, had failed. Uncontrolled closing led to under-damped, high-magnitude and sub-synchronous currents. Protection tripped and isolated the four transformers, followed shortly by shunt reactor protection tripping. Before the reactor could be isolated by circuit breakers, a damaging internal fault developed. This paper presents forensic investigation describing sequence of events leading up to reactor damage and shares the lessons learned with the peer utilities having similar installations.    [ABSTRACT FROM AUTHOR]

The integration of overhead lines in future MTDC grids leads to a higher fault rate compared to cables. Most of the faults are considered to be non-permanent, so that the line can be reconnected after dielectric recovery. The auto-reclosing procedure in HVDC systems reveals new challenges since multiple restrikes are possible within a short period of time. This paper proposes an auxiliary circuit for DC Circuit Breakers (DCCB) which enables to use the DCCB internal capacitor for the line pre-energization. A comprehensive description of the switchgear operations during the pre-energization sequence is provided and the fault property identification method is defined. The method is validated by simulations in a MTDC grid and a sensitivity analysis is carried out using EMTP-RV. [ABSTRACT FROM AUTHOR]

Condition assessment of Medium Voltage switchgears requires effective, but inexpensive solutions to become a common practice. On the other hand, failure of a switchgear component can cause cascade effects and outage of other apparatus, in addition to significant economic losses due, e.g., to lack of energy availability. A major diagnostic property to evaluate switchgear health and reliability is partial discharges, being a direct cause of failure of organic insulation systems. A new approach to automatic, self-assessment of switchgear reliability based on partial discharge, PD, acquisition and processing, as well as a new type of PD sensor solution are presented in this paper. The sensor is based on the capacitive divider existing in most bushings to indicate the presence or absence of voltage. The innovative automatic software is able to provide automatic noise and PD separation, noise rejection and type of PD-source identification. The embedded bushing sensor has been tested on switchgears in the presence of defective components as cable terminations and bushings. Results show that the sensor, coupled with the automatic software, is able to provide good sensitivity compared to other sensors, and good capability to locate the cabinet and identify the type of source generating partial discharges. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed coordinated voltage control scheme for distribution networks with distributed generation (DG) and on-load tap changer (OLTC). In this scheme, static synchronous compensators (STATCOMs), DG units and OLTC are coordinated to regulate voltages of all buses to be close to the nominal value in the distribution network, mitigate voltage fluctuations, and minimize the number of operations of OLTC while considering different temporal characteristics of voltage regulation devices. The optimization problem of coordinating DG units and STATCOMs is decomposed by the gradient projection (GP) method. The local controller optimizes the reactive power outputs of DGs and STATCOMs according to local voltage and reactive power measurements, and still achieves the optimal coordination of DG units and STATCOMS in a decentralized manner without a central controller or communication between local controllers. The OLTC control scheme is designed to correct the long-term voltage deviations based on model predictive control (MPC) while minimizing the number of operations. The local controllers send the calculated reactive power references of DG and STATCOMs to the OLTC controller, which achieves distributed coordinated voltage control and mitigates the computation burden. A distribution network with two 20 kV feeders and 8 DG units was used to validate the control performance of the proposed coordinated voltage control scheme. [ABSTRACT FROM AUTHOR]

In the face of increasing natural disasters and an aging grid, utilities need to optimally choose investments to the existing infrastructure to promote resiliency. This paper presents a new investment decision optimization model to minimize unserved load over the recovery time and improve grid resilience to extreme weather event scenarios. Our optimization model includes a network power flow model which decides generator status and generator dispatch, optimal transmission switching (OTS) during the multi-time period recovery process, and an investment decision model subject to a given budget. Investment decisions include the hardening of transmission lines, generators, and substations. Our model uses a second order cone programming (SOCP) relaxation of the AC power flow model and is compared to the classic DC power flow approximation. A case study is provided on the 73-bus RTS-GMLC test system for various investment budgets and multiple hurricane scenarios to highlight the difference in optimal investment decisions between the SOCP model and the DC model, and demonstrate the advantages of OTS in resiliency settings. Results indicate that the network models yield different optimal investments, unit commitment, and OTS decisions, and an AC feasibility study indicates our SOCP resiliency model is more accurate than the DC model. [ABSTRACT FROM AUTHOR]

This paper proposes a multifunctional control strategy and associated control algorithms for distributed wind-turbine (WT) based nano-grids connected to a distorted utility-grid. The contribution is on a new strategy with innovative control algorithms to coordinate multiple converters for a multitasking operation of the nano-grids. The novelty is on a unique control design with feasibilities: maximizing the generated power from WT, maintaining power quality in both ac- and dc-sides under critical conditions of the power grid, and improving power quality against distortion from local nonlinear loads under a reduced switching frequency. A robust fast-dynamic predictive control method is developed for current controllers to fulfil the multifunction. Unconstrained deadbeat control inputs are derived in twofold targets: ensuring fast dynamic response and significantly reducing both the computation and switching frequency for finite predictive control. The control system is applied on a permanent-magnet synchronous generator (PMSG) WT-based nano-grid connected to a distorted utility-grid. An OPAL-RT-based real-time platform is used for comparative studies among the proportional integration (PI) control, finite predictive control (FS-MPC), and proposed control method. The performance verification exhibits the power quality improvement in both the nano- and utility-grids under critical conditions via high-performed regulation of currents, voltages, reactive power, and rotor-speed of the PMSG-WT. [ABSTRACT FROM AUTHOR]

The successful mission of CubeSat require reliable and fault-tolerant electrical power system (EPS) that powers all the other subsystems and payloads. Several studies have shown that EPS failure has been one of the main contributors for the CubeSat mission failure. The main objective of this paper is to enhance the lifetime of CubeSats EPS by proposing a distributed EPS architecture and power-down mode. The distributed architecture consists of independent converters for maximum power point tracking operation of photovoltaic (PV) panels. This is possible by using gallium nitride field-effect transistors to reduce the converter footprint and placing the converters on the back-side of the PV panels. Also, single-inductor based $N$ -1 redundant converters for generation and load-side are proposed to provide uninterrupted operation during component failures. Thus, the proposed distributed architecture not only improves the reliability but also facilitates placement of redundant converters to achieve the fault-tolerant capability. To further reduce the electrical and thermal stresses on the semiconductor devices and thus, improve the EPS life span, a novel power-down mode is proposed for the power converters. In this mode, semiconductor devices are switched-off whenever the power processed is below the threshold level and/or no-load operation. Reliability block diagrams are illustrated to demonstrate the reliability improvement and calculations shows that the proposed distributed architecture has higher reliability than the conventional EPS architecture. All the proposed concepts are validated using a prototype developed based on the specifications of MYSAT-1, which is an 1U CubeSat launched by Khalifa University. [ABSTRACT FROM AUTHOR]

In a recent work, Beierle, Brinkmann and Leander presented a recursive tree search for finding APN permutations with linear self-equivalences in small dimensions. In this paper, we describe how this search can be adapted to find many new instances of quadratic APN functions. In particular, we found 12,921 new quadratic APN functions in dimension eight, 35 new quadratic APN functions in dimension nine and five new quadratic APN functions in dimension ten up to CCZ-equivalence. Remarkably, two of the 35 new APN functions in dimension nine are APN permutations. Among the 8-bit APN functions, there are three extended Walsh spectra that do not correspond to any of the previously-known quadratic 8-bit APN functions and, surprisingly, there exist at least four CCZ-inequivalent 8-bit APN functions with linearity 27, i.e., the highest possible non-trivial linearity for quadratic functions in dimension eight. [ABSTRACT FROM AUTHOR]

The large antenna arrays with hybrid analog and digital (HAD) architectures can provide a large aperture with low cost and hardware complexity, resulting in enhanced direction-of-arrival (DOA) estimation and reduced power consumption. This paper investigates the trade-off between DOA estimation and power consumption in large antenna arrays with HAD architectures. Particularly, the DOA estimation problem of fully-connected, sub-connected (SC), and switches-based (SE) hybrid architectures is formulated into a unified expression, with the compression matrix in a time-varying form. Based on this model, we derive a dynamic maximum likelihood (D-ML) estimator that is suitable for both HAD and conventional fully digital (FD) structures, and the closed-form expression of Cramér-Rao bound (CRB) to evaluate the performance limit of the D-ML estimator for different HAD structures. The theoretical CRB analysis in the single-source case reveals that, the SC structure has the ability to achieve approximately the same performance as the FD structures at DOAs around zero, but suffers from the inherent angle ambiguity because of the antenna grouping. In addition, we propose a dynamic SC (D-SC) structure that is proved to eliminate the angle ambiguity with time-varying phase shifters, and a switch optimization (SWO) algorithm to minimize the CRB of SE structures. Finally, we introduce a new metric, DOA efficiency, to measure the trade-off between the DOA estimation performance and power consumption of different structures. Simulation results verify our theoretical analysis and the superiority of the proposed D-SC structure and the SWO algorithm. [ABSTRACT FROM AUTHOR]

This article develops a series of improved Z-source dc–dc converters to realize additional voltage pumping and high power density through two propositions. Proposition 1 develops two improved positive- and negative-connected Z-source dc–dc converters (IPZSC and INZSC), using the same number of components as in the existing voltage pumping Z-source converter. Based on Proposition 1, Proposition 2 proposes four novel embedded Z-source dc–dc converters (EZSCs) by placing the source in a specifically designed position, which realizes lower voltage stresses across capacitors. Various technical aspects of the proposed EZSCs, including operations, power losses, and small signal stability analyses are detailed in this paper. Besides, comparisons between the proposed series of improved Z-source dc–dc converters and other existing Z-source dc–dc converters are thoroughly made to demonstrate the better performance of the EZSCs. Finally, experiments are conducted to well validate the effectiveness and superiority of the proposed converter circuits. [ABSTRACT FROM AUTHOR]

Objective: This paper presents a Proof-of-Concept (POC) design and implementation of a biosensing and communication system that can be used for biotelemetry in neural and Gastrointestinal (GI) applications. Methods: Our proposed system is based on backscattering from a semi-passive Radio-Frequency-Identification-Device (RFID) implemented using an Application Specific Integrated Circuit (ASIC) in which electronic switching between transistor gates in high and low states create an impedance difference, thereby effectively changing the ASIC's Radar Cross Section (RCS) and thus modulating its backscattered field. The ASIC is used in conjunction with a biosensor to measure and transmit vital signs from within the body. With this system, we conducted backscatter propagation experiments through different biological and phantom tissues (in ex-vivo and in-vitro) in the GI and neural environments. Results: Our results show that the backscattered waveforms can penetrate tissues of various compositions and thicknesses with power received at distances of up to 55 cm away from the RFID ASIC. Furthermore, results from single- and multi-bit biotelemetry measurements showed a high signal fidelity with low Bit-Error-Rate (BER) while being able to resolve varying tissue temperatures measured by the biosensor in our system. Conclusion: We realized a POC system in which on-chip transistor switching in an ASIC can be used to achieve backscatter communication and biosensing. This system is deployable in neural and GI applications. Significance: Our findings in this work will provide an important practical basis for the design and development of RFID ASIC for biosensing and biotelemetry in medical applications. [ABSTRACT FROM AUTHOR]

Data center networks typically adopt multi-rooted tree topologies to provide high bisection bandwidth. Various fine-grained load balancing schemes have been proposed to split flows across multiple paths. However, data center networks suffer from many uncertainties such as highly dynamic traffic. These uncertainties easily make network become asymmetric, resulting in significant packet reordering. Unfortunately, existing solutions passively deal with packet reordering based on a threshold and hardly adapt to asymmetric networks because of lacking the explicit reordering feedback. These solutions either fail to quickly respond to packet loss or cause unnecessary fast retransmission, which reduces link utilization and increases flow completion time. In this paper, we propose a fine-grained load balancing scheme RMC to eliminate the impact of packet reordering and handle uncertainties in asymmetric networks. To avoid unnecessary fast retransmission, the switch proactively identifies reordered packet according to local queue length and global path latency. Furthermore, we employ a coding technique with redundancy optimization to reduce long-tailed flow completion time under network asymmetry. Through a series of large-scale NS2 simulations and testbed experiments, we demonstrate that RMC effectively avoids unnecessary fast retransmission under different network scenarios and reduces flow completion time by up to 72% compared with state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

This paper presents an isolated single-stage on-board electric vehicle charger without an intermediate DC-link. Based on an isolated current-source topology, the converter features soft-switching in semiconductors regardless of load variation for the full AC line voltage range. Moreover, it requires no external snubber or clamp circuits. The power factor correction and voltage regulation are provided by a relatively simple phase shift modulation, while the amount of circulating energy is kept at minimum. The charger is distinguished by its efficiency characteristic – the maximum is achieved in the constant power charging mode. The control method, component stresses, and design constraints of the topology are analyzed. The concept is verified using a 3 kW experimental SiC-based prototype, which reaches a peak efficiency of 96.4%. Moreover, the charger has demonstrated efficiencies above 95% with the THD of 4.1% when operating in constant power mode at the maximal power. [ABSTRACT FROM AUTHOR]

In a previous paper (Part 1) the authors have performed the simulative evaluation of the life lost by HVDC extruded cables subjected to long TOVs occurring in VSC HVDC cable systems. The conclusions were that it cannot be completely ruled out that the field levels and the duration of such TOVs are a potential threat to certain cable designs, and tests other than Load Cycling Type Tests after CIGRÉ Technical Brochure 496 could assess quantitatively the potential threat associated with long TOVs. For these reasons, in this Part 2 superimposed switching impulses applied during Type Tests after TB 496 are analyzed in order to check if such impulses might be equivalent to long TOVs as for their electro-thermal stress effects on extruded insulation. The analysis is similar to that carried out for long TOVs in Part 1, i.e., it consists of: calculating the electric field during superimposed switching impulses; comparing it with the field during long TOVs; calculating with Miner's law of cumulated damage the life lost during superimposed switching impulses and comparing it with the loss of life during TOVs. A brief literature survey of potential high field effects during long TOVs is also reported. [ABSTRACT FROM AUTHOR]

AC–DC line-commutated converters (LCCs) are widely utilized in existing and emerging ac–dc power systems. Analysis of such systems under balanced and unbalanced conditions is often carried out using electromagnetic transient (EMT) simulation programs. Therein, the detailed switching models of LCCs are often the computational bottlenecks for system-level studies. Recently, the parametric average-value models (PAVMs) have been developed to achieve fast and efficient simulations of switching converters. In this paper, the PAVM methodology is extended to consider operation of LCCs under unbalanced conditions in the ac network. This is done in the extended PAVM by formulating the ac-side harmonics in positive and negative sequences as well as the dc-side harmonics (i.e., ripples) with respect to the ac network imbalance. The new PAVM is validated experimentally and by simulations, and is demonstrated to be accurate in reconstructing the ac and dc waveforms under unbalanced conditions in the ac network. Meanwhile, the proposed PAVM is computationally much faster than its detailed switching model counterpart. [ABSTRACT FROM AUTHOR]

This paper presents a new single-source three-phase seven-level inverter with an inherent three-time voltage boosting capability for medium-voltage applications. The proposed topology is comprised of series connection of two switched-capacitor (SC) networks with an added half-bridge module per phase. Each of such integrated SC networks requires a single capacitor associated with three active power switches. The three-time voltage boosting feature of the proposed topology can reduce the dc-link voltage requirements by 50% in comparison to the traditional neutral point clamped (NPC), flying capacitors, active NPC (ANPC), hybrid clamped ANPC, and cascaded H-bridge topologies, and 75% to advanced ANPC topologies. It can also reduce the number of required switches and capacitors as well as their voltage stresses compared to those state-of-the-art topologies reported in the literature. By integrating “n” number of added SC networks in the proposed seven-level basic topology, the number of output voltage levels can be extended to 2n+3 per phase. A finite control set model predictive control algorithm is also derived to control the converter in both the active and reactive power exchanges modes without distorting the generated grid current quality. The capacitor voltage balancing is inherent in the proposed topology, and thus, there is no need for any additional voltage balancing circuit, which further reduces the control complexity. The performance of the proposed topology and its control algorithm are validated by several measurement results. [ABSTRACT FROM AUTHOR]

An improved two-stage model predictive current control (MPCC) for three-phase three-level converters in the paper, which can simultaneously achieve common-mode voltage (CMV) reduction, effective dc-link capacitor voltage control, and decreased computational burden, is proposed. Compared to the other current control strategies, it has the capability of handling multiple control objectives and possesses a simple structure. Furthermore, it greatly reduces the CMV since the peak CMVs of all the candidate voltage vectors are constrained to be less than one sixth of the dc-link voltage. In addition, an optimal two-stage voltage vector selection mechanism is employed in the proposed method. It helps to significantly reduce the computational complexity. Simulation and experimental results are provided to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents Space Vector Modulation (SVM) sequences that reduce Common Mode Voltage (CMV) in Dual Three-phase Asymmetrical Induction Motor (DTAIM). At first, two existing SVM techniques such as Reference SVM (RSVM) and CMV1 are studied. Additionally, three new switching sequences are developed as CMV2, CMV3 and DCMV3, which reduce peak magnitude of CMV by 66.8% in comparison with RSVM technique. In SVM techniques, to obtain least CMV, zero vectors are usually replaced by two opposite large Active voltage Vectors (AV) with equal time duration. In such topologies like CMV1, total six AVs are utilized to synthesize the reference vector. The proposed SVM technique CMV2 utilizes only five large AVs to synthesize the reference vector and reduces CMV. Selection of five neighbouring AVs is reflected in reduction of harmonic flux trajectories and stator current ripple in proposed techniques. Additionally, two more switching sequences (CMV3 and DCMV3) are developed related to utilization of specific zero voltage vectors in all sectors (7 and 56) that produce zero CMV. These two switching sequences also provide easy implementation feature during the development of c-code program. In this study, CMV and stator current ripple are considered as performance parameters for different SVM techniques. All SVM techniques are analysed by analytical results, computer simulations, and using prototype test setup of DTAIM fed by Dual Three-phase Voltage Source Inverters (DTVSIs). [ABSTRACT FROM AUTHOR]

Mobile edge computing becomes a promising technology to mitigate the latency of various cloud services. In addition, network function virtualization (NFV) has been shown a great potential in reducing the operational cost of cloud services while enhancing the flexibility of virtual network function deployments, by implementing dedicated hardware network functions as pieces of software in generic servers. Recently, the GPU acceleration has been investigated to speed up flow processing in virtual network functions (VNFs), by leveraging the parallelism of GPUs. VNFs that need accelerations prefer to stay at cloudlets (locations) equipped with GPUs. However, little attention has been paid for the VNF placement that takes into account GPU-affinity in cloudlets of mobile edge clouds. In this paper, we consider the affinity-aware throughput maximization problem in a mobile edge cloud via leveraging the parallelism on GPUs for user requests with VNF requirements. We consider two types of affinities in the VNF placement: The soft-affinity that allows VNFs to be executed by either CPUs or GPUs in cloudlets; and the hard-affinity that only allows VNFs to be placed to the GPUs of a specified set of cloudlets. We formulate two corresponding VNF placement problems in a mobile edge cloud. Specifically, we first propose an exact solution to the soft-affinity throughput maximization problem by formulating an Integer Linear Program (ILP). We then propose an efficient algorithm for the problem, by proposing a randomized algorithm with a provable approximation ratio for the hard-affinity-aware throughput maximization problem and extending the proposed approximation algorithm to the soft-affinity throughput maximization problem. Furthermore, assuming that user requests arrive into the mobile edge cloud one by one without the knowledge of future arrivals, we devise an online algorithm with a good competitive ratio for this dynamic hard-affinity-aware throughput maximization problem. Finally, we evaluate the performance of the proposed algorithms, through simulations and implementations in a real test-bed. Experimental results show that the performance of the proposed algorithms outperform their existing counterparts and achieve higher throughput. [ABSTRACT FROM AUTHOR]

This paper introduces a network topology identification (TI) method based on deep neural networks (DNNs) for online applications. The proposed TI DNN utilizes the set of measurements used for state estimation to predict the actual network topology and offers low computational times along with high accuracy under a wide variety of testing scenarios. The training process of the TI DNN is duly discussed, and several deep learning heuristics that may be useful for similar implementations are provided. Simulations on the IEEE 14-bus and IEEE 39-bus test systems are reported to demonstrate the effectiveness and the small computational cost of the proposed methodology. [ABSTRACT FROM AUTHOR]

Line-switching operations introduce several concerns to microgrid operators since they trigger reliability and power quality issues in addition to increasing the wear and tear cost of switching devices. This paper proposes a novel methodology for achieving seamless line-switching in low-inertia islanded microgrids. The proposed methodology aims at mitigating the detrimental line-switching impacts by minimizing the power flow in the switched lines at the moments of executing the switching operations. The minimization of the power flow is realized by optimizing the droop control parameters of the DGs during the transition from one network topology to another. Besides, during executing a series of line-switching operations, the sequence of switching is also optimized to minimize the total switched power. While optimizing the line-switching execution sequence, the transitional droops are optimized for each line-switching operation within that sequence. A dynamic mixed-integer nonlinear programming problem is formulated to find both the optimized dynamic transitional droops and line-switching sequence simultaneously. Simulation results demonstrate the effectiveness of the proposed seamless line-switching methodology where the switched power can be reduced by more than 80% for a single line-switching operation and 54% considering a series of four switch exchanges in addition to achieving several instances of zero-current switching. As a result, a significant decrease in the peak of voltage transients has been recorded for some cases. [ABSTRACT FROM AUTHOR]

This paper investigates the outage and throughput performance of full-duplex (FD) cooperative relaying (CR) based non-orthogonal multiple access system (NOMA) with energy harvesting (EH) i.e., FD-CR-EH-NOMA system. We consider a network scenario, where the base station (BS) serves two downlink users, with the near user configured as a FD relay to deliver messages to the far user. We derive analytical expressions for the outage probabilities experienced by the users and the system outage probability of FD-CR-EH-NOMA network under time switching relaying (TSR) protocol in the presence/absence of direct link from BS to the far user. Assuming imperfect successive interference cancellation (i-SIC), we derive analytical expressions for (i) optimal power allocation (OPA) factor at the BS and (ii) optimal time switching (OTS) factor at the relay that independently minimizes the system outage probability. Further, we use the alternating optimization technique to determine the jointly optimal power allocation and time switching factors that minimize the system outage probability. Furthermore, we determine the OTS factor that maximizes the asymptotic throughput of the system in the delay-limited transmission mode. With the help of numerical and simulation investigations, we show that the system outage and throughput of the considered network improve significantly under the proposed schemes. [ABSTRACT FROM AUTHOR]

We formulate and study the problem of ON-OFF privacy. ON-OFF privacy algorithms enable a user to continuously switch his privacy between ON and OFF. An obvious example is the incognito mode in internet browsers. But beyond internet browsing, ON-OFF privacy can be a desired feature in most online applications. The challenge is that the statistical correlation over time of a user’s online behavior can lead to leakage of information. We consider the setting in which a user is interested in retrieving the latest message generated by one of $N$ sources. The user’s privacy status can change between ON and OFF over time. When privacy is ON the user wants to hide his request. Moreover, since the user’s requests depend on personal attributes such as age, gender, and political views, they are typically correlated over time. As a consequence, the user cannot simply ignore privacy when privacy is OFF. We model the correlation between user’s requests by an $N$ state Markov chain. The goal is to design query schemes with optimal download rate, that preserve privacy in an ON-OFF privacy setting. In this paper, we present inner and outer bounds on the achievable download rate for $N$ sources. We also devise an efficient algorithm to construct an ON-OFF privacy scheme achieving the inner bound and prove its optimality in the case $N=2$ sources. For $N > 2$ , finding tighter outer bounds and efficient constructions of ON-OFF privacy schemes that would achieve them remains an open question. [ABSTRACT FROM AUTHOR]

The electromagnetic repulsion model of 400 V/630 A/12.5 kA fast vacuum transfer switch (FVTS) is established using finite element method. The speed and characteristics of the contact bounce of the FVTS are taken as constraints, and the objective is to keep the reliable opening of the mechanism with allowable bounce. The deceleration of the fast operating mechanism in the process of opening and closing is realized by applying the reverse electromagnetic repulsion force. Moreover, the simulation results demonstrate that the electromagnetic buffer effect is available, and the allowable bounce opening of the operating mechanism has been obtained. Furthermore, this paper compares the buffering effects of three kinds of conditions, such as no electromagnetic buffering, 110 V electromagnetic buffering and 220 V electromagnetic buffering. It can be found that the electromagnetic buffering is a necessary part of the 400 V FVTS, and the dynamic characteristics are the optimal scheme when the 220 V electromagnetic buffering is applied. Based on the results of simulation, a FVTS experimental prototype is developed to prove the effectiveness of the design scheme. [ABSTRACT FROM AUTHOR]

Microgrids with multiple converters suffer from excessive pressure on the communication network during traditional voltage and frequency regulation control. This paper proposed an event-triggered control strategy based superconducting magnetic energy storage (SMES) scheme to improve AC microgrids stability under successive disconnection of sources or step change of loads. By designing an event-triggered mechanism, each converter in the microgrid sends its own information to SMES in a non-periodic way. Then the control method of bus voltage and frequency regulation using SMES is constructed, which enables SMES to update its control mode. The microgrid model is established in PSCAD/EMTDC, and two cases of extreme conditions are conducted to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

X-ray computed tomography (CT) uses different filter kernels to highlight different structures. Since the raw sinogram data is usually removed after the reconstruction, in case there is additional need for other types of kernel images that were not previously generated, the patient may need to be scanned again. Accordingly, there exists increasing demand for post-hoc image domain conversion from one kernel to another without sacrificing the image quality. In this paper, we propose a novel unsupervised continuous kernel conversion method using cycle-consistent generative adversarial network (cycleGAN) with adaptive instance normalization (AdaIN). Even without paired training data, not only can our network translate the images between two different kernels, but it can also convert images along the interpolation path between the two kernel domains. We also show that the quality of generated images can be further improved if intermediate kernel domain images are available. Experimental results confirm that our method not only enables accurate kernel conversion that is comparable to supervised learning methods, but also generates intermediate kernel images in the unseen domain that are useful for hypopharyngeal cancer diagnosis. [ABSTRACT FROM AUTHOR]

Although the logically-centralized perspective is offered in Software-Defined Networking (SDN), the data plane is still distributed. Update commands sent by the centralized controller are executed asynchronously and independently in each switch. The timed SDN enables synchronous and coordinated update operations as each update command can be triggered by a pre-defined timestamp. Prior work on timed update mainly focuses on producing a congestion-free update sequence, whereas finding a congestion-free timed update sequence may prolong the update time. Even worse, such an update order may not exist. In this paper, we propose Chronus+, a novel timed update system that utilizes the switch buffer to shorten the update time while minimizing the switch buffer during updates. First, we formulate the Minimum Switch Buffer Problem (MSBP) as an integer linear programming and show its hardness. Then, we propose a set of efficient algorithms to solve the problem in polynomial time. Extensive evaluations in Mininet and large-scale simulations show that Chronus+ can reduce the update time by at least 17% and the switch buffer size by at least 27% compared with state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Identifying the location of partial discharges (PDs) and providing clear information on insulation vulnerabilities in power systems can help utility companies to improve their maintenance efficiency. This paper presents a PD monitoring and locating system for medium-voltage switchgears using a set of transient earth voltage (TEV) detectors. A time-of-flight methodology was used to identify the switchgear affected by PD among a row of switchgears. A time sharing access mechanism, which was implemented by multiple high-frequency surface mounting relays integrated into each TEV detector, was applied to automatically identify the site of PD and minimize the number of expensive high-speed acquisition cards. The operation principle and implementation of the modular system were formulated, and the efficiency of the proposed system in identifying the switchgear with PD among three 10 kV metal-clad switchgears was confirmed experimentally. [ABSTRACT FROM AUTHOR]

Medium voltage direct current (MVDC) power systems are in their early phase of development, but the lack of efficient and reliable DC circuit breakers is currently one of the most significant bottlenecks for widespread adoption of MVDC applications. Compared to protection devices in high voltage direct current (HVDC) systems, MVDC circuit breakers are expected to interrupt fault currents with higher rates of rise in more power-dense and more controllable structures. A hybrid approach with a piezoelectrically actuated fast mechanical switch in parallel to a solid-state circuit breaker is expected to meet the above requirements. A prototype of a 15 kV-class piezoelectrically actuated fast mechanical switch is presented in this paper. The prototype demonstrates an actuator opening time of 1 ms, a breakdown voltage of over 20 kV, and a continuous current rating of 500 A. After integrating the fast mechanical switch into a hybrid circuit breaker testbed, the fast mechanical switch was able to open within 1.5 ms and the fault was cleared within 5 ms. Therefore, piezoelectrically actuated fast mechanical switches can enable fast, reliable and controllable protection for various MVDC systems like electric ships, electric aircraft and microgrids that integrate distributed energy resources. [ABSTRACT FROM AUTHOR]

360-degree video streaming shows great potential to revolutionize the streaming market, by providing much better immersive experience than standard video streams. However, its wide adoption is hindered by the surging demand of network bandwidth due to multi-screen video transmission. To reduce the bandwidth cost, one promising approach is to predict a user’s field of view (FoV), and then prefetch video tiles that a user will view a few seconds ahead. The challenge lies in that user behaviors cannot be properly captured with very limited information, especially the viewing time spent on each tile and the FoV switching behavior are hard to predict. In this paper, we propose a novel 360-degree video streaming algorithm called TVG-Streaming to optimize user experiences by learning user view behaviors. Different from previous approaches, our idea is to exploit tile-view graphs (TVGs) generated by real user behaviors and accurately estimate the probability that each tile falls in the FoV. With the tile view probability, we can determine the bitrate of each tile for delivery and buffering with limited bandwidth budget so as to maximize users’ quality of experience (QoE). For evaluation, we conduct extensive experiments using real traces and the results show that our proposed TVG-Streaming algorithm significantly outperforms other algorithms by at least 20% improvement in terms of users’ QoE. [ABSTRACT FROM AUTHOR]

Well-annotated training samples show necessity in achieving high performance of object detection, but collection of massive samples is extremely laborious and costly. Recently, cut-paste based methods show the potential to augment the training samples by cutting the foreground instances and pasting them on some background regions. However, existing cut-paste based methods hardly guarantee the quality of synthetic images due to lack of mechanism to ensure rationality of the pasted instances (e.g., context, geometry and diversity), limiting the effectiveness of data augmentation. To overcome above issues, this paper proposes a novel Constrained Online Cut-Paste (COCP) method, making an attempt to effectively and efficiently augment training data for improving performance of object detection. Specifically, our COCP generates synthetic images by switching instances of same class from various image pairs in each training mini-batch, ensuring context coherence between the cut instances and the pasted backgrounds. Furthermore, two constraints based on geometric consistency and sample diversity are developed to eliminate counterproductive and meaningless switched instances those suffer from significant geometric discrepancy or lack variations, further improving quality of the synthetic images. The experiments are conducted on both MS COCO and PASCAL VOC datasets using various state-of-the-art detectors (e.g., Faster R-CNN, RetinaNet, FCOS and Mask R-CNN). The results show that our proposed COCP can be well generalized to various datasets and detectors with clear performance gains, while performing favorably against its counterparts. [ABSTRACT FROM AUTHOR]

In this paper, we propose a topology-cognizant optimal power flow (OPF) paradigm with additional safety constraints for multi-terminal direct current (MTDC) grids. The resulting formulation is concerned with the optimization of controller set-points, i.e., voltage and power levels at each bus, and the switching status of transmission lines that collectively referred to as grid topology. A pair of additional safety constraints are integrated into the problem formulation to prevent voltage violations caused by power fluctuations in between two controller set-point updates. Searching for a grid topology that offers more efficient operation leads to a mixed-integer nonlinear program (MINLP) which is computationally challenging due to: i) Non-convex power flow equations, (ii) Non-convex converter loss equations, and iii) Binary variables accounting for the operational status of transmission lines. Non-convexities of power flows and converter loss equations are tackled by means of a mixed-integer second-order cone programming (MISOCP) relaxation, while the optimal switching status of transmission lines are determined via a branch-and-bound search. Numerical results for the modified IEEE 14, 30, and 57-bus systems are used to verify the merits of the proposed method. Furthermore, this method is experimentally validated using the CIGRE B4 DC grid benchmark in a real-time hardware-in-the-loop platform. [ABSTRACT FROM AUTHOR]

In this paper, a methodology to solve the optimal reactive power dispatch (ORPD) in electric power systems (EPS), considering discrete controllers, is proposed. Discrete controllers, such as the tap position of on-load tap changing (OLTC) transformers and switchable reactive shunt compensation, are optimized by the proposed method. A semidefinite relaxation (SDR) of the ORPD problem and a branch-and-bound (B&B) algorithm have been fully deployed. A new formulation is presented for the OLTC transformers to obtain a connected structure of the semidefinite programming (SDP) matrices. The customized B&B algorithm deals with the discrete nature of the binary control variables. Moreover, in order to enhance the convexification, valid inequalities called lifted nonlinear cuts (NLC) are implemented in the SDR. Additionally, a chordal decomposition technique is used to improve the computational performance. Finally, the B&B algorithm is used to solve the mixed-integer semidefinite programming problem. Several benchmarks have been used to show the accuracy and scalability of the proposed method, and convergence analysis shows that near-global optimal solutions are generated with small relaxation gaps. [ABSTRACT FROM AUTHOR]

In this paper, the idea of offset spatial modulation (OSM) is integrated with orthogonal frequency division multiplexing (OFDM), toward an efficient design to bridge their advantages. Compared to its conventional counterpart as spatial modulation (SM)-OFDM, the proposed OSM-OFDM scheme aims at providing a simplified implementation structure with less number of radio frequency (RF) chains, by introducing an offset between the RF chain and the index of the activated transmit antenna on each subcarrier. Specifically, three types of offset antenna selection (OAS) methods are developed to meet different scene requirements for different number of available RF chains. Furthermore, through theoretical analysis, we quantify the bit error rate upper bounds of OSM-OFDM with different types of OAS methods. Finally, extensive computer simulations demonstrate that OSM-OFDM provides a flexible tradeoff among implementation cost, computation complexity and error performance. [ABSTRACT FROM AUTHOR]

The implementation of finite-control-set model predictive control (FCS-MPC) in voltage source inverters (VSIs) can make the system suffer from poor current harmonics performance, which may complicate the design of the required AC filter. To overcome this shortcoming, a carrier-based modulated model predictive control (CB-MMPC) strategy is proposed in this paper. This method enables the utilization of existing PWM modulation techniques with FCS-MPC, where a modulation waveform with zero-sequence signal injection is generated and compared to a triangular carrier wave, while optimizing the selection of the switching states. As it is shown, the studied CB-MMPC strategy not only considerably improves the current total harmonic distortion (THD) but also attains the performance of fast current dynamic response and robustness as the traditional FCS-MPC. Herein, the detailed implementation of the CB-MMPC control strategy is given, while considering its application to the current feedback control loop of a three-phase three-wire two-level VSI modulated at constant switching frequency. Finally, PLECS circuit simulation and a 3-kW VSI prototype are used to verify the superiority and the effectiveness of the presented CB-MMPC strategy. This is also benchmarked to the FCS-MPC and dead-beat based controllers. [ABSTRACT FROM AUTHOR]

Conventionally, the converter of switched reluctance motor (SRM) is fed by the uncontrollable diode bridge rectifier (DBR), which leads to a low grid-side power factor (PF) and high current total harmonic distortion (THD). In this paper, an alternative solution for the grid-connected high-speed SRM drive system with improved PF is proposed. In the proposed drive system, the three-level active front end (AFE) is connected in cascade with the midpoint converter for SRM operation. A centralized strategy, which controls the AFE and SRM together, is proposed to govern the motor speed and grid-side PF by regulating the real power and reactive power of the system, respectively. Specifically, the real power, reactive power, and the voltage balancing of split capacitors are controlled by the model predictive directed power control (MP-DPC) algorithm, which significantly reduces the control complexity and guarantees the fast dynamic response. Consequently, satisfying speed regulation, high PF, low current THD, and bi-directional power-transfer capability are achieved. An idea-proofed testbench is constructed in laboratory, and the applicability of the proposed drive system is verified by a series of experimental results. [ABSTRACT FROM AUTHOR]

The belt-driven starter/generator (BSG), as a cost-effective solution, has been widely employed in hybrid electric vehicles (HEVs) to improve the stability and reduce the fuel consumption of the vehicles. It can provide more than 10% reduction in CO2. Electrical machine is the heart of the BSG system, which is functioned both as motor and generator. In order to optimize both aspects of motor and generator simultaneously, this paper presents a new multimode optimization method for the switched reluctance machines. First, the general multimode concept and optimization method are presented. The switched reluctance motor and the switched reluctance generator are the two operation modes. The optimization models are established based on motor and generator functions. Sensitivity analysis, surrogate models and genetic algorithms are employed to improve the efficiency of the multimode optimization. Then, a design example of a segmented-rotor switched reluctance machine (SSRM) is investigated. Seven design variables and four driving modes are considered in the multiobjective optimization model. The Kriging model is employed to approximate the finite element model (FEM) in the optimization. Finally, the optimization results are depicted, and an optimal solution is selected. The comparison between the initial and optimal designs shows that the proposed method can improve the foremost performance of the SSRM under all driving modes. [ABSTRACT FROM AUTHOR]

Multicasting is becoming more and more important in the Internet of Things (IoT) and wearable applications (e.g., high definition video streaming, virtual reality gaming, public safety, among others) that require high bandwidth efficiency and low energy consumption. In this regard, millimeter wave (mmWave) communications can play a crucial role to efficiently disseminate large volumes of data as well as to enhance the throughput gain in fifth-generation (5G) and beyond networks. There are, however, challenges to face in view of providing multicast services with high data rates under the conditions of short propagation range caused by high path loss at mmWave frequencies. Indeed, the strong directionality required at extremely high frequency bands excludes the possibility of serving all multicast users via a single transmission. Therefore, multicasting in directional systems consists of a sequence of beamformed transmissions to serve all multicast group members, subgroup by subgroup. This paper focuses on multicast data transmission optimization in terms of throughput and, hence, of the energy efficiency of resource-constrained devices such as wearables, running their resource-hungry applications. In particular, we provide a means to perform the beam switching and propose a radio resource management (RRM) policy that can determine the number and width of the beams required to deliver the multicast content to all interested users. Achieved simulation results show that the proposed RRM policy significantly improves network throughput with respect to benchmark approaches. It also achieves a high gain in energy efficiency over unicast and multicast with fixed predefined beams. [ABSTRACT FROM AUTHOR]

Network topology identification (TI) is an essential function for distributed energy resources management systems (DERMS) to organize and operate widespread distributed energy resources (DERs). In this paper, discriminant analysis (DA) is deployed to develop a network TI function that relies only on the measurements available to DERMS. The propounded method is able to identify the network switching configuration, as well as the status of protective devices. Following, to improve the TI resiliency against the interruption of communication channels, a quadratic programming optimization approach is proposed to recover the missing signals. By deploying the propounded data recovery approach and Bayes’ theorem together, a benchmark is developed afterward to identify anomalous measurements. This benchmark can make the TI function resilient against cyber-attacks. Having a low computational burden, this approach is fast-track and can be applied in real-time applications. Sensitivity analysis is performed to assess the contribution of different measurements and the impact of the system load type and loading level on the performance of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper presents and evaluates a discrete-event control-based Supervisory Controller (SC) for a grid-connected, battery-enabled, DC Fast-Charging (DCFC) station for Electric Vehicles’ (EVs). The SC enhances operational resiliency of the DCFC station and its host grid by decoupling the dynamics and limiting the steady-state power between the station and its host grid. The charging station includes multiple DCFC units, a Battery Energy Storage System (BESS), a solar-PV unit, and a grid-interface Voltage-Sourced Converter (VSC). The SC (i) limits the station-imported power from the grid based on the grid-imposed requirements, (ii) dynamically dispatches power flow among the grid, PV unit, DCFC units, and BESS to meet charging needs of EVs and when applicable charges BESS or exports power to the grid, (iii) protects the BESS by enforcing its state of charge upper and lower limits and the maximum charge/discharge rates, and (iv) enables the VSC to provide grid ancillary services, if required. Simulation results in PLECS software platform are given to assess the dynamic performance of the proposed SC in response to various discrete events/transitions. The SC algorithm is implemented on a Programmable Logic Controller (PLC) and verified based on real-time Hardware-In-the-Loop approach using an OPAL-RT platform. [ABSTRACT FROM AUTHOR]

Operational performance in the low-voltage distribution network (LVDN) can be undermined by its inherent unbalances, which may become worse as the penetration of rooftop solar continuously increases. To address this issue, load balancing via phase-reconfiguration devices (PRDs), which can change phase positions of residential customers as required, provides a cost-efficient option. However, most reported approaches to control PRDs require that demands of all residential customers are available, which are not viable for many LVDNs without smart meters or advanced metering infrastructure (AMI) installed. To bridging the gap in this field, this paper proposes a novel method to control PRDs purely based on measurable data from PRDs, and its controller. Based on limited information, sensitivity analysis in the network with PRDs is studied, followed by the optimization model that comprehensively considers operational requirements in the network. Moreover, slack variables are introduced to the model, and penalized in the objective function to assure either a strategy that is secure or with minimized violations can always be provided. The model is a challenging mixed-integer non-convex programming (MINCP) problem, which is reformulated as an efficient solvable mixed-integer second-order cone programming (MISOCP) based on exact reformulations or accurate linear approximations. Simulations based on two modified IEEE systems, and a real system in Australia demonstrate that an efficient strategy can be provided to mitigate unbalances in the network. [ABSTRACT FROM AUTHOR]

For Electro-Magnetic-Transient (EMT) simulations of power networks with switches, techniques such as linear interpolation and Critical Damping Adjustment (CDA) are widely used for improving numerical robustness. This paper analyzes the numerical stability of simulations with these techniques. Firstly, it is mathematically shown that the interpolation or CDA step is equivalent to the introduction of additional switching states. Subsequently, Common Quadratic Lyapunov Function (CQLF) theory is used to investigate the numerical stability of the whole simulation considering these new switching states. It is proved that the widely used strategies like linear interpolation and CDA always result a stable simulation if the original switched system is strictly passive in all switching states. Finally, it is shown that the developed approach can be used to determine the stability of other practical interpolation methods. Examples are provided to verify the proposed technique. [ABSTRACT FROM AUTHOR]

Natural calamities always have been a serious threat to energy systems. In this regard, this paper constitutes a stochastic mixed integer linear programming (SMILP) model to enhance the resilience of power distribution systems to deal with disastrous events. In particular, the proposed model is developed to enhance both survivability and restoration capability of distribution systems. In this regard, to increase the preparedness of the power distribution system, the system operator reconfigures the network by utilizing remote-control switches (RCSs), manual switches (MSs), and distributed generations (DGs) before the natural calamity hits. The proposed model contemplates the traveling time of crew teams to the MS sites in the transportation system in order to achieve the best switching sequence. In addition, it pre-positions the crews and mobile emergency generators (MEGs) in staging locations to hasten the likely post-disturbance operations. To do so, likely post-event operations are included in the model using the scenario generation technique. To validate the performance of the developed model a distribution system is employed. The results of simulations confirm the effectiveness of the proposed approach in declining the interruption of electric energy for customers. [ABSTRACT FROM AUTHOR]

In a line-commutated converter based high-voltage direct-current (LCC-HVDC) system, the inverter control system usually includes constant extinction angle (CEA) controller, constant current (CC) controller, current error controller (CEC), and voltage-dependent current order limiter (VDCOL). However, the interaction influence of multiple controllers may cause repetitive commutation failure (CF). For this purpose, this paper deeply investigates the mechanism and the influencing factors of repetitive CF caused by controller interaction. It is found that the lower limit value of CEA controller can affect the control switching process and thus the probability of repetitive CF. Besides, the minimum gamma measurement (MGM) unit prevents the system from acquiring the real extinction angle in time, which results in the DC current fluctuation during the recovery process. Moreover, the probability of control-induced repetitive CF is much higher when the HVDC inverter is connected to a weak AC system or the AC fault is not serious but not cleared in time. Based on the above analyses, an improved control method is proposed for recovery performance improvement, which is mainly realized by modifying the lower and upper limits of the CEA controller during recovery. Finally, the simulation and experimental results verify the theoretical analyses and the proposed control method. [ABSTRACT FROM AUTHOR]

With increasing penetration of solar PV, some distribution feeders are experiencing highly variable net-load flows and even reverse flows. To optimize distribution systems under such conditions, the scheduling of mechanical devices, such as OLTCs and capacitor banks, needs to take into account forecasted solar PV and actual grid conditions. However, these legacy switching assets are operated on a daily or hourly timescale, due to the wear and tear associated with mechanical switching, which makes them unsuitable for real-time control. Therefore, there is a natural timescale-separation between these slower mechanical assets and the responsive nature of inverter-based resources. In this paper, we present a network admissible convex formulation for holistically scheduling controllable grid assets to position voltage optimally against solar PV. An optimal hourly schedule is presented that utilizes mechanical resources to position the predicted voltages close to nominal values, while minimizing the use of inverter-based resources (i.e., DERs), making them available for control at a faster time-scale (after the uncertainty reveals itself). A convex, inner approximation of the OPF problem is adapted to a mixed-integer linear program that minimizes voltage deviations from nominal (i.e., maximizes voltage margins). The resulting OPF solution respects all the network constraints and is, hence, robust against modeling simplifications.Simulation based analysis on IEEE distribution feeders validates the approach. [ABSTRACT FROM AUTHOR]