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Pumped storage hydro units (PSHU) can provide flexibility to power systems. This becomes particularly valuable in recent years with the increasing shares of intermittent renewable resources. However, due to emphasis on thermal generation in the current market practices, the flexibility from PSHUs has not been fully explored and utilized. This paper proposes a configuration based pumped storage hydro (PSH) model for the day-ahead market, in order to enhance the use of PSH resources in the system. A strategic design of incorporating and fully optimizing PSHUs in the day-ahead market is presented. We show the compactness of the proposed model. Numerical studies are presented in an illustrative test system and the Midcontinent Independent System Operator (MISO) system. [ABSTRACT FROM AUTHOR]

In the steady-state contingency analysis, the traditional Newton-Raphson method suffers from non-convergence issues when solving post-outage power flow problems, which hinders the integrity and accuracy of security assessment. In this paper, we propose a novel robust contingency analysis approach based on holomorphic embedding (HE). The HE-based simulator provides theoretical convergence guarantee, which is desirable because it avoids the influence of numerical issues and provides a credible security assessment conclusion. In addition, based on the multi-area characteristics of real-world power systems, a partitioned HE (PHE) method is proposed with an interface-based partitioning of HE formulation. The PHE method does not undermine the numerical robustness of HE and significantly reduces the computation burden in large-scale contingency analysis. The PHE method is further enhanced by parallel or distributed computation to become parallel PHE (P2HE). Tests on a 458-bus system, a synthetic 419-bus system and a large-scale 21 447-bus system demonstrate the advantages of the proposed methods in robustness and efficiency. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to dynamic phasor-based transient stability simulation. The proposed method is based on the modified nodal analysis (MNA) approach to circuit simulation, which is used to construct continuous differential-algebraic equations (DAEs). The proposed method makes use of the stamp technique, which makes it possible to construct a general purpose MNA-based simulator. Stamp-based models for common power system components are derived in this work. A new MNA-based synchronous machine model is presented, which represents machines as nonlinear inductances instead of subtransient equivalents. The resultant continuous DAEs are numerically solved using the general purpose variable step and variable order library IDA. Simulation results from the IEEE 68 bus test system, a real 400 bus power system, and the IEEE 39 bus test system with an embedded HVdc transmission system demonstrate that the proposed method is suitable for large ac networks with power electronic devices. The results demonstrate good agreement between the proposed method and electromagnetic transient (EMT) simulation. The results also demonstrate that the proposed method is fast and scalable with CPU times that are up to 200 times faster than EMT simulation. [ABSTRACT FROM AUTHOR]

This paper develops a grey-box approach to small-signal stability analysis of complex power systems that facilitates root-cause tracing without requiring disclosure of the full details of the internal control structure of apparatus connected to the system. The grey-box enables participation analysis in impedance models, which is popular in power electronics and increasingly accepted in power systems for stability analysis. The Impedance participation factor is proposed and defined in terms of the residue of the whole-system admittance matrix. It is proved that, the so defined impedance participation factor equals the sensitivity of the whole-system eigenvalue with respect to apparatus impedance. The classic state participation factor is related to the impedance participation factor via a chain-rule. Based on the chain-rule, a three-layer grey-box approach, with three degrees of transparency, is proposed for root-cause tracing to different depths, i.e. apparatus, states, and parameters, according to the available information. The association of impedance participation factor with eigenvalue sensitivity points to the re-tuning that would stabilize the system. The impedance participation factor can be measured in the field or calculated from the black-box impedance spectra with little prior knowledge required. [ABSTRACT FROM AUTHOR]

In light of the increasing coupling between electricity and gas networks, this paper introduces two novel iterative methods for efficiently solving the multiperiod optimal electricity and gas flow (MOEGF) problem. The first is an iterative MILP-based method and the second is an iterative LP-based method with an elaborate procedure for ensuring an integral solution. The convergence of the two approaches is founded on two key features. The first is a penalty term with a single, automatically tuned, parameter for controlling the step size of the gas network iterates. The second is a sequence of supporting hyperplanes and halfspaces for controlling the convergence of the electricity network iterates. Moreover, the two proposed algorithms use as a warm start the solution from a novel polyhedral relaxation of the MOEGF problem, for a noticeable improvement in computation time as compared to a cold start. Unlike the first method, which invokes a branch-and-bound algorithm to find an integral solution, the second method implements an elaborate steering procedure that guides the continuous variables to take integral values at the solution. Numerical evaluation demonstrates that the two proposed methods can converge to high-quality feasible solutions in computation times at least two orders of magnitude faster than both a state-of-the-art nonlinear branch-and-bound (NLBB) MINLP solver and a mixed-integer convex programming (MICP) relaxation of the MOEGF problem. The experimental setup consists of five test cases, three of which involve the real electricity and gas transmission networks of the state of Victoria with actual linepack and demand profiles. [ABSTRACT FROM AUTHOR]

This paper studies the communication time-delay issue in islanded microgrids (MGs) with the distributed secondary control architecture. Firstly, a time-delayed MG small-signal model is developed. Then, a new weight-average-prediction (WAP) controller is proposed to compensate the delayed system states. By introducing a time-delayed differential term in the proposed control law, the traditional time-delayed small-signal model is transformed into a neutral time-delayed mathematic model. Based on the developed model, the stability analysis is conducted considering both fixed time delay and time-varying delay. For the fixed time delay, a novel graphic analytical method is proposed to evaluate the time delay margin, which eliminates the conservatism compared with existing time-domain methods. For the time-varying delay, stability condition is established by a Lyapunov-Krasovskii function and linear matrix inequalities. In addition, some non-linear WAP control methods are discussed to guide the parameter tuning with a higher resolution. Lastly, the proposed method and analytical result are verified in the OPAL-RT real-time test platform. The results demonstrate the effectiveness and high performance of the proposed controller. [ABSTRACT FROM AUTHOR]

Distributed optimization algorithms for security-constrained economic dispatch (SCED) problems have been the subject of significant research interest in recent years. However, existing distributed SCED algorithms can be ineffective in the presence of malicious participants and inefficient in the absence of a coordinator. On the other hand, blockchain, an emerging technique known as the trust machine, has not shown its potential to address the above challenges in state-of-the-art literature. This paper proposes a blockchain-based distributed SCED algorithm. Using blockchain to form a coordination committee and enable balance among committee members, the proposed method allows the use of hierarchical SCED algorithms in the absence of a coordinator and can disable malicious participants. Numerical results show the robustness and necessity of the proposed blockchain-based SCED algorithm, by comparing the SCED results with and without blockchain. [ABSTRACT FROM AUTHOR]

The frequency stability of microgrids is of paramount importance due to their low inertia and high share of renewable energy sources. In this paper, a frequency stability-constrained microgrid scheduling (FSC-MS) model is developed based on a time-dependent discretized frequency response model considering seamless unintentional islanding events. The optimal dispatch of controllable units, as well as optimal upward and downward primary reserves, are determined with a minimum operating cost while ensuring frequency stability criteria are maintained in their safe ranges following an unintentional islanding event, such as rate of change of frequency (RoCoF) and frequency nadir and overshoot. The limitation of generators with respect to primary frequency response is formulated in the form of primary reserve capacity and primary ramp rate limits. A cost-based model is presented to describe the available primary reserve of synchronous generators. The proposed FSC-MS model is formulated as a mixed-integer linear programming (MILP) problem using Benders decomposition. Simulation results on a medium voltage microgrid test system demonstrate the effectiveness of the proposed model to meet the frequency stability constraints while minimizing the total operating cost. [ABSTRACT FROM AUTHOR]

Traditional Potentiometric Ion-selective Electrodes (ISE) are widely used in industrial and clinical settings. The simplicity and small footprint of ISE have encouraged their recent adoption as wearable/implantable sensors for personalized healthcare and precision agriculture, creating a new set of unique challenges absent in traditional ISE. In this paper, we develop a fundamental physics-based model to describe both steady-state and transient responses of ISE relevant for wearable/implantable sensors. The model is encapsulated in a “generalized Nernst formula” that explicitly accounts for the analyte density, time-dynamics of signal transduction, ion-selective membrane thickness, and other sensor parameters. The formula is validated numerically by self-consistent modeling of multispecies ion-transport and experimentally by interpreting the time dynamics and thickness dependence of thin-film solid-contact and graphene-based ISE sensors for measuring soil nitrate concentration. These fundamental results will support the accelerated development of ISE for wearable/implantable applications. [ABSTRACT FROM AUTHOR]

This paper proposes an inequality constraints based method to efficiently and quickly estimate stability regions of droop control slopes for modular multilevel converter (MMC)-based multi-terminal dc (MTDC) systems. At first, a general small-signal model of the MMC-MTDC system is developed, which consists of the dc network and the MMCs with $dq$ controllers and multiple droop controllers. When deriving corresponding nonlinear state-space models, the edge-node matrix is introduced for the dc network modeling with arbitrary grid topology and transmission line model. Then, based on the eigenvalues sensitivity and the Taylor Series of eigenvalues, a set of inequality constraints are proposed to expeditiously estimate the suprema of the droop slopes and identify the droop slope stability regions for the MMC-MTDC system. To verify the state-space model, a comparison of dynamic responses between the math model calculation in MATLAB and the EMT simulation in PSCAD/EMTDC is conducted, which demonstrates the accuracy and the correctness of the developed small-signal model. The effectiveness of the proposed parameter stability region estimation method is demonstrated by several examinations including the supremum tests of droop slopes, the stability region sketches on accuracy, and the predicted unstable operations in PSCAD/EMTDC. [ABSTRACT FROM AUTHOR]

This paper investigates a comprehensive optimization method of determining the size and location of dynamic voltage restorers (DVRs) in distribution network considering customers’ demand for sag mitigation. The objective is to minimize the investment of DVRs subject to customers’ satisfaction. In the objective function, the unit price per kVA of DVR was described by a continuous function of the capacity to calculate the investment. In the constraints, a mitigation expectation index (MEI) was proposed to assess the customers’ demand for mitigation. The MEI indicates the proportion among all sag events affecting customers, which were expected to be mitigated by the customers. It is represented by the cumulative probability of residual voltage of sag events. To improve the computational efficiency, the binary encoding for the locations and real encoding for the output voltage of DVRs are combined as chromosomes in multiple population Genetic Algorithm (MPGA). The proposed method was testified with the IEEE 33 bus distribution system with different sensitive loads. Optimal results were obtained to satisfy different customers’ demand for sag mitigation efficiently. [ABSTRACT FROM AUTHOR]

This paper presents a multiobjective optimization technique for the submarine cables of high-power remotely operated vehicles (ROVs). A detailed design flowchart with integrated electrical and mechanical designs of the ROV submarine cables is provided to quantitatively compare AC and DC-based power distribution systems and identify the optimal design from multiple standpoints, prioritizing electrical loss and cable weight. The electromechanical cable design optimization plays a vital role in the ROV industry and in all those applications where the power distribution system is employed vertically from the support platform/vessel. The entire procedure is exemplified by carrying out a particular case study; for an ROV power hub with rated power of 5 MW and operational depth of 6000 m, the DC submarine cable design with distribution voltage of 33 kV results in an electrical loss reduction of 54.3% compared to the AC submarine cable design with distribution voltage of 22 kV at similar cable weights of 63 ton. Additionally, the proposed method can be widely applied to any type of AC-DC comparison to achieve the optimal ROV submarine cable design with a considerably short process time in comparison to the approaches with finite element analysis. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach, based on the theory of hyperplanes, for mode identification of linear systems. The proposed approach can operate on either a set of ordinary differential equations (converted to diagonal form, if needed) or a set of partial fractions derived from a synthesized transfer function of the system under analysis. For either format, the linear system is structured to have as unknown variable a vector containing the residues. Singular value decomposition is initially used to identify an initial sparsity of the residue vector where the number of nonzero values corresponds to the pre-defined order of the dominant poles (eigenvalues) under search. An algorithm based on geometrical search of hyperplanes is used to optimize the selection of the nonzero residue locations, minimizing the residual of the zero residue hyperplanes. Finally, a recalculation of the residues is carried out by using the obtained optimal sparsity. [ABSTRACT FROM AUTHOR]

A reduced-order model of a converter-dominated microgrid system may not resemble its full-order system associated with uncertainties. This paper aims to provide a singular perturbation-based contraction framework for model order reduction in converter-dominated uncertain microgrid systems. For this purpose, the concerned microgrid system is modeled as a generalized multi-timescale system, and certain sufficient conditions are derived such that convergence between the trajectories of the uncertain full-order and the corresponding reduced-order model can be guaranteed. The contraction theory-based strategy also provides explicit parameter-dependent expressions for quantifying discrepancies. The derived results are utilized to analyze the inverter-based microgrid system’s convergence behavior and obtain uncertainty bounds on its parameters. Further, the effects of modeling uncertainties and different loading conditions on the reduced-order model’s validity are also discussed. It is observed that for any uncertainty associated with the microgrid parameters that are within the bounds of checkable conditions, the states of the reduced-order microgrid model converge to that of the uncertain full-order system. Further, it is also shown that the obtained discrepancy expressions are more precise than state of the art. [ABSTRACT FROM AUTHOR]

Performance prediction of induction machines (IMs) is highly dependent on the accuracy of the material characteristics and geometry of the machine during the modeling stage. To reduce the complexity of an IM model, normally the slotting effects are neglected. Likewise, the permeability of the stator and rotor cores are assumed to be infinite leading to an ideal set of partial differential equations (PDEs) for homogenous and isotropic materials. In this paper, the permeability of the stator and rotor cores are assumed not to be infinite and the slotting effects are taken into consideration to propose a more accurate and realistic model of an IM to reduce the discrepancies between the performance expectations and actual results. Fourier-based (FB) magnetic field approach is used to fulfill this aim via anisotropic layer theory (ALT) enabling the proposed model to include distortion of magnetic flux in the slotted regions. Air-gap flux density, core losses, efficiency and torque of an IM are predicted via the FB model and are validated through the finite element analysis (FEA) and experimental studies. [ABSTRACT FROM AUTHOR]

This paper focuses on the transient modelling of a specific type of permanent magnet linear synchronous machine designed for line-start operation. The machine uses conductive ladders embedded in the mover to realise a permanent-magnet machine capable of line-start operation. Transient modelling of this type of machine under line-start conditions is critical to optimising machine design, and electrical and mechanical performance prediction, which leads us to devise a novel set of matrices of electrical parameters first. These matrices are developed considering both the impact of the conductive ladders and the longitudinal end effect based on electromagnetic field analysis. The model is then suitable for numerical computation in typical simulation environments. This yields a sufficiently accurate transient model that is verified by experimental results. Hence our novel model, that includes the longitudinal end effects and the effects of conductive ladders, is proven effective in predicting the line-start transients and associated electrical and mechanical performance. The novel model assists in the design optimisation stage where a compromise between synchronised performance and line-start operation is required. The novel machine type can then be investigated as a competitive candidate topology in various applications including electromagnetic launch. [ABSTRACT FROM AUTHOR]

Accurate and computationally-efficient models of induction machines (IMs) are essential for many simulation programs and analysis of power systems transients. Conventionally, when modeling magnetic saturation in the classical qd0 models, only the fundamental component of magnetizing flux is considered. To represent the saturation air-gap flux harmonics, fairly complicated phase-domain and/or implicit models have been proposed in the prior literature. In this paper, a new explicit two-axis IM model is developed to include the air-gap harmonics caused by magnetic saturation. The new model is validated by experimental measurements and simulations in various steady state and transient scenarios and is shown to provide accurate results while being simple to implement. [ABSTRACT FROM AUTHOR]

Frequency response analysis (FRA) is a popular tool to detect transformer winding deformation faults. It has been recently used to diagnose the winding inter-turn short circuit fault of the electric machine. The application of FRA is based on the fact that the winding can be equivalent to an electrical circuit consisting of resistance, inductance, and capacitance. Therefore, to obtain an accurate broadband equivalent circuit model of synchronous machine and perform the fault analysis and diagnosis, this paper introduces the gray box model technique based on the state space and genetic algorithm. The electrical circuit of a form-wound coil of a 4 kW machine with known electrical parameters is used to verify the proposed method primarily. Besides, the equivalent circuit modeling is carried out and experimentally verified on an actual 5 kW synchronous machine. Finally, the fault simulation analyses of winding inter-turn short circuits are performed based on the proposed equivalent electrical circuit. The verification result shows that the circuit parameters identified by the proposed method are accurate. Moreover, the fault simulation results indicate that the inter-turn short circuit faults can cause apparent variations in the frequency response curves. It is feasible to detect the winding fault of the synchronous machine by the FRA method. [ABSTRACT FROM AUTHOR]

This paper presents a new Magnetic Equivalent Circuit (MEC) to model the Variable Reluctance Resolver (VR-Resolver) and study the effect of different windings configurations on its performance. Therefore, VR-Resolver with non-overlapping (constant turn) and overlapping (variable turn) windings are modeled to investigate their effect on the accuracy of obtained results. The proposed method gives the possibility to model both healthy and faulty conditions by a unique model to analyze faults effects on the position error. For this purpose, the inter-turn fault is considered on the excitation winding, and both dynamic and static eccentric rotors (DE and SE) are studied. It is shown that the variable turn VR-Resolver has more accuracy and lower sensitivity to eccentricity fault, while the constant turn type is less sensitive to inter-turn fault. However, the latter may be preferred in some applications thanks to its simpler windings and lower manufacturing costs. Finally, the MEC results are proved by Finite Element Method (FEM) and experimental results. Generally, the model flexibility and shorter processing time can be considered as the proposed MEC advantages over FEM. [ABSTRACT FROM AUTHOR]

Impedance modeling of a permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS) usually ignores the machine-side dynamics, instead, the machine-side system is simplified as a constant power source, while merely keeping the detailed grid-side converter model. This simplification is mainly based upon the intuition that the dc-bus capacitor is large enough so that the machine- and grid-side dynamics can be decoupled. However, the simplification probably does not hold in practice since there is always a tendency to minimize the capacitor size to achieve a smaller package for installation. Therefore, the machine-side system should not be ignored, otherwise maybe leading to error for stability analysis. To address this issue, this paper developed a complete ac-side impedance model of the PMSG-based WECS. Then, impact factors about the coupling characteristics between machine- and grid-side systems of the PMSG-based WECS are discussed. Finally, a case study of sub/super synchronous oscillation is carried out on a practical offshore wind farm integrated with a modular multilevel converter based high-voltage dc (MMC-HVDC) transmission system in China. The results show that ignoring the machine-side system would lead to an optimistic stability judgement, which confirms the necessity of the complete model of PMSG-based WECS. Furthermore, the system can be stabilized by either changing the couplings between machine- and grid-side systems of PMSG-based WECS or implementing active damping in the wind farm side MMC. [ABSTRACT FROM AUTHOR]

Winding faults are the most commonly occurring type of fault in offshore doubly-fed generator units. Such faults are difficult to detect and repair, and therefore higher fault identification accuracy is required. Most of the existing research analyzes stator and rotor winding faults separately, but due to the coupling characteristics between windings, it is necessary to analyze doubly-fed induction generator (DFIG) winding faults in a unified way. This paper proposes a general fault diagnosis method that can be applied to both the stator and rotor winding faults of DFIGs. First, a general mathematical model of a windings short circuit of a doubly-fed generator is established. Then, according to the mechanism of a turn-to-turn short circuit fault of a DFIG and the expression of a bilateral flux linkage between stator winding and rotor winding, a new fault feature-bilateral flux linkage difference vector (FLDV) is obtained by mathematical derivation. Finally, the recommended value for an experimental motor of feature quantity is set. The proposed method for inter-turn fault (ITF) diagnosis of stator and rotor windings provides technical support for the sustainable development of offshore wind power. A simulation and experiment prove that FLDV has high sensitivity and high reliability for windings ITF diagnosis. [ABSTRACT FROM AUTHOR]

This paper presents a modified Mayergoyz-based vector hysteresis model to describe the anisotropic material behavior of nonoriented (NO) steels over a wide range of rotational excitations. The proposed model adopts a new representation of a vector Everett function, which is actually an elliptical interpolation motivated by the real anisotropic behavior of NO steel, to deal with the uniaxial anisotropy characteristic, which is especially pronounced at low induction levels. The biaxial anisotropy occurring at high densities is described by a nonlinear coefficient, which is actually a function of the magnitude of magnetic flux density. A systematic identification algorithm is given in detail. The validity of this model is verified through comparison with experimental data under both alternating and rotational excitations. The 2-D finite element analysis (FEA) of incorporating this model into TEAM problem 32 simulation is also illustrated. [ABSTRACT FROM AUTHOR]

For the short-term high torque output, an improved model predictive direct torque control (MPDTC) method with field enhancing is proposed to increase torque. In order to avoid the possible loss of synchronism while increasing torque, the MPDTC method limits the load angle in the cost function. Under the constant load angle limitation, the improved method increases the torque output capability by increasing the magnetic field. This paper starts from the torque calculation, theoretically analyzes the torque-load angle characteristics, and illustrates the flux vector trajectory with the voltage limit circle and current limit circle. The proposed method maintains the dynamic and static performance of the traditional MPDTC method while ensuring the system stability. The experimental results show that the torque capacity of the proposed method has been improved, and it has stable extreme output torque. So, some applications, such as electric load simulators, can choose the motor with small capacity and small inertia, thereby weakening negative effects of the inertia torque. [ABSTRACT FROM AUTHOR]

This paper proposes a new fast chargingstrategy for lithium-ion (Li-ion) batteries. The approach relies on an experimentally validated high-fidelity model describing battery electrochemical and thermal dynamics that determine the fast charging capability. Such a high-dimensional nonlinear dynamic model can be intractable to compute in real-time if it is fused with the extended Kalman filter or the unscented Kalman filter that is commonly used in the community of battery management. To significantly save computational efforts and achieve rapid convergence, the ensemble transform Kalman filter (ETKF) is selected and tailored to estimate the nonuniform Li-ion battery states. Then, a health- and safety-aware charging protocol is proposed based on successively applied proportional-integral (PI) control actions. The controller regulates charging rates using online battery state information and the imposed constraints, in which each PI control action automatically comes into play when its corresponding constraint is triggered. The proposed physical constraint-triggered PI charging control strategy with the ETKF is evaluated and compared with several prevalent alternatives. It shows that the derived controller can achieve close to the optimal solution in terms of charging time and trajectory, as determined by a nonlinear model predictive controller, but at a drastically reduced computational cost. [ABSTRACT FROM AUTHOR]

A dynamic model of a battery is required for the appropriate real-time control during charging/discharging process. Present paper considers the development of nonlinear Dynamic Equivalent Electric Circuit Model (DEECM) of a Valve Regulated Lead-Acid (VRLA) battery based on the data obtained through the experimentation and the available datasheet information. Cases of charging, discharging, and the self-discharging are considered for 12V, 26Ah VRLA battery at room temperature. Accordingly, experimental ${\boldsymbol{v}} - {\boldsymbol{i}}$ characteristics of the battery are used to express the nonlinear model parameters as a function of measurable battery current and estimated open-circuit voltage as a part of parameter estimation. Further model is validated through voltage response test with maximum error of 0.4% during discharging and 0.7% during charging under different current levels. [ABSTRACT FROM AUTHOR]

This paper aims to improve the performance of the permanent magnet synchronous motor (PMSM) speed regulation system by combining a novel disturbance observer (DOB) with the super-twisting sliding mode (STSM) technique. First, a STSM controller is constructed to eliminate the adverse effects of the lumped disturbance in the PMSM speed regulation system. A novel DOB is introduced to estimate and compensate the lumped unknown disturbance, which constitutes a composite controller with a feedforward compensation term and a state-feedback control. As a result, the gain of the composite sliding mode controller can be significantly reduced, which will improve the performance of the closed-loop PMSM speed regulation system. The validity and robustness of the proposed composite control scheme are fully verified by simulation and experimental results. [ABSTRACT FROM AUTHOR]

The main idea of this paper is to offer a continuous C-cores unique configuration for switched reluctance motor (SRM) and to present an analytical model for its analysis. The advantages of this structure are having a short path for the main part of the magnetic flux, resulting in less core losses and as well as less negative torque. On the other hand, there is less leakage flux in the proposed structure. Another advantage of this structure is that it has a high mean torque compared to conventional structures, so that this increase in mean torque also increases a small amount of torque ripple, which is negligible. However, power density at a constant volume increases relatively much. The proposed SRM is analyzed by the finite element method (FEM) and by employing a magnetic flux density pattern and magnetic fluxes path, its magnetic equivalent circuit (MEC) is obtained. In this MEC model, the main fluxes and leakage fluxes are fully modeled. After its complete analysis, electromagnetics torque, inductance, flux-linkage, mean torque, and peak torque are evaluated. Static and dynamic performances are then determined. Finally, the proposed SRM was prototyped and tested. The experimental results consisting of static torque, flux-linkage, voltage, and current waveforms and input power are compared with the corresponding results in the MEC model and FEM. The comparisons verify the accuracy and validity of the introduced analytical model. Besides, static torque, flux-linkage characteristics, and dynamic performance at a nominal speed of 1000 rpm and the current chopping control mode with chopping 5A under the load of the proposed SRM are compared with the conventional SRM and its merits are observed. [ABSTRACT FROM AUTHOR]

In order to realize the grid-friendly wind turbine system (WTS), applying of the virtual synchronous generator (VSG) control strategy to WTS has become a trend of research, and it is also required to analyze the grid-connected operation characteristics of the VSG controlled WTS. In this paper, the impedance modeling and impedance-based stability analysis of the VSG controlled type-IV WTS are carried out. Different from existing impedance modeling method that the WTS is modeled by a high dimensional impedance model with complex expressions, a model to describe the shaping effects of dc-link dynamics is proposed, and combined with the space vector diagram to analyze the system impedance characteristics. It is found that the impedance of the VSG controlled type-IV can be capacitive below the fundamental frequency, which is inherited from its GSC impedance and the capacitive characteristics has been weakened by the influence of dc-link dynamics. Instable risk has also been found between the VSG controlled type-IV WTS and the connected weak grid, and the instability can be avoided if the capacitive characteristics of the VSG controlled type-IV WTS are weakened by reshaping its GSC impedance or by enhancing the dc-link dynamics. Experiments are also carried out as verifications. [ABSTRACT FROM AUTHOR]

Estimating effective connectivity from functional magnetic resonance imaging (fMRI) time series data has become a very hot topic in neuroinformatics and brain informatics. However, it is hard for the current methods to accurately estimate the effective connectivity due to the high noise and small sample size of fMRI data. In this paper, we propose a novel framework for estimating effective connectivity based on recurrent generative adversarial networks, called EC-RGAN. The proposed framework employs the generator that consists of a set of effective connectivity generators based on recurrent neural networks to generate the fMRI time series of each brain region, and uses the discriminator to distinguish between the joint distributions of the real and generated fMRI time series. When the model is well-trained and generated fMRI data is similar to real fMRI data, EC-RGAN outputs the effective connectivity by means of the causal parameters of the effective connectivity generators. Experimental results on both simulated and real-world fMRI time series data demonstrate the efficacy of our proposed framework. [ABSTRACT FROM AUTHOR]

Hybrid ac-dc grids can gain the benefits of both ac and dc grids. The Ac-Dc circuit analysis can be performed using sequential methods that decouple ac and dc systems or unified (simultaneous) methods that solve the ac and dc mismatch equations simultaneously. This paper introduces a unified ac–dc analysis via an improved model for the ac–dc coupling through which the ac and dc load flow analyses can be simultaneously conducted. The ac–dc coupling is modeled by an admittance building block, and thus, the dc grid is converted to an ac-equivalent circuit within the hybrid network. However, unlike past literature, state variables beyond nodal voltages and angles are avoided, leading to a simpler algorithm, and reactive power injection of the coupling mechanism, a requirement for the IEEE 1547 Std, is explicitly modeled. Furthermore, the proposed model can be applied to both voltage-source and line-commuted converters. Accordingly, the conventional ac power flow algorithms can be applied to the hybrid circuit paving the path for seamless adoption of hybrid circuits and significantly saving time and effort in programming, troubleshooting, and upgrading techniques currently used in research and industry as well as a high-level analysis tool regarding the hybrid ac-dc grid is achieved. [ABSTRACT FROM AUTHOR]

In this paper, we consider the policy evaluation problem in reinforcement learning with agents on a decentralized and directed network. In order to evaluate the quality of a fixed policy in this decentralized setting, one option is for agents to run decentralized temporal-difference (TD) collaboratively. To account for the practical scenarios where the state and action spaces are large and malicious attacks emerge, we focus on the decentralized TD learning with linear function approximation in the presence of malicious agents (often termed as Byzantine agents). We propose a trimmed mean-based Byzantine-resilient decentralized TD algorithm to perform policy evaluation in this setting. We establish the finite-time convergence rate, as well as the asymptotic learning error that depends on the number of Byzantine agents. Numerical experiments corroborate the robustness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Isothermal natural gas flow model with constant gas temperature has been widely used in conventional coordinated operations of integrated electricity and natural gas systems (IEGS). However, as a crucial state variable in IEGS, gas temperature varies significantly among nodes in a natural gas system, which can be calculated along with nodal pressures and mass flow rates. This paper proposes a novel non-isothermal optimal power and gas flow (OPGF) model that avoids the isothermal assumptions involved in traditional natural gas network model and improves the accuracy significantly. In the proposed model, partial differential terms with minimal weights are neglected based on the quantitative analysis of the energy conservation equation to further simplify the energy conservation equation. A non-isothermal model of natural gas networks is developed by introducing the finite difference method and laws of thermodynamics to incorporate the gas temperature change into the coordinated operation of IEGS. A start point initialization scheme is developed based on the Newton-Raphson algorithm to accelerate the interior point method solution convergence and improve its solution quality. Numerical experiments presented for two test systems validate the effectiveness of the proposed OPGF model and solution methodology. [ABSTRACT FROM AUTHOR]

Bulk integrated electricity and gas systems (IEGSs) introduce complex coupling relations and induce synergistic operation challenges. The growing uncertainty arising from the renewable power generation in the IEGS further aggravates the synergistic problems. Considering the availability of historical wind power generation data, this paper adopts a two-stage sample robust optimization (SRO) model, which is equivalent to the two-stage distributionally robust optimization (DRO) model with a ${\text{type}} - \infty $ Wasserstein ambiguity set, to address the wind power penetrated unit commitment optimal energy flow (UC-OEF) problem for the IEGS. Compared to the equivalent DRO model, the two-stage SRO model can be approximately transformed into a computationally efficient form. Specifically, we employ linear decision rules to simplify the proposed UC-OEF model. Moreover, we further enhance the tractability of the simplified model by exploring its structural features and, accordingly, develop a solution method. Simulation results on two IEGSs validate the effectiveness of the proposed model and solution method. [ABSTRACT FROM AUTHOR]

Chance-constrained economic dispatch (CCED) is widely used to cope with uncertainties brought by renewable energy sources. In CCED, security of power system is guaranteed by restricting risks under permitted level. As the penetration rate of renewable energy increases rapidly, the CCED model may be infeasible because of inadequate system reserve and/or transmission congestion under certain circumstances. Therefore, the curtailment of renewable energy is indispensable to guarantee security in some scenarios for power systems with high penetration of renewable energy. To address this crucial issue, this paper proposes a novel CCED model, where generation of conventional units and curtailment strategies of renewable energy are co-optimized to minimize total operational cost and restrict operational risks. An efficient solution method is developed to schedule generation and curtailment sequentially, in which tractable optimization models are formulated for each step. Numerical tests demonstrate that the proposed model can significantly reduce the probability of emergency control of curtailment compared with conventional CCED models. Furthermore, this solution method also outperforms scenario-based method with significantly improved computational efficiency and higher-quality solution. [ABSTRACT FROM AUTHOR]

The penetration of photovoltaics (PVs) has been increasing in active distribution networks (ADN), which leads to severe voltage violation problems. PV inverters can provide fast and flexible reactive power support and are now allowed to participate in the voltage regulation process. This paper proposes a real-time combined central and local Volt/Var control (VVC) strategy to mitigate voltage violation problems while minimizing the network power loss. Based on the historical PV and load data, the load flow and optimal power flow are performed in the centralized controller (CC) to obtain multiple voltage and optimal power settings for each PV system. The local controller (LC) then generates voltage control curves with these optimal scatters. To improve the voltage control effect, a novel 3-Dimension voltage control curve is proposed considering both the measurements of node voltage and PV generation. Moreover, a data-driven deep convolution neural network is designed and trained to generate optimal local voltage control curves without prior knowledge of specific curve functions. The proposed approach is tested on the IEEE 33-bus distribution system and simulation results verify the effectiveness in voltage control compared with the optimal Q(V) and Q(P) method. [ABSTRACT FROM AUTHOR]

The disturbance propagation mechanism is crucial for the preventive, corrective, and in-extremis control of power grids. This paper proposes a novel non-uniform frame structure model for power system disturbance propagation analysis. A general state transition model of the power grid is derived from the electromechanical wave propagation process. This is further used together with the Gaussian function to derive the non-uniform heterogeneous inertial continuum model, where the non-uniform parameters of the inertia are estimated using the state transition model. The proposed non-uniform frame structure model can be integrated with the electromechanical wave equation to study the disturbance propagation process. These novel developments allow us to tackle the inertial loss and uniform homogenous assumption in existing models. Extensive comparison results carried out on both the chain grid and the IEEE 118-bus system demonstrate that the proposed model can achieve 5- and 3-times accuracy improvements of the state-of-the-art SHU-FSM and ISHU-FSM models, respectively. [ABSTRACT FROM AUTHOR]

Increasing penetration of renewable energy sources based on power electronic interfaces in traditional power systems reduces the inertia constant and damping coefficient. It also increases uncertainty and the sensitivity of the system to disturbances. The concept of the virtual synchronous generator (VSG) is used to emulate the inertia constant and damping property like a synchronous generator. It can be shown that all given VSG structures have the same dynamics as the proportional-integral-derivative (PID) controller. In this paper, the quantitative feedback theory (QFT) is used to tune the VSG parameters such that robust system stability and performance are guaranteed. Moreover, the desired disturbance attenuation is also taken into account. Through frequency response analysis and time-domain simulations, it is shown that the proposed strategy can be successfully used to solve the load-frequency control problem in islanded microgrids (MGs). In addition, the proposed QFT-based VSG is compared with another robust VSG designed by the well-known $H_\infty$ technique to illustrate its better performance against disturbances. [ABSTRACT FROM AUTHOR]

Electric power grids regularly experience uncertain fluctuations from load demands and renewables, which poses a risk of violating operational limits designed to safeguard the system. In this paper, we consider the robust AC OPF problem that minimizes the generation cost while requiring a certain level of system security in the presence of uncertainty. The robust AC OPF problem requires that the system satisfy operational limits for all uncertainty realizations within a specified uncertainty set. Guaranteeing robustness is particularly challenging due to the non-convex, nonlinear AC power flow equations, which may not always have a solution. In this work, we extend a previously developed convex restriction to a robust convex restriction, which is a convex inner approximation of the non-convex feasible region of the AC OPF problem that accounts for uncertainty in the power injections. We then use the robust convex restriction in an algorithm that obtains robust solutions to AC OPF problems by solving a sequence of convex optimization problems. We demonstrate our algorithm and its ability to control robustness versus operating cost trade-offs using PGLib test cases. [ABSTRACT FROM AUTHOR]

Time delays are inevitable in load frequency control (LFC) of the power system, especially in a deregulated system where open communication networks are more favorable than the dedicated ones. However, extensive delays may affect the stability of a system. In this paper, an exact frequency-domain method for calculating the delay margin of LFC systems is presented, which is likely to be used to assess a system's stability caused by time-delays and guide the controller design. Firstly, a dynamic model of load frequency control systems is established, described by delay differential and algebraic equations (DDAEs). The Rekasius substitution is then employed to eliminate the transcendental terms in the characteristic equation without making any approximation. Afterward, an eigenvalue perturbation theory is introduced to transform the problem of calculating the delay margin into solving a series of one-dimensional nonlinear equations. Since only equivalent transforms are involved in the whole process, the delay margins obtained by the proposed method are exact. Finally, a two-area and a three-area deregulated LFC systems are applied to verify the correctness and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents an optimal transient-stability control strategy that modulates the real power injected and absorbed by distributed energy-storage devices. These devices are located at the high-voltage bus of several generators in a synchronous power system. The system is broken into areas based upon groupings of generators. The control strategy consists of two parallel feedback loops. One loop focuses on preserving the synchronism of the generator to its own area. The second loop focuses on preserving the synchronism of a given area to the other areas. Each control loop strategy is based upon local and center-of-inertia frequency measurements. The strategy is derived from two perspectives. With the first, the goal is to remove as much kinetic energy gained during a disturbance as quickly as possible before it is converted to potential energy. With the second perspective, an optimal transient control cost-function is minimized. Both perspectives result in the same strategy. The performance of the control strategy is evaluated on a four-machine power system model and on a 34-generator reduced-order model of the western North-American grid. The results show that this control approach significantly improves the transient stability of power systems. [ABSTRACT FROM AUTHOR]

In this paper, a Frequency Stability Constrained Unit Commitment (FSCUC) model is presented. The on/off status of generating units, generation levels and operating reserves are optimized to minimize the operational daily costs. The frequency stability constraints are included in the proposed FSCUC model to guarantee the safety of System Frequency Response (SFR) under sudden generation outages. A new multi-area SFR model is proposed to capture the regional dynamics of system frequency with considering the impacts of transmission network. An SFR model is developed for each electric region and then the resulted regional SFRs are coupled via a set of constraints. In order to enhance the primary SFR and keep the daily operating point at its economic schedule, Flywheel Energy Storage (FES) devices are utilized in the proposed FSCUC model. The proposed multi-area SFR model allows the optimal allocation of operating reserve and the accurate modeling of FESs in FSCUC model. The proposed FSCUC model is formulated as a Mixed Integer Linear Programming (MILP) problem and is applied over the IEEE 118-bus test system to show the accuracy of the proposed multi-region SFR and the impact of FES in frequency support. The developed MILP model is solved using CPLEX in GAMS. [ABSTRACT FROM AUTHOR]

Distributed Series Reactances are devices that dynamically increase the impedance of a line to reduce the power flow it carries. This work explores whether widely deploying these devices enhances a power system's robustness against line overload cascading failures. The presence of Distributed Series Reactances may make it less likely that equipped lines would become overloaded by contingencies elsewhere, and so their presence may arrest the propagation of line overloads through a system. However, the efficacy of these devices in this role has not been widely investigated. Likewise, there are few extant methodologies for siting dynamic reactances within the grid to mitigate the propagation of cascades. In this paper, the ability of these devices to arrest the propagation of cascading failures within power grids is investigated. First, a novel dc power flow is formulated, which models dynamic line impedances. A novel methodology is proposed for siting the devices on lines spread throughout the network. With these innovations in hand, the devices’ effects on cascade propagation are simulated using a sizeable database consisting of multiple load & generation snapshots across eight test networks. No major beneficial effect is found, even when 25% of lines are equipped. [ABSTRACT FROM AUTHOR]

With continuing advances in high-performance parallel computing platforms, parallel algorithms have become powerful tools for development of faster than real-time power system dynamic simulations. In particular, it has been demonstrated in recent years that parallel-in-time (Parareal) algorithms have the potential to achieve such an ambitious goal. The selection of a fast and reasonably accurate coarse operator of the Parareal algorithm is crucial for its effective utilization and performance. This paper examines semi-analytical solution (SAS) methods as the coarse operators of the Parareal algorithm and explores performance of the SAS methods to the standard numerical time integration methods. Two promising time-power series-based SAS methods were considered; Adomian decomposition method and Homotopy analysis method with a windowing approach for improving the convergence. Numerical performance case studies on 10-generator 39-bus system and 327-generator 2383-bus system were performed for these coarse operators over different disturbances, evaluating the number of Parareal iterations, computational time, and stability of convergence. All the coarse operators tested with different scenarios have converged to the same corresponding true solution (if they are convergent) and the SAS methods provide comparable computational speed, while having more stable convergence to the true solution in many cases. [ABSTRACT FROM AUTHOR]

This paper derives the optimal Bayesian processing of an out-of-sequence (OOS) set of measurements in continuous-time for multiple target tracking. We consider a multi-target system modelled in continuous time that is discretised at the time steps when we receive the measurements, which are distributed according to the standard point target model. All information about this system at the sampled time steps is provided by the posterior density on the set of all trajectories. This density can be computed via the continuous-discrete trajectory Poisson multi-Bernoulli mixture (TPMBM) filter. When we receive an OOS measurement, the optimal Bayesian processing performs a retrodiction step that adds trajectory information at the OOS measurement time stamp followed by an update step. After the OOS measurement update, the posterior remains in TPMBM form. We also provide a computationally lighter alternative based on a trajectory Poisson multi-Bernoulli filter. The effectiveness of the two approaches to handle OOS measurements is evaluated via simulations. [ABSTRACT FROM AUTHOR]

This paper presents a unified propagation method for dealing with both the classic Eikonal equation, where the motion direction does not affect the propagation, and the more general static Hamilton-Jacobi equations, where it does. While classic Fast Marching Method (FMM) techniques achieve the solution to the Eikonal equation with a O(M log M) (or O(M) assuming some modifications), solving the more general static Hamilton-Jacobi equation requires a higher complexity. The proposed framework maintains the O(M log M) complexity for both problems, while achieving higher accuracy than available state-of-the-art. The key idea behind the proposed method is the creation of ‘mini wave-fronts’, where the solution is interpolated to minimize the discretization error. Experimental results show how our algorithm can outperform the state-of-the-art both in precision and computational cost. [ABSTRACT FROM AUTHOR]

In this paper we study a data-supported caching policy design for wireless D2D caching networks, which is based on a dataset collected from a campus Wi-Fi network. After a well-designed preprocessing for the dataset, for the first time, we conduct a real dataset based performance evaluation for the caching policies designed based on the homogeneous Poisson Point Process (PPP) model and a clustered PPP model. We proceed to propose a novel approach for the design of the D2D caching policy. It directly models the number of D2D neighbours, instead of characterizing the locations of users as the PPP models. We show that the number of D2D neighbours can be well modeled by a discrete Gamma distribution. Given the model, we develop an iterative algorithm to optimize the D2D caching policy, and also provide a method to optimize the cache update time in order to balance the caching gain and overhead. Simulation results based on the dataset show that the proposed caching policy can achieve good performance with low cost of cache updating. [ABSTRACT FROM AUTHOR]

This paper considers the multiaccess coded caching systems formulated by Hachem et al., including a central server containing $N$ files connected to $K$ cache-less users through an error-free shared link, and $K$ cache-nodes, each equipped with a cache memory size of $M$ files. Each user has access to $L$ neighbouring cache-nodes with a cyclic wrap-around topology. The coded caching scheme proposed by Hachem et al. suffers from the case that $L$ does not divide $K$ , where the needed number of transmissions (a.k.a. load) is at most four times the load expression for the case where $L$ divides $K$. Our main contribution is to propose a novel transformation approach to smartly extend the schemes satisfying some conditions for the well known shared-link caching systems to the multiaccess caching systems. Then we can get many coded caching schemes with different subpacketizations for multiaccess coded caching system. These resulting schemes have the maximum local caching gain (i.e., the cached contents stored at any $L$ neighbouring cache-nodes are different such that the number of retrieval packets by each user from the connected cache-nodes is maximal) and the same coded caching gain as the original schemes. Applying the transformation approach to the well-known shared-link coded caching scheme proposed by Maddah-Ali and Niesen, we obtain a new multiaccess coded caching scheme that achieves the same load as the scheme of Hachem et al. but for any system parameters. Under the constraint of the cache placement used in this new multiaccess coded caching scheme, our delivery strategy is approximately optimal when $K$ is sufficiently large. Finally, we also show that the transmission load of the proposed scheme can be further reduced by compressing the multicast message. [ABSTRACT FROM AUTHOR]

We analyze the symbol error probability (SEP) of $M$ -ary pulse amplitude modulation ($M$ -PAM) receivers equipped with optimal low-resolution quantizers. We first show that the optimum detector can be reduced to a simple decision rule. Using this simplification, an exact SEP expression for quantized $M$ -PAM receivers is obtained when Nakagami- $m$ fading channel is considered. The derived expression enables the optimization of the quantizer and/or constellation under the minimum SEP criterion. Our analysis of optimal quantization for equidistant $M$ -PAM receiver reveals the existence of error floor which decays at a double exponential rate with increasing quantization bits, $b$. Moreover, by also allowing the transmitter to optimize the constellation based on the statistics of the fading channel, we prove that the error floor can be eliminated but at a lower decay exponent than the unquantized case. Characterization of this decay exponent is provided in this paper. We also expose the outage performance limitations of SEP-optimal uniform quantizers. To be more precise, its decay exponent does not improve with $b$. Lastly, we demonstrate that the decay exponent of a quantized receiver can be complemented by receive antenna diversity techniques. [ABSTRACT FROM AUTHOR]

Nowadays, the availability of accurate vehicle position becomes more and more indispensable. The GNSS/INS (Global Navigation Satellite Systems/Inertial Navigation System) is currently the most widely-used integrated navigation scheme for land vehicles, which is capable of provide high-accuracy and continuous positioning results in the open-sky environments. However, under the GNSS-denied conditions, the existing GNSS/INS integrated system often fails to provide reliable positioning results due to various and nonlinear errors contained in the MEMS (Micro-Electro-Mechanical System) IMU (Inertial Measurement Unit) measurements. To improve the positioning accuracy during GNSS outage, deep learning has been introduced into the GNSS/INS integrated system in recent years. In this paper, we propose a residual attention network-based confidence (i.e., measurement noise covariance) estimation algorithm for non-holonomic constraint in GNSS/INS integrated navigation system, which adopts a residual attention network to dynamically estimate the noise covariance of the pseudo-observation (i.e., non-holonomic constraint) for optimal Kalman filtering (KF) fusion. To emphasize the more representative features with larger weights for accurate noise covariance estimation, we introduce an attention mechanism to automatically assign proper weights to the learned features according to their contributions. We evaluate our proposed method on three practical road datasets and compare it with other seven methods including the traditional KF, Pure INS, KF with three deep learning networks, K-means, and the Input-Delayed Neural Networks based method. Extensive experimental results demonstrate that our proposed RA-NHC bounds the errors associated with velocities and achieves reasonable accuracy improvement in position and velocity estimation. [ABSTRACT FROM AUTHOR]

Path tracking is one of the most crucial issues of autonomous vehicles, but uncertain factors including road roughness and wind gusts could cause lateral deviation and even divergence of the control system. Therefore, this paper proposes a hierarchical anti-disturbance tracking architecture based on the steer-by-wire (SBW) system to improve tracking accuracy and dynamic stability for autonomous vehicles. The proposed architecture is robust strongly against different types of disturbances in the path tracking process by means of hierarchical decoupling. Firstly, in the upper-layer path tracking module, a robust model predictive control (MPC) method with a feedback correction term calculates the expected front-wheel steering angle. Secondly, in the lower-layer SBW module, a nonlinear high gain rack force observer is proposed to compensate for the generalized rack force disturbance. Then, an improved non-singular fast terminal sliding mode auxiliary control law based on the super-twisting algorithm is presented to attenuate the norm-bounded rack disturbance effectively. Simulation and experiment results show that the proposed control architecture can improve the path tracking accuracy and has strong interference resistance and robustness against both modeled and unmodeled disturbances. [ABSTRACT FROM AUTHOR]