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This study was designed to examine methanol as a new aging marker of insulating paper. An analytical GC-MS method coupled to headspace injection was developed, followed by a validation. To further validate the possible applicability of methanol for different transformer conditions some laboratory studies were performed such as a stability and an aging test. Oil samples of power transformers of several Belgian nuclear and coal-fired power plants have been analyzed since mid 2009 and are followed-up periodically to correlate the results with the analysis of the furanic compounds which have been used since mid 1980s as oil soluble degradation products of the insulating winding paper. It seemed that while no 2FAL was present some considerable amount of MeOH was detected which revealed some paper degradation. A second real case study was started to further correlate MeOH and 2FAL results. From these laboratory and real case studies it seemed that MeOH is a very promising marker for paper degradation in power transformers. [ABSTRACT FROM AUTHOR]

Citing data and software is a means to give scholarly credit and to facilitate access to research objects. Citation principles encourage authors to provide full descriptions of objects, with stable links, in their papers. As Jupyter notebooks (JNs) aggregate data, software, and other objects, they may facilitate or hinder citation, credit, and access to data and software. We report on a study of references to JNs in astronomy over a five-year period (2014–2018). References increased rapidly, but fewer than half of the references led to JNs that could be located and opened. JNs appear better suited to supporting the research process than to providing access to research objects. We recommend that authors cite individual data and software objects and that they stabilize any notebooks cited in publications. Publishers should increase the number of citations allowed in papers and employ descriptive metadata-rich citation styles that facilitate credit and discovery. [ABSTRACT FROM AUTHOR]

In this paper, a new adaptive fractional frequency control method for microgrids(MG) and low inertia networks is presented. The newly proposed grid frequency control is based on the droop and inertia controller for doubly-fed induction generator (DFIG) wind turbine (WT) using a data-driven algorithm. Also, in this paper, to ensure the grid frequency stability, the stability region boundary has been calculated using the parameter space method for above and below synchronous speeds. In the first step in the proposed method, a data-driven control (DDC) is used to update the frequency control coefficients. In the second step, in order to deployment more frequency data and to use both frequency error concavity and slope, the utilization of fractional gradient descent (FGD) and fractional inertia control is proposed. In the third step to maintain frequency stability, the updated frequency controller coefficients are compared with the stability region boundary. If the updated frequency controller coefficients are in the authorized band, they are applied. To test the proposed idea is a simulated real grid in Ontario, Canada. The simulation results indicate the proper operation of the control system in transient and steady-state and under different conditions. [ABSTRACT FROM AUTHOR]

This paper proposes an approach to determine the participation of algebraic variables in power system modes. The approach is based on a new interpretation of the classical participation factors, as well as on the definition of adequate output variables of the system's state-space representation. The paper considers both the linear and generalized eigenvalue problems for the calculation of the participation factors and presents a theorem to cope with eigenvalue multiplicities. An illustrative example on the two-area system, as well as a study on a 1479-bus dynamic model of the all-Irish transmission system are carried out to support the theory and illustrate the features of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive control for a class of uncertain nonlinear systems under denial-of-service (DoS) attacks. We analyze the closed-loop system stability under DoS attacks in terms of attack duration, attack frequency and resting time duration respectively. Three scenarios of DoS attacks against the system stability are considered. Firstly, it is shown that if the duration of each attack is less than a given constant, asymptotical convergence of system output is still preserved. Secondly, if the bounds on the frequency and duration of attacks with respect to overall intervals meet certain conditions, the proposed event-triggered control scheme guarantees that all the closed-loop signals are globally bounded and the stabilization error converges to a ball with a radius arbitrarily small. Thirdly, if resting time duration meets certain conditions after an arbitrarily long attack, closed-loop boundedness is still preserved. Simulation results are shown to illustrate the effectiveness of the proposed control schemes. [ABSTRACT FROM AUTHOR]

The modern power grid features the high penetration of power converters, which widely employ a phase-locked loop (PLL) for grid synchronization. However, it has been pointed out that PLL can give rise to small-signal instabilities under weak grid conditions. This problem can be potentially resolved by operating the converters in grid-forming mode, namely, without using a PLL. Nonetheless, it has not been theoretically revealed how the placement of grid-forming converters enhances the small-signal stability of power systems integrated with large-scale PLL-based converters. This paper aims at filling this gap. Based on matrix perturbation theory, we explicitly demonstrate that the placement of grid-forming converters is equivalent to increasing the power grid strength and thus improving the small-signal stability of PLL-based converters. Furthermore, we investigate the optimal locations to place grid-forming converters by increasing the smallest eigenvalue of the weighted and Kron-reduced Laplacian matrix of the power network. The analysis in this paper is validated through high-fidelity simulation studies on a modified two-area test system and a modified 39-bus test system. This paper potentially lays the foundation for understanding the interaction between PLL-based (i.e., grid-following) converters and grid-forming converters, and coordinating their placements in future converter-dominated power systems. [ABSTRACT FROM AUTHOR]

This paper aims to resolve a clear and unrealistic limitation found in recent works that have proposed solutions to the massive demand for the autonomous electric mobility-on-demand (AEMoD) services. Namely, this paper will focus on the matched charge-to-trip only service by enabling sub-class service; i.e., allowing vehicles to serve customer classes with trips needing less charge. The paper proposes a multi-class management system with a new queuing model for one city zone, and then derives the stability conditions of the system. Proportions of vehicles from each class that will immediately serve customers with sub-class service or full/partial charge are modeled, and the maximum expected response time of the system is then minimized by optimizing these vehicle service decisions. The advantages of the new model are then compared with previously proposed schemes and non-optimized models through simulations. [ABSTRACT FROM AUTHOR]

This paper examines the problem of designing integrated systems of photovoltaic (PV) arrays and battery cells in a manner that achieves self-balancing by design. This paper focuses on two topologies for integrating PV and battery cells, both of which connect PV generation to each battery cell directly, either with or without dc–dc conversion. This paper proves, using Lyapunov stability methods, that both the topologies are globally, asymptotically self-balancing. This means that initial differences among battery cells in either the state of charge or other internal state variables are guaranteed to diminish asymptotically with time. This self-balancing behavior reduces the amount and hence the cost of the power electronics needed for energy storage integration into PV farms significantly compared to conventional integration topologies—an argument substantiated using a financial assessment in this paper. This paper extends previous work by the authors on self-balancing PV energy storage systems in four significant ways. First, the proof of self-balancing is provided using equivalent-circuit battery models of arbitrary order, as opposed to first-order models. Second, this proof is provided for multiple integration topologies, instead of just one. Third, we demonstrate this self-balancing behavior experimentally, using a hardware-in-the-loop setup, for the first time. Finally, we perform a cost benefit analysis of our hybrid topologies in comparison to a benchmark system in order to quantify the integration cost reduction due to self-balancing. [ABSTRACT FROM AUTHOR]

This paper first points out and carefully analyzes the complementary regulation characteristics (CRC) of wind power generators (WGs) and demand response resources (DRRs), which indicate the fact that their regulation capacities and costs of upward and downward regulation are significantly different and complementary. Based on the CRC of WGs and DRRs, this paper proposes a coordinated control to achieve a more robust and cost-efficient primary frequency regulation (PFR). In the proposed coordinated control, the droop gains of WGs and DRRs for upward and downward regulation are designed in a coordinated way so that the resources with larger capacities and lower costs could provide more frequency support. Meanwhile, the stability and robustness conditions of their coordinated droop gains are constructed by small-signal analysis method and the potential instability risks arising from unreasonable coordinated droop gains and time delays are addressed. An optimal $H_{\infty }$ control method and an updated mechanism are supplemented to obtain the optimal droop gains under the proposed coordinated structure for ensuring optimal system robustness under different CRCs. The robust performances and costs of the proposed coordinated control are evaluated on the IEEE 39-bus test system and its advantages are verified. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic event data-based stability risk assessment method for power grids with high penetrations of inverter-based resources (IBRs). This method relies on obtaining the IBRs’ DQ admittance through dynamic event data and computing the system’s eigenvalues based on the admittance models. Two critical technologies are employed in this research, including time-domain and frequency-domain data fitting and $dq$ -frame voltage and current signal derivation. The first technology is key to obtaining the $s$ -domain expressions from the transient response data, and the $s$ -domain DQ admittance model from the frequency-domain measurements. The second technology is key to obtaining the $dq$ -frame voltage and current signals from either the three-phase instantaneous measurements or the phasor measurement unit (PMU) data. The method is illustrated using data generated from a Type-4 wind power plant modeled in PSCAD. This paper demonstrates the technical feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the existence and stability of equilibrium of dc micro-grids under the master-slave control (where some distributed generations (DGs) are under droop control with dual-loop (Droop-DGs) and some DGs are under MPPT control (MPPT-DGs)). Firstly, the power-flow equation of the dc micro-grids under master-slave control with CPLs is obtained. Then, we transform the solvability of the power-flow equation into the existence of a fixed point for a contraction mapping. Based on Banach's fixed point theorem, a sufficient condition to guarantee the existence of the power-flow solution in dc micro-grids is derived. The condition derived in this paper is not only useful for master-slave control but also for droop control. Besides, to calculate the power-flow solution, an iterative algorithm with exponential convergence rate is proposed. Secondly, we use a singular perturbation model to predict the qualitative behavior of the system near the equilibrium point. By analyzing eigenvalues of the boundary layer system and reduced-order system Jacobian matrix, the robust stable analytic conditions of the system are obtained. The effect of the sampling delay on the system stability is analyzed, the robust stability condition is obtained by using linear matrix inequality. The simulation results verify the correctness of the proposed conditions. The obtained conditions provide a reference for establishing a reliable dc micro-grid. [ABSTRACT FROM AUTHOR]

This paper presents an elegant method for determining the simplest model of a power system electrical/mechanical load that will suffice for dynamic frequency power system studies and closed-loop simulation work. The strategy behind this technique is to supply the simplest load model possible that gives sufficiently accurate results for the goals of each unique modeling effort. This paper identifies the frequency characteristics of several different load types. It also identifies the level of load model detail required for testing typical power management systems, contingency-based load-shedding systems, frequency-based load-shedding systems, governor control systems, island/grid/unit autosynchronization systems, and exciter control systems. This paper describes how to lump loads without loss of fidelity, when an induction motor needs to be modeled as a single-cage or double-cage motor model, what sort of mechanical load model is appropriate, when we can assume zero inertia for a direct-on-line type of load, and how to verify the turbine/generator inertia, and load inertia from field tests. This paper concludes with a simple reference that engineers can use to specify the level of detail required when modeling industrial power system loads. [ABSTRACT FROM PUBLISHER]

In the system and control community, the sliding mode control technology has been known as a tool which is able to handle system uncertainties and external disturbances. Simplicity in implementation and good stability performance are the other interesting features of the sliding modes. However, traditional sliding mode controllers exhibit two weaknesses, as follows: 1) generally, they have asymptotic stability in sliding mode dynamics which results in a slow speed system and 2) the so-called chattering phenomenon exists, which produces undesirable high frequency oscillations in the control signal. In this paper, the former problem is solved using a twofold terminal sliding manifold displaying desired transient and steady state behavior. The latter issue is responded to by a twofold sliding mode technology which leads to a continuous sliding control rule instead of a discontinuous switching control. The effects of uncertain terms as well as external perturbations with unknown bounds are fully compensated using updated parameters. The values of the updated parameters approach fixed values as the system trajectories converge to the equilibrium states. The analytical results of this paper are theoretically proved using the Lyapunov technique and the finite-time control strategy. Comparative computer simulations on a robotic manipulator confirm the fast convergence attribute and robust performance of the introduced adaptive robust nonsingular terminal sliding control algorithm. [ABSTRACT FROM AUTHOR]

This paper considers a stochastic customer order scheduling problem to maximize throughputs. Customer orders dynamically arrive at a server station that consists of a set of heterogeneous servers. Each incoming order contains multiple product types with random workloads. These workloads will be processed by the servers under two commonly applied production schemes named workload assignment scheme and server assignment scheme. The objective is to determine the optimal assignments that maximize the long-term stable throughputs. The optimization problems under both production schemes are formulated as corresponding mathematical programs whose adequacy is validated through fluid model analysis. It is further proved that the two programs share the same optimal objective value and their corresponding optimal assignments can be transformed into each other. Based on these results, the equivalency of the two production schemes is established with regard to processing time allocation. Optimal assignments of several important special cases are also explored. The numerical experiment shows that the maximum throughputs can be achieved through the proposed mathematical programs, and demonstrates the equivalency relationship between the two assignment schemes. [ABSTRACT FROM AUTHOR]

Voltage source inverters (VSIs) with vector control based on phase-locked loop (PLL) suffer instability when connecting to a very weak AC grid (short circuit ratio (SCR) $ < $ 1.3). The conventional inductive grid impedance compensation for the PLL by virtually reducing the grid impedance can stabilize this connection. However, the analysis in this paper indicates that its stabilization effectiveness is sensitive to grid impedance variance and, indeed, overcompensation causes the PLL instability. Therefore, in this paper, an improved grid impedance compensation for the PLL is proposed to achieve the same stabilization for very-weak-grid connection and possess a good tolerance of grid impedance variance and overcompensation. A comprehensive small-signal model of the VSI using the proposed PLL’s grid impedance compensation is derived for stability analysis and parameter design. The time-domain simulation for this VSI is built to validate the stability analysis. Comparison studies for both proposed and conventional PLL’s grid impedance compensation are conducted including the stability effectiveness, VSI performance and grid impedance variance. [ABSTRACT FROM AUTHOR]

Sanding is a common yet important task in the manufacturing of many wooden objects (e.g. furniture, decoration box), where the coated layer attached on objects is removed after the interaction with sanding belts. Existing sanding operation is heavily dependent on manual works, which is highly labor-intensive and with the low consistency of quality, and the issues of safety and health also arise after continuous working in the noisy and dusty environment. To deal with the aforementioned, this paper presents the development of a new autonomous sanding robot. The autonomous capability of the developed robot is reflected in the whole procedure of sanding. In particular, the CAD model of the target object is automatically constructed with the structured-light technology, and the sanding behavior on the target surface is self-regulated under the desired impedance model. Such feature makes the robot capable of working towards uncertain objects with minimum human involvement. The proposed impedance controller has the model-free advantage, by using the adaptive neural networks (NNs) to compensate the uncertain dynamics and the unknown disturbances online. The stability of the closed-loop system is rigorously proved with Lyapunov methods, and experimental results on different objects are presented to validate the performance of the developed robot. The implementation of the developed robot can systematically address the problems associated with manual works. Note to Practitioners—The current working environment of sanding is not healthy or safe to humans, due to the nature of noise, dust, high-speed sanding belt. By controlling the robot to autonomously perform sanding tasks can keep humans away from such environment and hence systematically address the issues of health and safety. This paper presents a new impedance control method for sanding robot. In impedance control, the control goal is specified as a dynamic relationship between the contact position and the interaction force. In this paper, the contact position is determined by using the 3D vision sensor, while the interaction force is regulated by referring to the human experience. In addition, the influence caused by unmodeled factors (e.g. unknown dynamics of the sanded object) is also dealt with by using the techniques of NNs. Such setting can effectively guarantee the sanding quality and also avoid the physical damage to the sanded object. Therefore, it lays the foundation for the autonomous robotic sanding. [ABSTRACT FROM AUTHOR]

A cross-layer based asymmetric resource allocation strategy for multi-destination relay systems in cellular downlink is proposed in this paper. Existing cross-layer schemes on relay networks are based on symmetric resource allocation (RA) where the transmit duration is assumed to be symmetric between base station to relay station (RS) and RS to mobile station links. This may not be realistic and hence our proposed model considers an asymmetric RA (ARA) in which the transmit durations are asymmetric. Very little work has been done in asymmetric resource allocation and many have failed to consider the queue stability and quality of service (QoS) requirements. Packet length ratio is also ignored in many of these works. In this paper, maximum delay threshold, minimum data rate requirement and zero overflow are considered as QoS requirements. This paper evolves an optimal cross-layer based ARA taking into account the above-mentioned factors. Simulation results are also verified in a cellular testbed which shows that the proposed ARA serves the edge users satisfactorily. Cellular parameters, such as blocking ratio, operating expenditure, electromagnetic pollution index, and QoS assurance, are evaluated and compared. [ABSTRACT FROM PUBLISHER]

This paper investigates systemwide short-term voltage stability concerns of power systems due to the multiple parametric uncertainties in the dynamic load model. The impact of regional load model uncertainty can be widespread and may mislead the whole system analysis and subsequent measures, if not properly addressed. This research discloses that the systemwide impact is related to the voltage weak areas through voltage stability modal analysis, and suggests that the impact of uncertain parameters needs to be assessed from a systems perspective, which has rarely been done in the existing practices. We thus present a three-step methodology for evaluating the systemwide uncertainty impacts: Firstly, it screens possible trajectories of all buses. The second step verifies whether the screened trajectories comply with the defined criteria, and determines the necessity of the final step. The final detailed analysis is conducted for those selected scenarios. Comprehensive studies for both the IEEE test and real Korea power systems consistently confirm the observations and demonstrate the efficacy and validity of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes a new battery management system (BMS) for a series string of battery cells. The proposed control structure is based on the duality of the adaptive droop control theory used in dc micro-grid connected sources. An adaptive virtual admittance is used in this paper similar to the virtual resistance control structure used with dc micro-grid connected sources. The virtual admittance value is adjusted according to the associated state of charge for every connected battery cell. The presented BMS control structure yields higher reliability compared to the conventional ones due to its decentralization features and its communication-less ability. Thus, balanced power-sharing is realized among the connected battery cells during charging/discharging conditions. The stability of the proposed control is analyzed using the small signal model. The proposed BMS control structure is validated using simulation results and an experimental prototype for three connected battery cells. [ABSTRACT FROM AUTHOR]

The approach of dynamical system (DS) is promising for modeling robot motion, and provides a flexible means of realizing robot learning and control. Accuracy, stability, and learning speed are the three main factors to be considered when learning robot movements from human demonstrations with DS. Some approaches yield stable dynamical systems, but these may result in a poor reproduction performance, while some approaches yield good reproduction performance but are quite complex and time-consuming. In this paper, we address the accuracy-stability-speed issues simultaneously. We present a learning method named the fast and stable modeling for dynamical systems, which is based on the extreme learning machine to efficiently and accurately learn the parameters of the DS as well as to ensure the asymptotic stability at the target. We confirm the proposed approach by performing both 2-D tasks of learning handwriting motions and a set of robot experiments. [ABSTRACT FROM AUTHOR]

In this paper, system properties of a physics-based model of a supercapacitor are computed using a local Lyapunov analysis and the solution of linear matrix inequalities. By considering the model as a Lurie system, bounds are computed for the resistance, capacitance, stored and dissipated energies for a charging profile, model stability, maximum reachable set with an input current impulse and the maximum voltage such that the potential difference across the double layer never exceeds the electrolyte overpotential. The bounds computed in this paper will aid the designers of supercapacitors, as the effect on the system properties caused by changes to the physical parameters can now be estimated. The theoretical results predicted by the analysis are compared against experimental data. [ABSTRACT FROM AUTHOR]

Consider observing a collection of discrete events within a network that reflect how network nodes influence one another. Such data are common in spike trains recorded from biological neural networks, interactions within a social network, and a variety of other settings. Data of this form may be modeled as self-exciting point processes, in which the likelihood of future events depends on the past events. This paper addresses the problem of estimating self-excitation parameters and inferring the underlying functional network structure from self-exciting point process data. Past work in this area was limited by strong assumptions which are addressed by the novel approach here. Specifically, in this paper we 1) incorporate saturation in a point process model which both ensures stability and models non-linear thresholding effects; 2) impose general low-dimensional structural assumptions that include sparsity, group sparsity, and low-rankness that allows bounds to be developed in the high-dimensional setting; and 3) incorporate long-range memory effects through moving average and higher-order auto-regressive components. Using our general framework, we provide a number of novel theoretical guarantees for high-dimensional self-exciting point processes that reflect the role played by the underlying network structure and long-term memory. We also provide simulations and real data examples to support our methodology and main results. [ABSTRACT FROM AUTHOR]

This paper is concerned with the event-based security control problems for a set of discrete-time stochastic systems suffered from randomly occurred attacks, especially the denial-of-service attacks and the deception attacks. An attack model with compensation is established to describe combinations of attacks to the networked control systems. An event-triggered mechanism is employed to debase the communication load by transmitting measurement signals when a definite triggering condition is satisfied. A definition of security probability is proposed to describe the transient state of controller systems. The aim of this paper is to design a dynamic output feedback controller, thereupon the closed-loop system achieves the described security in probability. Some novel sufficient conditions are proposed to guarantee the input-to-state stability of the system in probability, and the controller gains are designed by solving a set of matrix inequalities. The upper bound of the quadratic cost function is also derived. Finally, simulation examples are applied to illustrate the effectiveness of the proposed design scheme. [ABSTRACT FROM AUTHOR]

The paper introduces the concept of complex frequency. The imaginary part of the complex frequency is the variation with respect of a synchronous reference of the local bus frequency as commonly defined in power system studies. The real part is defined based on the variation of the voltage magnitude. The latter term is crucial for the correct interpretation and analysis of the variation of the frequency at each bus of the network. The paper also develops a set of differential equations that describe the link between complex powers and complex frequencies at network buses in transient conditions. No simplifications are assumed except for the usual approximations of the models utilized for the transient stability analysis of power systems. A variety of analytical and numerical examples show the applications and potentials of the proposed concept. [ABSTRACT FROM AUTHOR]

The application of inter-vehicle wireless communication offers significant advantages in terms of improving traffic efficiency and safety while also suffering from unreliable communication links. This paper deals with the problem of event-triggered vehicular platoon control with communication time delay and package dropout, aiming to achieve a suitable trade-off between communication utilization and vehicle following performance. A disturbance based platoon model with communication time delay, package dropout and event-triggered scheme is established. Subsequently, the criterion for co-designing the event-trigger parameters and CACC controller parameters is derived by adopting the parameter space approach with the requirements to ensure individual vehicle internal stability, following accuracy and platoon string stability. To achieve a superior trade-off between communication resource utilization and following performance under unreliable communication condition, the adaptive event-triggered threshold is designed for the varying failure probability. The effectiveness of the proposed adaptive CACC strategy is verified using numerical simulations of a six-vehicle platoon during the FTP 72 drive cycle. The comparison results of three different scenarios show that the adaptive event-triggered scheme guarantees the following performance even when failure probability is 0.4. [ABSTRACT FROM AUTHOR]

Edge audio devices can reduce data bandwidth requirements by pre-processing input speech on the device before transmission to the cloud. As edge devices are required to ensure always-on operation, their stringent power constraints pose several design challenges and force IC designers to look for solutions that use low standby power. One promising bio-inspired approach is to combine the continuous-time analog filter channels with a small memory footprint deep neural network that is trained on edge tasks such as keyword spotting, thereby allowing all blocks to be embedded in an IC. This paper reviews the historical background of the continuous-time analog filter circuits that have been used as feature extractors for current edge audio devices. Starting from the interpretation of a basic biquad filter as a two-integrator-loop topology, we introduce the progression in the design of secondorder low-pass and band-pass filters ranging from OTA-based to source-follower-based architectures. We also derive and analyze the small-signal transfer function and discuss their usage in edge audio applications. [ABSTRACT FROM AUTHOR]

Understanding the feasible power flow region is of central importance to power system analysis. In this paper, we propose a geometric view of the power system loadability problem. By using rectangular coordinates for complex voltages, we provide an integrated geometric understanding of active and reactive power flow equations on loadability boundaries. Based on such an understanding, we develop a linear programming framework to 1) verify if an operating point is on the loadability boundary, 2) compute the margin of an operating point to the loadability boundary, and 3) calculate a loadability boundary point of any direction. The proposed method is computationally more efficient than existing methods since it does not require solving nonlinear optimization problems or calculating the eigenvalues of the power flow Jacobian. Standard IEEE test cases demonstrate the capability of the new method compared to the current state-of-the-art methods. Understanding the feasible power flow region is of central importance to power system analysis. This paper proposes a geometric view of the power system loadability problem. By using rectangular coordinates for complex voltages, this paper provides an integrated geometric understanding of active and reactive power flow equations on loadability boundaries. Based on such an understanding, this paper develops a linear programming framework to 1) verify if an operating point is on the loadability boundary, 2) compute the margin of an operating point to the loadability boundary, and 3) calculate a loadability boundary point of any direction. The proposed method is computationally more efficient than existing methods since it does not require solving nonlinear optimization problems or calculating the eigenvalues of the power flow Jacobian. Standard IEEE test cases demonstrate the capability of the new method compared to the current state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper presents the design of a power system stabilizer (PSS) for stability improvement of a droop-controlled inverter-based microgrid systems. For faster power sharing, high droop gains are required, but increasing the droop gains degrades the system stability. Hence, there is a tradeoff between the faster load sharing and system stability. An answer to the given problem is presented in this paper by developing a PSS for inverter-based microgrid. The proposed stabilizer provides sufficient damping to the low-frequency oscillation even at higher value of droop gains which are usually unstable otherwise. The PSS designed in this paper is a generalized one and a step-by-step method to select the PSS parameters is also presented. Time domain simulation, experimental results, and eigenvalue analysis are presented for verification of the proposed controller. [ABSTRACT FROM AUTHOR]

In this paper, we modify the graph model for conflict resolution (GMCR) to model interactive unawareness of decision makers (DMs) about the options available to them in the conflict. More specifically, we consider a GMCR with two DMs, where a DM, in some given state, can be unconscious about some of his options, or about the options of his opponent, and therefore, may have only a partial knowledge of the state space. By interactive unawareness, it is meant that a DM can reason about the awareness level of the other DM and about the awareness level of the other DM regarding his or her own awareness level and so on. We generalize standard solution concepts for this model and illustrate its usefulness by means of a hypothetical war conflict. [ABSTRACT FROM AUTHOR]

With the continuous iteration of information technology, information presents an explosive development trend, so how to effectively classify, retrieve, and summarize information is very important. Data classification and mining technology as the key technology to solve the aforementioned problems is of great significance. At present, in the fields of data processing, information classification and machine learning reinforcement learning, it is usually based on the learning automata, but the traditional learning automata algorithm cannot meet the development of information technology in terms of convergence and learning rate. In order to improve the convergence stability and learning efficiency of the learning automata algorithm in random environment and enhance its learning ability in dealing with large-scale space and action, this paper innovatively proposes an adaptive fuzzy reinforcement learning model of the learning automata, which makes full use of the randomness of gradient information to solve its stability problem, and abandons the original reinforcement learning method. For the linear function, an adaptive fuzzy numerical superposition algorithm is used to further enhance its learning rate and improve its stability. The experimental results show that the proposed learning automata fuzzy reinforcement learning model has practical application value, and can solve the problems of unstable convergence and poor learning efficiency of the current learning automata. [ABSTRACT FROM AUTHOR]

The papers in this special section brings together papers focused on the recent advancements and breakthroughs in the technology of modeling and enhanced active/reactive power control of wind power conversion systems, ranging from components of wind turbines to wind farms. [ABSTRACT FROM PUBLISHER]

The stability of discrete event systems (DESs) is a property related to its robustness; a stable DES is guaranteed to reach a set of desired states in a finite number of steps. Algorithms proposed in the literature are useful for analyzing the stability of DES modeled either by finite automata or a constrained subclass of Petri nets (PNs). In this paper, a novel method to decide the stability of safe PNs is presented. It is based on the analysis of the finite complete prefix of the net unfolding rather than the reachability graph. For concurrent systems, the prefix is usually smaller than the reachability graph and then the analysis using the proposed algorithm is more efficient than analyzing the reachability set of the PN. Note to Practitioners—The stability of a discrete event system (DES) is a property that guarantees that the DES will return to the normal operation behavior after a disturbance deviates the system from such a behavior. This is a key property that a controlled DES must fulfill. The algorithms proposed in this paper allow determining efficiently the stability of concurrent DES by analyzing the Petri net structure. [ABSTRACT FROM AUTHOR]

The LCL-based filter has been widely applied to mitigate the size of the inductor in the high-power converter, but it usually leads to resonance in the system. Therefore, an active damping technique based on the virtual resistor is provided in this paper for the LCL-filter system. The literature papers only suppressed the resonance of the LCL-filter and focused on the stability of the internal current control loop with an inductive grid impedance. Therefore, these previous stability analysis methods cannot be suitable for offshore wind farm applications due to the multiple resonance frequency characteristic of the transmission cable and multiparalleled converters. Therefore, this paper analyzes the control stability with both of the internal resonance (LCL-filter) and external resonance (between the grid impedance and current controller). Besides, the behavior of multiparalleled converter and the multiple resonance frequency of long transmission cable are discussed and analyzed for the offshore wind farm applications. Finally, the laboratory and simulation results are for the proposed method verification. [ABSTRACT FROM AUTHOR]

In this paper, the damping ability of point of common coupling (PCC) voltage feedforward is analyzed in order to improve the stability of current control, in which interference with an LCL filter of a battery energy storage system (BESS) and synchronous inductance of a diesel generator is considered in a stand-alone microgrid. A BESS can be charged by a diesel generator when the state of charge of the battery bank is significantly insufficient and where the BESS operates with constant current constant voltage control and the diesel generator provides constant voltage constant frequency control. In this case, large synchronous when the diesel generator is in a steady state may severely cause the instability of current control. The stability analysis should be required to guarantee the paralleled operation between BESS and diesel generator. An equivalent circuit model of the diesel generator is needed to perform these processes. To bring availability of analysis, this paper considers a simple equivalent circuit model considering synchronous inductance in the steady state, and it has very large inductance corresponding 1 per unit. The resonance issue is attenuated by the damping ability of PCC voltage feedforward where it is possible to improve the stability by appropriately adjusting the gain of the voltage feedforward. The effects of the synchronous inductance and the feedforward loop are analyzed in the s-domain and z-domain. The gain of the voltage feedforward is determined to be 0.2 and 0.4 based on stability analysis. To verify the validity of the damping effect of PCC voltage feedforward, a demonstration site is constructed and the stability is verified through simulation and experiment with a full model, and total harmonic distortion of current is improved to 2.44%. [ABSTRACT FROM AUTHOR]

Till now, there are lots of stability and stabilization results about Takagi–Sugeno (T–S) fuzzy systems with time delay, but most of them are independent of the analysis of membership functions. Since the membership functions are an essential component to make a fuzzy system different from others, the conditions without its information are conservative. In this brief paper, a new Lyapunov–Krasovskii functional is designed to investigate the stability and stabilization of continuous-time T–S fuzzy systems with time delay. Different from the existing results in the literature, the integrand of the Lyapunov–Krasovskii functional in this paper depends not only on the integral variable, but also on the membership functions, and thus, the information of the time derivative of membership functions can also be used to reduce the conservativeness of finding the maximum delay bounds. Utilizing the information of the time derivative of membership, a number of controllers are designed according to their sign, and then, a switching idea is applied to stabilize the fuzzy system. In the end, two examples are given to illustrate the feasibility and validity of the design and analysis. [ABSTRACT FROM AUTHOR]

This paper addresses the distributed consensus controller design approaches for one-sided Lipschitz nonlinear multiagents by employing relative state feedback. A new treatment for one-sided Lipschitz nonlinearity is rendered from the consensus control point of view. By employing the quadratic inner-boundedness and the one-sided Lipschitz constraints, a sufficient condition for asymptotic consensus of nonlinear systems under strongly connected communication topologies is provided. Further, a robust consensus protocol design scheme for the nonlinear multiagents is derived by ensuring the ${L_{2}}$ stability of the consensus error system. Furthermore, a novel robust consensus control scheme against amplitude-bounded perturbations is developed that guarantees asymptotic convergence of the consensus error into a compact set. Extensions to the proposed methodologies for the leader-following consensus for a spanning tree communication topology with the leader as the root are addressed. In contrast to the conventional consensus control methodologies, this paper is less conservative and can be applied to a broader class of nonlinear multiagent systems. Moreover, the proposed consensus control approach is less conservative for robustness against disturbances owing to its ability to handle amplitude-bounded disturbances and due to the relaxation of a balanced communication topology. A numerical simulation study is provided for the consensus control of eight mobile agents. [ABSTRACT FROM AUTHOR]

Spectrum trading creates more accessing opportunities for secondary users (SUs), and economically benefits the primary users (PUs). Compared with centralized spectrum trading designs, e.g., spectrum auction, distributed spectrum trading captures instantaneous spectrum trading opportunities better over large geographical regions without incurring extra infrastructure deployment and has no network scalability issues. However, the existing distributed spectrum trading designs have limited concern regarding spectrum reuse. Considering spatial reuse, in this paper, we propose a novel distributed frequency reuse-based opportunistic spectrum trading (D-FROST) scheme, which can further improve spectrum utilization, provide more accessing opportunities for SUs, and increase the revenues of PUs. In this paper, we employ conflict graph to characterize the SUs’ co-channel and radio interferences, and mathematically formulate a centralized PUs’ revenue maximization problem under multiple wireless transmission constraints. Due to the NP-hardness to solve the problem and the non-existence of centralized trading entity, we develop the D-FROST algorithms based on matching with evolving preferences, and prove its stability. Through extensive simulations, we show that the proposed D-FROST algorithm is superior to other distributed spectrum trading algorithms without considering spectrum reuse, yields results close to the centralized optimal one, and is effective in increasing PUs’ revenue and improving spectrum utilization. [ABSTRACT FROM AUTHOR]

The stability of haptic rendering is affected by many factors that limit the range of impedances that can be applied to virtual objects. This paper addresses the effect of the vibration modes of the haptic interface on the stability of the impedance control loop. It is well known that experimental stability boundaries present complex shapes, making it difficult to predict the final $Z$ -width of the haptic system. This paper shows how the vibration modes of the mechanical interface highly affect the size of the $Z$ -width, causing a sudden reduction in the critical virtual stiffness $K$ if the virtual damping $B$ is increased beyond a certain value. The inclusion of the most significant vibration modes in the theoretical model of the haptic system—together with the viscous damping, time delay and sampling rate—makes it possible to obtain the stable impedances associated with the haptic device. A PHANToM Premium 1.0 haptic interface was used as a test bed to validate this paper. Although results have been tested only on this device, this paper proposes a methodology for obtaining the $Z$ -width that can be generalized for any other haptic system. [ABSTRACT FROM AUTHOR]

Maritime traffic prediction is critical for ocean transportation safety management. In this paper, we propose a novel knowledge assisted methodology for maritime traffic forecasting based on a vessel’s waterway pattern and motion behavior. The vessel’s waterway pattern is extracted through a proposed lattice-based DBSCAN algorithm that significantly reduces the problem scale, and its motion behavior is quantitatively modeled for the first time using kernel density estimation. The proposed methodology facilitates the knowledge extraction, storage, and retrieval, allowing for seamless knowledge transfer to support maritime traffic forecasting. By incorporating both the vessel’s waterway pattern and motion behavior knowledge, our solution suggests a set of probable coordinates with the corresponding probability as the forecasting output. The proposed forecasting algorithm is capable of accurately predicting maritime traffic 5, 30, and 60 min ahead, while its computation can be efficiently completed in milliseconds for single vessel prediction. Owing to such a high computational efficiency, an extensive predictive analysis of hundreds of vessels has been reported for the first time in this paper. A web-based prototype platform is implemented for Singapore waters to demonstrate the solution’s feasibility in a real-world maritime operation system. The proposed approaches can be generalized for other marine waters around the world. [ABSTRACT FROM PUBLISHER]

Differentiable architecture search (DARTS) enables effective neural architecture search (NAS) using gradient descent, but suffers from high memory and computational costs. In this paper, we propose a novel approach, namely Partially-Connected DARTS (PC-DARTS), to achieve efficient and stable neural architecture search by reducing the channel and spatial redundancies of the super-network. In the channel level, partial channel connection is presented to randomly sample a small subset of channels for operation selection to accelerate the search process and suppress the over-fitting of the super-network. Side operation is introduced for bypassing (non-sampled) channels to guarantee the performance of searched architectures under extremely low sampling rates. In the spatial level, input features are down-sampled to eliminate spatial redundancy and enhance the efficiency of the mixed computation for operation selection. Furthermore, edge normalization is developed to maintain the consistency of edge selection based on channel sampling with the architectural parameters for edges. Theoretical analysis shows that partial channel connection and parameterized side operation are equivalent to regularizing the super-network on the weights and architectural parameters during bilevel optimization. Experimental results demonstrate that the proposed approach achieves higher search speed and training stability than DARTS. PC-DARTS obtains a top-1 error rate of 2.55 percent on CIFAR-10 with 0.07 GPU-days for architecture search, and a state-of-the-art top-1 error rate of 24.1 percent on ImageNet (under the mobile setting) within 2.8 GPU-days. [ABSTRACT FROM AUTHOR]

This paper presents some results on the accuracy of normal form analysis for large deviations from the stable equilibrium point (SEP) in a power system. The results of studies on the region of convergence of Neumann series, which is required for normal form analysis, are presented. A polynomial function approximation is proposed to model the generator exciter limiter. Studies on the accuracy of higher order normal form analysis for large deviations from SEP are presented. Use of Prony analysis in addition to simulation is proposed for the verification of accuracy. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of the dynamic properties of a photovoltaic generator (PVG) on the stability of a grid-connected current-source inverter (CSI)-based photovoltaic system and presents a simple yet effective active compensator to ensure system stability. A detailed equivalent model of the PVG that considers the dynamic resistance, diffusion capacitance, series inductance, and dc cable resistance and inductance is used, and the effects of these parameters are assessed. It has been found that when the PVG operates in the constant-current region (CCR), the phase margin becomes negative in the control-to-input dynamics, which alters the stability of the dc-link current control. The change in the system dynamics when the operating point of the PVG shifts from the constant-voltage region (CVR) to CCR is verified through a detailed small-signal state-space model of the complete system. Furthermore, an active compensator is proposed to ensure stable dc-link current control operation at all operating points of the PVG. The influence of different control parameters on the integrated system dynamics is examined to determine the range of the control parameters required for stable operation. The performance of the proposed system under utility-grid fault, grid voltage parameter variation, weak grid, and changes in insolation level is also evaluated. Detailed nonlinear time-domain simulation results, using a typical utility-scale CSI-based PV system, validate the analytical results and the effectiveness of the proposed active stabilization under different operating conditions. [ABSTRACT FROM AUTHOR]

The use of VSC-HVDC grids for offshore wind farm integration will require the use of dc breaker systems and presently they require dc reactors to limit the rate of rise of fault current. The introduction of large dc reactors throughout a VSC-HVDC system can have a significant impact on its stable operation and will require additional control. This paper analyzes this problem and proposes a PSS-like control (DCPSS) to aid dc grid stability and cope with this effect. A generalized analytical model for studies on dc voltage control is presented. Key stability and transient performance issues caused by the use of the dc reactors in a multiterminal system are investigated by analyzing poles, zeros, and frequency responses of open-loop and closed-loop models. Design and location identification methods for the DCPSS are provided. An excellent damping enhancement is achieved by this controller. The analytical studies and time-domain simulations in this paper are performed based on two VSC-HVDC models. [ABSTRACT FROM AUTHOR]