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The virtual synchronous generator (VSG) is the most widely used grid-forming inverter (GFMI) control technique. The VSG can provide enhanced ancillary services and improved dynamic response compared to conventional synchronous generators and grid-following inverters (GFLIs). Developing an improved understanding of VSG strategies is vital to deploy them in the appropriate context in power grids. Therefore, this paper provides a rigorous comparative performance analysis of prominent VSG strategies (e.g., ISE-Lab, synchronverter, Kawasaki Heavy Industries (KHI) model, and power synchronisation control (PSC)) under different network conditions (e.g., X/R ratios, network faults, and load types). Dynamic simulation studies have been carried out using a simplified test system to assess the performance of VSG models. Furthermore, comprehensive mathematical models of VSGs have been derived in order to verify the simulation results through a frequency domain stability analysis. Moreover, the offline simulation platform results have been validated in real-time using the IEEE-39 bus network on the OPAL-RT platform. According to the analysis, the synchronverter-based VSGs perform much better under low X/R ratios, fault conditions, and dynamic loads. Hence, they are more suitable for distribution grids and load centres with a high share of dynamic loads.

The dual wound generator brings significant advantages to integrated electric propulsion systems in ships, particularly in terms of footprint reduction and space saving. However, prior research on machines using the same pole number for each of the windings has highlighted the challenge of severe magnetic coupling effects between the two outputs when subjected to dynamically changing loads. This reduces the stability of the electric power distribution system and its controllability. This paper proposes a new design based on a wound synchronous generator that overcomes this limitation by using different pole numbers for the windings to provide independent power supplies for both ship propulsion and ship services. In this novel approach, the two sets of windings physically share the same slots within a single machine frame but are fully electromagnetically decoupled. To investigate and validate this electromagnetic decoupling, the impact of load conditions such as resistive, resistive-inductive, and rectified DC loads are modelled and experimentally evaluated in detail. The results demonstrate that the novel dual wound generator operates as a fully decoupled machine, where the load change in one winding output does not impact the other winding, regardless of the load type. This unique ability to decouple the two outputs represents a significant innovation in the development of electric propulsion systems for transportation applications. This work therefore demonstrates the significant potential of the use of dual wound generators for applications in electric ships, electric aircraft, and heavy-duty vehicles, where independent power supplies are essential for efficient and reliable operation.

Nowadays, there is a race between active and passive harmonic filters and still ambiguity persists. It is a proven fact that active harmonic filters (AHFs) are costly solutions though have proved better than passive harmonic filters. Except sizing and resonance problems, tuned passive harmonic filters (TPHFs) are proved to give economical solutions with little compromise on their performance. The accurate design of TPHFs gives a greater impact on its performance. The triple-TPHF (TTPHF) is essential to alleviate first three dominant ac side current harmonics simultaneously at the high voltage direct current (HVdc) converters and it is proved better than the single and double TPHFs. Existing equivalent methods of TTPHF design failed to give satisfactory performance under dynamic conditions. Hence, this article introduces a novel parametric method-based design of TTPHF, which will give better performance under static and dynamic loading conditions. The results also reveal that the proposed TTPHF design method will perform better than the existing methods. [ABSTRACT FROM AUTHOR]

IoT application development usually involves separate programming at the device side and server side. While separate programming style is sufficient for many simple applications, it is not suitable for many complex applications that involve complex interactions and intensive data processing. We propose EdgeProg, an edge-centric programming approach to simplify IoT application programming, motivated by the increasing popularity of edge computing. With EdgeProg, users could write application logic in a centralized manner with an augmented If-This-Then-That (IFTTT) syntax and virtual sensor mechanism. The program can be processed at the edge server, which can automatically generate the actual application code and intelligently partition the code into device code and server code, for achieving the optimal latency. EdgeProg employs dynamic linking and loading to deploy the device code on a variety of IoT devices, which do not run any application-specific codes at the start. Results show that EdgeProg achieves an average reduction of 20.96%, 27.8% and 79.41% in terms of execution latency, energy consumption, and lines of code compared with state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

A novel power amplifier (PA) with wide bandwidth and load mismatch resilience is presented based on the quasi-balanced Doherty PA (QB-DPA) architecture. By reconfiguring the parallel/series QB-DPA operation modes with the nominal/exchanged biasing alternation and control of phase dispersion, the proposed QB-DPA topology can overcome the bandwidth limitations and ensure a standard Doherty profile and high efficiency and linearity against dynamic load mismatch over the operational bandwidth. Based on the theoretical analysis, a design guidance of output matching topology on phase offset implementation is presented. As a proof of concept, a physical prototype is demonstrated targeting for 1.7–2.7-GHz bandwidth. The developed QB-DPA achieves an efficiency of 56%–78% at $\text {OP}_{\mathrm {1\,dB}}$ and 47%–71% at 6-dB output back-off (OBO) over the in-band operation with 50- $\Omega $ load. Through reconfiguration (parallel/series mode for mismatch recovery and nominal/exchanged biasing for bandwidth extension), the developed QB-DPA demonstrates significantly improved $\text {OP}_{\mathrm {1\,dB}}$ variation both at center frequency 2.1 GHz and edged-frequency 1.7 and 2.6 GHz at 2:1 voltage standing wave ratio (VSWR) over 360° phase span. In modulated measurement using 20-MHz long-term evolution (LTE) signals, $> 44.5\%$ average efficiency and $ < -30.9$ -dBc adjacent channel power ratio (ACPR) are obtained across the wide bandwidth at matched-load condition. More importantly, for VSWR 2:1 circle, the high linearity [ $ < 5.3\%$ error vector magnitude (EVM)] and average efficiency ($> 38.1\%$) can be experimentally maintained through reconfigurations. [ABSTRACT FROM AUTHOR]

With the power system operating close to its stability margin, the increased penetration of renewable resources and loads with diverse characteristics, appropriate stability studies, and control decisions have become crucial. Due to the importance of accurate representation of aggregate loads in such studies, research interests for load modeling have increased. This paper puts forward a novel measurement-based load modeling approach that adapts itself based on the complex dynamics exhibited by the installed aggregate loads. The proposed approach primarily utilizes the collected measurements to gain insight regarding the dynamic trend in the measurements and subsequently determines the optimal order of an equivalent system or load model capable of effectively representing the aggregate load dynamics. An advanced signal pre-processing technique is employed, which effectively suppresses the noise and also preserves the transients present in the measurements. Afterward, an adaptive dynamic load model (ADLM) accurately represents the installed aggregate load. Lastly, the Refined Instrumental Variable (RIV) approach estimates the equivalent dynamic load model parameters. The results on a 2 bus and the IEEE 118 bus networks in DIgSILENT Powerfactory and a 7 bus network in Real-Time Digital Simulator (RTDS) reveal the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

Time-of-use (TOU) is an effective price-based demand response strategy. A reasonable design of TOU strategy can effectively reduce the peak-valley difference, and then produce a lot of benefits (such as delaying power grid investment, reducing interruption cost, and improving reliability). However, changing peak-valley period has a great influence on the peak-valley difference and power supply reliability of power system. Therefore, this paper aims to investigate the optimal modification of peak-valley period considering reliability loss under multiple TOU schemes. Firstly, this paper presents a clustering model and algorithm of optimal load curve based on a minimum error iteration method. Secondly, an optimal modification of peak-valley period based on a dynamic load point method is proposed, and the traditional peak-valley difference is replaced by the global peak-valley difference to calculate the objective function. Thirdly, this paper establishes a load–reliability relation fitting model based on the back propagation neural network. Finally, the effectiveness and correctness of the proposed method are investigated by the Roy Billinton test system and reliability test system. [ABSTRACT FROM AUTHOR]

High voltage DC transport at long distances represents an opportunity for wider use of superconductors. In particular, the second generation of high temperature superconductor tapes produced in form of coated conductors (CC) offers a unique solution for protecting a high-capacity connection against fault currents. In the resistive superconducting fault current limiter (R-SFCL), the CC tape would emerge as a substantial resistance in case of overcoming its critical current, Ic. Non-uniformity of Ic along the CC length is a common issue requiring attention. Because of highly nonlinear current/voltage dependence, the spot with critical current Icmin < Ic could transform into the hot spot with rapid rise of local temperature. Due to its small dimension, it would not create an observable voltage at the device terminals, thus may escape attention of a quench detection system. We have investigated the mechanism of hot spot creation at the DC currents between Icmin and Ic, and the analytical formulas have been derived predicting the limits of stable operation. Now we extend the analysis to the case of the limitation event, when for a fraction of second the current exceeds also the Ic. It is desirable that the temperature rise happens along all the conductor length, leading to a quick reduction of transported DC. Numerical modelling has been utilized to analyze such an event, and a simplified analytical model has been developed to predict the range of currents causing the formation of hot spots. [ABSTRACT FROM AUTHOR]

This article addresses the hierarchical resilient event triggered sampled-data security control and valve opening management problem for networked hysteretic leaf spring hydro-suspension with asymmetric actuator under false injected deception attack. For the derived Takagi–Sugeno (T–S) fuzzy model employed to tackle hysteresis nonlinearity, a new full-order dynamic output feedback top control with improved error and threshold functions for resilient event triggered mechanism is proposed to generate the target force so as to suppress the body and tire vibration under limited suspension chatter space. For the asymmetric cylinder hydraulic actuator over actuated by multiple servo valves, optimal servo valve openings are dynamic regulated to track the target force with weight adaptive nonlinear model predictive lower control. Benefiting from saved communication resource while more sparsely generating piecewise target force, as well as precise regulation by reasonably allocating over actuated valve openings to produce required force, the obtained results indicating more comfortable ride performance and less tire dynamic loads within smaller suspension chatter space favorably demonstrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This article describes the design method for an electrical machine for a free-piston linear generator. As with other applications for linear machines, defining a steady-state operating point as the basis for the design proved infeasible. To overcome the challenge of optimizing for an alternating motion cycle with accelerations and dynamic load forces, a previously established design methodology was implemented. In addition to the experimental validation of the optimization approach, each research step was presented, beginning with the preliminary choices for the machine topology. This was followed by the optimization of the linear machine and lastly the measurements of its characteristics for comparison with the simulation. A control strategy was determined and a machine prototype constructed that achieved the desired operating cycle, matching the simulated behavior remarkably. [ABSTRACT FROM AUTHOR]

How to enhance the shock wave (SW) generated by underwater electrical wire explosion (UEWE) is one of the core problems in dynamic high-pressure loading. In this article, numerical simulations were carried out using ANSYS/AUTODYN to visualize the convergence process of SWs and analyze the parametric influences on converging waves. Unlike the assumption regarding exploding wire as typical explosives, we assumed that the formation of SW originates from the instantaneous expansion of high-temperature metal gas/plasma. In order to validate the effectiveness of the simulation tool, numerical simulation was first conducted at experimental conditions in the literature, and the obtained simulation results exhibit good consistency. Then, cylindrical wire arrays and cylindrical split wire arrays (whose total cross section of all wires is constant) were studied at a fixed specific internal energy, simulation results show that: 1) the converging wave produced by cylindrical split wire array has smaller pressure amplitude than cylindrical wire array, but consumes much less energy and 2) the convergence effect can make up the shortage of rapid decay of SW induced by thin wire when the wire number is over 8. Besides, shrinking the wire array radius is a better way for enhancing the converging wave compared with pouring more energy into exploding wire. This article indicates that the numerical approach presented in this article can be used to rapidly assess the characteristics of converging wave for existing or when developing new wire array configurations. [ABSTRACT FROM AUTHOR]

The effect of reduction in the terminal voltage of a grid-tied inverter together with minimization in total harmonic distortion (THD) of terminal voltage and current, in the presence of dead-band in the switching remains always challenging for the researchers. With high switching frequency, this issue increases by many folds. The grid-tied inverter used for harmonic compensation acts as a shunt active power filter (SAPF). The implementation of the dead-band elimination technique is based on output current polarity detection, suffers from multiple zero-crossing due to the generation of high frequency switching harmonics during SAPF operation. This paper deals with a dead band elimination methodology together with harmonic compensation using SAPF under non-linear and unbalanced loading conditions. Here, SAPF uses a dual fundamental component extraction (DFCE) scheme with modified complex coefficient filter (MCCF) to extract fundamental components for reference current generation to implement an indirect current control PWM scheme. MCCF extracts fundamental components even in the presence of dc offset and unbalancing at the input. For incorporating dead-band elimination in control, exact polarity detection is done separately through SAPF output current estimation using sensed load current, and modified CCF computed reference source current. Since the estimated SAPF output current contains no high-frequency switching harmonics, the dead-band elimination technique can be correctly implemented. To synchronize the zero-crossing of the estimated and actual SAPF current, an adaptive delay control is used. The proposed MCCF based control logic’s performance together with the dead-band elimination technique is validated for SAPF operating under non-linear, unbalance, and dynamic load conditions. The proposed dead-band elimination scheme based SAPF model is developed and simulated using MATLAB/ SIMULINK. The simulation results show a significant reduction in source current harmonics due to the elimination of odd harmonic injection into the system by incorporating dead-band elimination in SAPF operation. The real-time simulation of the proposed method is also validated using OPAL-RT OP4510 real-time platform. [ABSTRACT FROM AUTHOR]

Most dc power distribution architectures are organized as a typical cascaded converter system that is composed of source and load converters, and may experience a system oscillation due to the negative impedance effect of constant power loads. The load-side virtual impedance method is a possible solution to such stability problem, which however makes the dynamic response of the load converter slow, and thus increases the requirement of the filter capacitance. In this article, an auxiliary circuit that is connected to the output port of the load converter is proposed to enhance the transient performance of the power converter system, while the system can be stabilized by the virtual impedance method. The control and parameter design of the proposed auxiliary circuit is introduced. The capacitance requirement of the system for an expected transient deviation of the output voltage is significantly reduced by using the proposed auxiliary circuit. An example design is given to verify the feasibility of the proposed method with simulation analysis and experimental results. [ABSTRACT FROM AUTHOR]

In this study, the effects of aspect ratio (AR) on the magneto-rheological elastomers (MREs) in tensile–compressive loading have been investigated considering magnetic field intensity, deformation rate, and amplitude in a moderately wide range. For this purpose, first, several MREs with different ARs (0.268–0.539) have been constructed. Then, using the Instron device, a test setup has been designed to identify the behavior of MREs in different magnetic fields in tensile–compressive mode. To provide the magnetic field, six permanent magnets made of neodymium 42 have been used. The MREs have been harmonically actuated with different deformation amplitudes (8%–14%) and deformation rates (1–8 Hz). The results illustrated a moderate impact of the AR on the hysteretic response of the MREs and also on its storage modulus. Results showed that the compressive and tensile storage moduli of MREs can increase up to 39.87%, and 52.70%, respectively, by decreasing the value of AR from 0.539 to 0.268. Furthermore, the MR effects of 29.95% and 21.66% for the compressive and tensile storage moduli, respectively, have been achieved. Finally, considering field intensity and mechanical deformations, an empirical mathematical model has been suggested to predict the compressive–tensile hysteretic response of MREs in the presence of AR and validated by the experimental results. [ABSTRACT FROM AUTHOR]

In the present paper, a new analog filter is proposed to check with high accuracy the axle load and gross vehicle weight of commercial vehicles moving at normal speed without disruption of traffic flow and ensure their respect to the transport regulation. The proposed technique is based on the zero crossing detector, designed as the basis component of the new analog filter which significantly decreases the range of measured errors according to the international standard. The promising results prove the effectiveness and the reliability of the filter under study. The intended accuracy is achieved since the maximum weighting error is less than 1% for the vehicle axles whereas the gross vehicle weight is less than 0.3% for a speed range of 40-100 km/h.

Exascale computing systems will exhibit high degrees of hierarchical parallelism, with thousands of computing nodes and hundreds of cores per node. Efficiently exploiting hierarchical parallelism is challenging due to load imbalance that arises at multiple levels. OpenMP is the most widely-used standard for expressing and exploiting the ever-increasing node-level parallelism. The scheduling options in OpenMP are insufficient to address the load imbalance that arises during the execution of multithreaded applications. The limited scheduling options in OpenMP hinder research on novel scheduling techniques which require comparison with others from the literature. This work introduces LB4OMP, an open-source dynamic load balancing library that implements successful scheduling algorithms from the literature. LB4OMP is a research infrastructure designed to spur and support present and future scheduling research, for the benefit of multithreaded applications performance. Through an extensive performance analysis campaign, we assess the effectiveness and demystify the performance of all loop scheduling techniques in the library. We show that, for numerous applications-systems pairs, the scheduling techniques in LB4OMP outperform the scheduling options in OpenMP. Node-level load balancing using LB4OMP leads to reduced cross-node load imbalance and to improved MPI+OpenMP applications performance, which is critical for Exascale computing. [ABSTRACT FROM AUTHOR]

Exascale workloads are expected to incorporate data-intensive processing in close coordination with traditional physics simulations. These emerging scientific, data-analytics and machine learning applications need to access a wide variety of datastores in flat files and structured databases. Programmer productivity is greatly enhanced by mapping datastores into the application process's virtual memory space to provide a unified “in-memory” interface. Currently, memory mapping is provided by system software primarily designed for generality and reliability. However, scalability at high concurrency is a formidable challenge on exascale systems. Also, there is a need for extensibility to support new datastores potentially requiring HPC data transfer services. In this article, we present UMap, a scalable and extensible userspace service for memory-mapping datastores. Through decoupled queue management, concurrency aware adaptation, and dynamic load balancing, UMap enables application performance to scale even at high concurrency. We evaluate UMap in data-intensive applications, including sorting, graph traversal, database operations, and metagenomic analytics. Our results show that UMap as a userspace service outperforms an optimized kernel-based service across a wide range of intra-node concurrency by 1.22-1.9 ${\times}$ × . We performed two case studies to demonstrate UMap's extensibility. First, a new datastore residing in remote memory is incorporated into UMap as an application-specific plugin. Second, we present a persistent memory allocator Metall built atop UMap for unified storage/memory. [ABSTRACT FROM AUTHOR]

As the inverter-based generation replaces the conventional synchronous generators, it may also need to fill in the missing ancillary service support. One of these ancillary services is dynamic reactive power provision and voltage control. This paper analyzes optimal strategy of reactive and active fault-current support of the inverter-based generation leading to fast voltage recovery of the system. For the purpose of the analysis, new ramping active current controller able to emulate different behavior of active current injection is proposed. By optimizing its parameters for different case studies of the system, the conclusions about optimal behavior of the inverter based generation with respect to system parameters and operating conditions are drawn. It is observed that the optimal combination of active and reactive fault-current is the most sensitive to the dynamic load component penetration levels in the system. With the increasing penetration levels, the significance of active fault-current injection increases. The results show that with higher penetration levels of dynamic load component in the heavy load areas, the ramping down of the inverter-based generation active fault-current results in slower voltage recovery of the system. Following this conclusion, a recommendation on update of current European grid codes is proposed. [ABSTRACT FROM AUTHOR]

Accurate load modeling is critical for credible power system stability analysis. Because of the increasing complexity in modern system load, establishing a more comprehensive load model and performing accurate parameter estimation are the two biggest challenges in composite load modeling. In this paper, an induction motor with variable frequency drive (IM-VFD) together with the traditional ZIP+IM model is utilized to describe the dynamic characteristics of the system load. We estimate the time-varying probabilistic distributions of all states and parameters to describe their stochastic characteristics, thereby representing the real-time varying features of an actual load. The Fokker-Planck operator is applied to linearize the updated load model in tensor format. We then use tensor decomposition to reduce the computational and storage costs for calculating load model parameters. A sensitivity indicator is used to analyze the sensitivities of the estimated parameter distributions for subsequent model reduction. Simulations demonstrate that the updated load model has better performance than the traditional ZIP+IM model. [ABSTRACT FROM AUTHOR]

As multistate system (MSS) reliability models can characterize the multistate deteriorating nature of engineering systems, they have received considerable attention in the past decade. The states of a multistate system/component can be distinguished by its performance capacity, which deteriorates over time and can be restored by maintenance activities. On the other hand, the deterioration of a system/component is, oftentimes, controllable by setting a loading strategy. In this article, a dynamic load optimization problem for repairable MSSs is investigated to achieve the maximum expected cumulative performance within a finite time horizon and limited maintenance resources. The degraded components in a system are dynamically maintained to recover to their better conditions, whereas the performance rate of each component can also be dynamically specified. The resulting sequential decision problem is formulated as a Markov decision process with a continuous action space and a mixed integer discrete continuous state space. The deep deterministic policy gradient algorithm, which is a specific deep reinforcement learning algorithm in the actor−critic framework, is customized to overcome the “curse of dimensionality” and mitigate the uncountable state and action spaces. The effectiveness of the proposed method is examined by two illustrative examples, and a set of comparative studies are conducted to demonstrate the advantage of the proposed dynamic loading strategy. [ABSTRACT FROM AUTHOR]

Electrochemical mechanisms in lithium-ion batteries (LIBs) pose a significant challenge in deriving models that are highly accurate, have low computational complexity, and enable real-time state and parameter estimation. In this article, we propose a machine learning model as an important building block of a physics-based ANCF-e model that was recently proposed for LIBs. This machine learning model is used to estimate nonlinear potentials, including the open-circuit potential, electrolyte potential, and lithium-intercalation overpotential. Such an estimation is shown to result in a much smaller computational complexity and therefore can enable real-time state and parameter estimation. Three different machine learning architectures are explored, including multilayer perceptron, radial basis function (RBF)-based neural networks, and support vector machines. The training of these machine learning models is carried out using current profiles obtained with an electric vehicle model from driving cycles as inputs and ANCF-e model-based outputs. The underlying ANCF-e model is validated both through a high-fidelity numerical approach, including COMSOL and an experimental test using commercial LIBs. Both validations are carried out under both constant current discharging and dynamic load cycles. The resulting performance using these machine learning models is compared using different metrics, including estimation errors, convergence rates, training time, and computational time. The results indicate that an RBF-based neural network leads to better estimation of the underlying potentials in LIBs and that all machine learning models require a computational time that is 95% smaller than a physics-based approach for this estimation. [ABSTRACT FROM AUTHOR]

In this article, a novel vehicle sideslip angle estimation method is proposed using the Takagi–Sugeno (T–S) observer based on a piecewise affine (PWA) lateral dynamics model. Since conventional lateral dynamics models have complex structures and nonlinearities, difficulties in sideslip angle observer design and online implementation are inevitable. To address nonlinearities, the PWA and T–S fuzzy modeling approaches are applied in this article. First, a nominal PWA model is obtained using the nominal tyre load and tyre-road friction coefficient. An explicit relationship between the PWA model parameters and the tyre load, tyre-road friction coefficient is deduced based on the Dugoff tyre model. Then, a novel PWA lateral dynamics model is obtained considering a varying tyre load and tyre-road friction coefficient. Due to the residual nonlinear terms, this PWA model is further converted into a T–S fuzzy model. Finally, a switched T–S observer is designed as it is computationally simple and efficient enough for online estimation. To validate the effectiveness of the proposed approach, experiments are conducted on both low- and high-friction coefficient roads. Experimental results show that the proposed PWA modeling technique is effective and the T–S observer can estimate the sideslip angle well under both stable and unstable steering maneuvers. [ABSTRACT FROM AUTHOR]

This article presents a new control strategy merging a sliding mode control (SMC) with a linear extended state observer (LESO) to regulate the output voltage of the buck–boost power converter system affected by matched and mismatched disturbances. The SMC–LESO schema uses the input–output linearization approach and the equivalent control method to determine the boundary layer around the sliding surface. This boundary layer depends on the sliding surface and the equivalent control value, depending on the estimated variables obtained through a LESO. With this schema, the unknown matched, and mismatched disturbances are observed and compensated by an adaptation of the SMC. The proposed approach minimizes the sliding surface chattering and improves the performance against sudden static and dynamic load changes as well as voltage variations on the power supply input. An experimental comparison with traditional sliding mode control and classical proportional–integral–derivative control is performed, confirming the proposal's effectiveness. The closed-loop stability (observer-controller-plant) is guaranteed in the input-to-state stability framework. [ABSTRACT FROM AUTHOR]

Many real-time software systems, such as those commonly found in the context of multimedia, cloud computing, robotics, and real-time databases, are characterized by a dynamic workload, where applications can join and leave the system at runtime. Global schedulers can transparently support dynamic workload without requiring any off-line task-allocation phase, thus providing advantages to the system designer. Nevertheless, such schedulers exhibit poor worst-case performance when compared to semi-partitioned schedulers, which instead can achieve near-optimal schedulability performance when used in conjunction with smart task splitting and partitioning techniques, and they are also lighter in terms of run-time overhead. This article proposes an approach to efficiently schedule dynamic real-time workloads on multiprocessor systems by means of semi-partitioned scheduling. A linear-time approximation scheme for the C=D splitting algorithm under partitioned EDF scheduling is proposed. Then, a load-balancing algorithm is presented to admit new real-time workloads with a limited number of re-allocations. The article finally reports on a large-scale experimental study showing that (i) the linear-time approximation is characterized by a very limited utilization loss compared with the corresponding exact approach (that has a much higher complexity), and that (ii) the whole approach allows achieving considerable improvements with respect to global and partitioned EDF scheduling. [ABSTRACT FROM AUTHOR]

This article proposes a real-time control strategy for induction motor drives, harmonizing accurate torque, and flux tracking with energy efficiency. Common problems related to lengthy control horizons and the associated computational burden are dealt with by introducing a value function approximation in the model-predictive structure to quantify the impact of instantaneous decisions on future states. An augmented model of the drive is introduced to determine this value function approximation offline. The resulting optimization problem is implemented in a real-time environment and its effectiveness is established on an experimental setup for both steady state and dynamic load conditions. Experiments show that the proposed approach outperforms default model-based methods by up to 89.7%, thus making it a promising real-time optimal control strategy in the domain of electric drives. [ABSTRACT FROM AUTHOR]

This article deals with the control and implementation of a multiobjective reconfigurable microgrid with electric vehicles (EVs), dynamic loads [induction motor (IM)], and home loads. This microgrid is reconfigurable in an islanded and the grid-connected modes with a robust synchronization control. For EVs, the microgrid provides the charging facility, and for home and dynamic loads, the microgrid balances and regulates the point of common coupling (PCC) voltage and frequency in an islanded mode. Usually, in an islanded mode of microgrid, the PCC voltage and frequency are regulated under the sudden start of an IM load, EV charging, and unbalanced nonlinear loads condition. An improved-diffusion proportionate affine projection sign-based control algorithm is used for voltage source converter to regulate the voltage and frequency of the islanded mode of microgrid and also improving power quality. Moreover, the robust grid synchronization control is also introduced in the microgrid control strategy to connect it to the grid/diesel generator set with a seamless mode of transition. The performance of the microgrid is demonstrated through simulated results obtained in the MATLAB/Simulink, and test results are taken from the experimental prototype, which is realized in the laboratory. [ABSTRACT FROM AUTHOR]

The approach of ambient signals-based load modeling (ASLM) was recently proposed to better track the time-varying changes of load models. To improve computation efficiency and model structure complexity, a hierarchical framework for ASLM is proposed in this paper. Through this framework, the hidden quasi-convexity of the load modeling problem is explored for the first time. This allows more complicated static load model structures and gradient or Hessian-based optimization algorithms to be used. In the upper level, the identification of dynamic load parameters is regarded as an optimization problem. In the lower level, the optimal static load parameters are obtained through linear regression for a given group of dynamic load parameters. Afterward, the regression residuals are regarded as the objective function (OF) of the upper level optimization problem. The proposed method is validated by the case study results on the Guangdong Power Grid. The results show that the OF is mostly quasi-convex after the transformation of the induction motor model, which provides the basis for the application of gradient or Hessian-based optimization algorithms. The case study results also validate that the proposed approach has better computation efficiency and model structure complexity compared with the previous ASLM approaches. [ABSTRACT FROM AUTHOR]

Over the past decades, the increasing penetration of distributed energy resources (DERs) has dramatically changed the power load composition in the distribution networks. The traditional static and dynamic load models can hardly capture the dynamic behavior of modern loads especially for fault-induced delayed voltage recovery (FIDVR) events. Thus, a more comprehensive composite load model with combination of static load, different types of induction motors, single-phase A/C motor, electronic load and DERs has been proposed by Western Electricity Coordinating Council (WECC). However, due to the large number of parameters and model complexity, the WECC composite load model (WECC CMLD) raises new challenges to power system studies. To overcome these challenges, in this paper, a cutting-edge parameter reduction (PR) approach for WECC CMLD based on active subspace method (ASM) is proposed. Firstly, the WECC CMLD is parameterized in a discrete-time manner for the application of the proposed method. Then, parameter sensitivities are calculated by discovering the active subspace, which is a lower-dimensional linear subspace of the parameter space of WECC CMLD in which the dynamic response is most sensitive. The interdependency among parameters can be taken into consideration by our approach. Finally, the numerical experiments validate the effectiveness and advantages of the proposed approach for WECC CMLD model. [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]

Real-time thermal capacity estimation is not only part of prognostics and health management but also determines the dynamic loading capability of the traction transformer. The hot-spot temperature (HST) is the vital parameter for real-time thermal capacity estimation. In high-speed railway, the unbalanced loads of the two phases of the traction transformer cause unbalanced winding losses and therefore affect the top-oil temperature and further influence the HST in each phase. In order to explore the dynamic thermal performance of the transformer under unbalanced load (current), a thermal model for calculating the HST was proposed incorporating thermal interaction between two power supply phases. This model treats the winding loss of each phase independently, considering the temperature dependence of winding ohmic losses and eddy current losses. A thermal circuit topology is presented with independent phase windings sharing the same top-oil temperature, where an improved heat transfer correlation is used to account for the nonlinear thermal convection. The proposed model is verified by the factory temperature rise tests and field operation data for the same batch of transformers. [ABSTRACT FROM AUTHOR]

In this article, we introduce an adaptive strictly negative-imaginary (SNI) autopilot for a low-cost quadrotor aerial vehicle, specifically designed to achieve high precision hovering and perform accurate trajectory tracking under time-varying dynamic load (i.e., displacement, velocity, and acceleration). Leveraging the learning ability of an artificial neural network, our adaptive SNI controller is robustly designed to overcome uncertainties in flight environments such as variations in the centre-of-gravity, modeling errors, and unpredictable wind gusts. The efficacy of the proposed adaptive control system is investigated under extensive flight tests in addition to numerous computer simulations and rigorous comparison with other control techniques, namely, fixed-gain SNI, fuzzy-SNI, and conventional PID controllers. We also conduct a stability analysis of the proposed control system using the SNI theorem. [ABSTRACT FROM AUTHOR]

Underwater acoustic sensor networks (UW-ASNs) have received increasing attention in the civil and military fields. However, due to the unique features of the underwater environment, designing a suitable media access control (MAC) protocol for UW-ASNs is an immense challenge. While orthogonal frequency division multiple access (OFDMA) is a multiple access technology based on orthogonal frequency division multiplexing (OFDM), allocating different subchannels to different users for parallel transmission. In this paper, we propose a traffic load-aware OFDMA-based MAC protocol for UW-ASNs, called TLAO-MAC, that can suit the operational requirements of distributed underwater sensor networks. It uses the exchange of control packets to collect data transmission requests and update the channel resource list. Neighboring nodes rely on receiving nodes to conduct channel negotiation and resource allocation in a distributed manner. In addition, we define the channel busyness index to sense the dynamic traffic load in distributed networks. The proposed TLAO-MAC includes two key schemes: an adaptive channel grouping algorithm based on channel busyness, and a distributed subcarrier and power allocation algorithm. By adaptively adjusting the channel grouping in consideration of the dynamics of the traffic load, TLAO-MAC allows simultaneous transmission between neighboring nodes and avoids conflict in the data channel. Under the premise of meeting the transmission rate requirement of the sender, the transmission power is saved to the greatest extent. The simulation results show that TLAO-MAC can improve network goodput and reduce end-to-end delay, showing better adaptability in distributed networks. [ABSTRACT FROM AUTHOR]

Cascaded connection of power converters is a dominant connection form in DC microgrids. In such systems, despite the possible instability caused by the impedance interactions between the individually designed converters, tightly regulated load converters acting as constant power loads (CPLs) tend to destabilize the system owing to their negative resistance characteristics. Hence, this paper proposes a new virtual series RC damper in parallel with the source-side converter's capacitor without compromising the load's dynamic performance. Using this design-oriented active damping method, which utilizes a simple control structure with a more straightforward tuning of the control parameter, the stability and performance of the system are guaranteed. The feasibility and robustness of the suggested active stabilization idea against unanticipated variations in input voltage amplitude, and CPL power rating (load changes) as well as step changes in output voltage reference, are also authenticated. The control and operation principles, as well as the circuit physical meaning realized by the presented technique for three cascaded systems comprising the basic DC/DC converters feeding CPLs, are theoretically analyzed. Simulation and experimental results are provided to validate the effectiveness of the proposed active stabilizer. [ABSTRACT FROM AUTHOR]

This paper presents a new structure of Permanent Magnet Flux-Switching Linear Motor (PM-FSLM) with a simple low weight modular primary and acceptable thrust ripple production. A flexible Magnetic Equivalent Circuit (MEC) is applied for modeling the proposed machine, which is capable to analyze the performance of different structures of PM-FSLMs. The saturation and end-effect phenomena are considered by a nonlinear permeability function and virtual zones at both ends of the machine, respectively. The machine operation under dynamic load is also investigated and its specifications are obtained. The proposed PM-FSLM has more power capability, lower current un-symmetry, and simpler mover structure compared to other ones, which can be mentioned as its benefits. Finally, the results of the proposed method are validated by the Finite Element Method (FEM) to show the effectiveness of the proposed MEC technique in terms of accuracy and processing time. The introduced linear machine and the proposed analysis method with adjustable accuracy are the paper novelties, which are presented in this work for the first time. [ABSTRACT FROM AUTHOR]

Routing is a very complex process in the field programmable gate array (FPGA) CAD flow. The increase of both FPGA size and design complexity leads to a long routing time hindering the productivity. In this article, we propose a more effective parallel router that combines static and dynamic load balance in parallel routing for FPGAs. First, we explore hierarchical region partitioning to assign routing tasks to different cores for static load balance. Then, we coordinate message propagation and task migration at runtime so that load balance between cores can be dynamically maintained in parallel routing. Finally, we combine static and dynamic load balance in the parallel routing for a higher degree of parallelism. Our parallel router performs on the multicore distributed-memory systems and the communication between cores is through message passing interface messages. We demonstrate the effectiveness of our parallel router using large-scale Titan designs. On average, our parallel router can scale up to 32 cores to achieve about $17\times $ speedup with slight loss of quality, compared with the latest VTR 8 router. [ABSTRACT FROM AUTHOR]

Applications based on the compute-in-the-network (COIN) paradigm require flexible network telemetry data to drive effective allocation decisions. Telemetry systems collect such data based on queries specifying the precise traffic metrics or features required. Recent advances in programmable switch hardware have led to highly efficient methods to compute query results using in-network resources. However, current approaches fail to meet the simultaneous requirements of dynamic traffic loads, diverse query types, and query dynamics. In this work, we argue that telemetry systems should be cast as active runtime schedulers rather than static data sources. COIN-based applications can then dynamically submit telemetry queries on the fly and react to their results in a closed-loop fashion – enabling a new generation of telemetry-driven reactive applications. As a first step toward this vision, we present a single-switch telemetry operation scheduling method. Our empirical evaluation demonstrates that such a method can reduce overhead by an order of magnitude compared to worst case allocations. This initial exploration opens the door to a multi-tier scheduling framework combining switch hardware with software-based compute platforms to meet the telemetry demands of future COIN-based applications. [ABSTRACT FROM AUTHOR]

In this paper, we propose a dynamic load balancing scheme, EdgeSafe, for provisioning Safety-as-a-Service (Safe-aaS) (Roy et al., 2018). Typically, in a Safe-aaS infrastructure, the sensor nodes are either static or mobile in nature. With the variation in the geographical location of the vehicles, the sensor nodes attached to them attain mobility. Consequently, the distance between the mobile sensor node and the edge nodes present within their vicinity changes. As the data is time-critical, it is necessary to be primarily processed at the edge nodes. Considering road transportation as the application scenario of Safe-aaS, we perform load balancing in two stages. In the first stage, we calculate the preferred capacity ratio of the edge nodes present within the communication range of the sensor nodes. We apply Markowitz Portfolio Selection Theory in the second stage to select the appropriate edge node. The profit return and risk incurred in their selection is calculated to design the portfolio of the edge nodes. Thereafter, the utility of each edge node is computed. We formulate an optimization function to obtain the minimum value of the utility of the edge nodes. Extensive simulation results show that the proposed scheme, EdgeSafe, is capable of improving the data rate by 41.37%, 35.64%, and 21.05% respectively, compared to the existing schemes, $HO$ (Park et al., 2018), $MLB$ (Lobinger et al., 2010), and Honeybee (Fernando et al., 2019). [ABSTRACT FROM AUTHOR]

This article presents on-chip power delivery hardware comprised of nine event-driven (ED) digital low-dropout voltage regulators (LDOs) for a large digital load. The goal is to address the performance degradations in an LDO’s accuracy and dynamic load regulation in the presence of parasitics in the power grid of a load. In particular, we investigate the effects of power grid resistance (RG), which becomes worse with the size of a digital load and technology scaling. Two critical problems that we address are: 1) the IR drop and 2) the dynamic voltage droop problems. Employing multiple LDOs across the power grid improves the IR drop for mainly better voltage sensing. To tackle the voltage droop problem, we distribute LDOs with ED control such that the LDO closest to a localized droop can instantly correct it. To further improve the feedback control latency, we also enhance each LDO with a novel domino sampling and regulation technique. We prototype the on-chip power delivery system consisting of 3 × 3 digital LDOs in a 65-nm CMOS. We also devise the framework to analyze the stability of the multi-LDO system across RG values. Measurements show that at 0.5-V (1 V) input, the single LDO exhibits 49.8-mV (94.1 mV) voltage droop for a load current change of 4.04 mA/0.1 ns (13.8 mA/0.2 ns) with a 0.1-nF integrated output capacitor. Also, the nine-LDO system achieves a current density of 248.8 mA/mm2 (1.118.6 A/mm2) at 0.5-V (1 V) input voltage. [ABSTRACT FROM AUTHOR]

Medium-voltage distributed generation (DG) units can be subjected to a high penetration level of dynamic loads, such as induction motor (IM) loads. The highly nonlinear IM dynamics that couple active power, reactive power, voltage, and supply frequency dynamics can affect the stability of MV grid-connected converter (GCC)-based DG units. However, detailed dynamic analysis and, more importantly, stabilization approaches of GCC-based DG units with IM loads when subjected to the grid faults, are not reported in the current literature. In addition, the literature lacks a thorough study on the effect of the grid strength on the low-voltage ride-through (LVRT) performance of such practical systems. To fill in this gap, this paper presents comprehensive integrated modeling, stability analysis, and LVRT performance improvement methods for GCC-based DG units in the presence of an IM load considering different grid strengths. A detailed multi-stage small-signal model of the complete system is obtained, and the eigenvalue analysis is conducted considering both static and dynamic load modeling. Furthermore, a sensitivity analysis is performed to investigate the effect of the length of the power line between the DG unit and the IM on the stability and LVRT performance of the entire system. Finally, the LVRT performance of the DG unit under an unbalanced grid fault is investigated using three different reference current generation strategies to determine the best strategy to provide a stable and efficient LVRT performance under strong and weak grid conditions. The time-domain simulation and experimental results are also presented to validate the effectiveness of the proposed methods.

This article focuses on the estimation of static/ dynamic tire load and vehicle parameters using intelligent tires and vehicle dynamics. This study is conducted to improve and ensure the performance of advanced vehicle control using accurate vehicle and tire states. The contact angle between tire and road surface is calculated by an intelligent tire and is used for tire load estimation. The tire load estimation results are validated by the flexible ring tire model. For a fast sampling rate and high robustness, a new estimation algorithm, which combines intelligent tire and vehicle dynamics, is proposed in this article. Not only the tire load but also the vehicle parameters, such as total mass, center of gravity point (CG point), and center of gravity height (CG height), are estimated by the proposed estimation algorithm. The proposed estimation algorithm is verified by an indoor test using Flac trac (tire test system) and a real-time test using AutoBox III. In short, the estimation algorithm proposed in this article can estimate static/dynamic tire load and vehicle parameters with a fast sampling rate and high robustness. [ABSTRACT FROM AUTHOR]

This article develops a real-time loss minimizing control technique on induction machines for dynamic load profiles. Steady-state loss minimization has been well addressed. However, when the steady-state optimal control is applied to a highly dynamic load profile, more losses are induced during transients due to the slow rotor flux dynamics. Several heuristic methods have been developed for real-time loss reduction, but they are not designed for minimum losses. Loss-minimizing flux trajectories have been generated by dynamic programming but require prior information of load profiles. In this article, a real-time loss minimizing control technique is developed for applications without prior information of load profiles. It resembles the loss-minimizing stator flux trajectory generated by a modified dynamic programming method, which generates the best practical solution for unknown load profiles. Both simulation and experimental results demonstrate the energy saving capability of the proposed method. Significant energy savings have been demonstrated on traction applications. [ABSTRACT FROM AUTHOR]

This article proposes an enhanced control strategy for a microgrid consisting of multiple rooftop solar photovoltaic sources. These sources are of different power ratings and intermittent in nature. The microgrid is flexible to function either in islanded mode or in grid connected mode. It affects power management and hampers the power quality in microgrid. The proposed control scheme enhances the power quality of the microgrid by providing reactive power compensation to local loads. Thus, it reduces the burden on utility grid. The proposed control technique establishes a priority-based policy for reactive and active power compensation under local demand variance. A smooth and automated transition of microgrid between islanded and grid connected modes is achieved. This seamless transition of the system between two modes avoids the transient in the system. In islanded mode, the proposed control scheme ensures improved voltage regulation under dynamic load demand. It also ensures a minimum burden on the voltage source. Also, the proposed control scheme maintains the power factor of the system near to unity. The system performance is validated experimentally under a number of various operating conditions such as dynamic load variation, grid condition, automated transition, intermittent power generation in real time simulator. [ABSTRACT FROM AUTHOR]

Fuel cells (FCs) are an alternative source of energy whose by-products are heat, vapor, and water. For medium-power and standalone operation, an FC is integrated with a boost converter, as the required voltage level is higher than the supply. Control of such a converter with a slow dynamic source requires a fast-acting controller, since the demand executed by the controller affects the action taken by the hydrogen valve in FCs. In this article, a linear–quadratic regulator (LQR) is developed to control the power converter. In practical applications, the conventional LQR produces offset in output voltage due to effective series resistance (ESR) of the output capacitor. To make the LQR dynamic with load perturbation, information of inductor reference current is required, which changes with variation in load current. To solve these two problems, two modifications in the classical LQR have been proposed to minimize the impact of ESR (m-LQR) and incorporate control action based on the reference inductor current (M-LQR). The proposed methods are compared with the conventional average current-mode control technique. The M-LQR-based scheme is found to outperform the classical m-LQR technique in terms of improved transient dynamics and reduced offset at the steady state. In addition to numerical simulations, the proposed control techniques have been validated experimentally. [ABSTRACT FROM AUTHOR]

Traditionally, the energy management objectives of a fuel cell–battery hybrid electric vehicle (FCBHEV) powertrain system is achieved by using the centralized control strategy, which suffers from poor flexibility, scalability, and reliability. What is worse, the system stability can hardly be guaranteed because of the serious interactions between the fuel cell (FC) as well as the battery converters and motor drive loads. In this article, a decentralized energy management strategy (EMS) based on a composite control scheme that combines mixed droop control and disturbance-observer-based control is proposed to achieve the dynamic load power allocation, extend the service life, improve the energy efficiency, enhance the robustness (i.e., realize the disturbance and uncertainty rejection), and guarantee the global stability of the FCBHEV powertrain system in a decentralized way simultaneously. First, the architecture of an FCBHEV powertrain system is described in detail. Then, analyses on the design and operating principle of the proposed EMS are deeply studied. Finally, a hardware-in-the-loop (HIL) real-time simulation system of a 50 kW FCBHEV powertrain system is established using the Typhoon HIL 602 device. The HIL simulation results verified the correctness of the theoretical analysis and effectiveness of the proposed EMS. [ABSTRACT FROM AUTHOR]

The SCAPE (SuperConducting Arbitrarily Polarizing Emitter) undulator is under development at the Advanced Photon Source (APS). This new undulator requires a cryostat that will be designed based on expected heat loads. For instance, the expected heating of the beam chamber by electron beam is estimated to be at a level of 182 W – much higher than in planar SCUs. This and other challenges require careful thermal analysis of the LHe-based SCAPE cryostat. A detailed thermal model of the LHe-based SCAPE cryostat has been created in ANSYS. This paper presents calculated cooling capacity and temperatures of the SCAPE cryostat for the static and dynamic heat loads. [ABSTRACT FROM AUTHOR]

The SCAPE (Superconducting Arbitrarily Polarizing Emitter) undulator is under development at the Advanced Photon Source (APS) as a part of the APS upgrade at Argonne National Laboratory. This new undulator requires a cryostat to handle the heat load on the beam chamber at a level of 182 W – much higher than in APS planar superconducting undulators. These challenges require careful thermal analysis of the SCAPE cryostat. Despite relatively large heat loads, a cryostat that does not contain any cryogen is a desirable option. Based on the experience on demo scale tests on SCAPE, a cryocooler-based cryogen-free cryostat is proposed. A detailed thermal model of such a cryostat has been created in Thermal Desktop. This paper presents the calculated heat load and temperatures profile of this cryostat under the static and dynamic heat loads [ABSTRACT FROM AUTHOR]

Dynamic thermal rating for underground cables with balanced phase currents has been extensively studied in the literature. Paradoxically, distribution feeders operate inherently unbalanced and no publications are available for unbalanced thermal rating. Because of the lack of technology, utilities operate with very conservative margins using the maximum of the three-phase currents to determine the line loading. This practice leads to the significant underutilization of underground cables. To fill the gap this paper presents a physically sound and accurate transient electro-thermal model of unbalanced three-phase distribution cables considering variations in the load and environment. Moreover, the model proposed in this paper allows harvesting the large hidden capacity of distribution systems trapped in the thermal inertia of underground cables. A convenient visual tool is developed to uncover hot spots and underutilized energy routes. This facilitates real-time network reconfiguration based on predicted load graphs and dynamic thermal conditions. The proposed model is also useful to study load growth, perhaps eliminating or deferring capital investments needed to upgrade the capacity of the existing underground feeders. The IEEE 37-bus distribution network is used as a case study. The results show that the proposed methodology has a high potential to defer investments, for instance, one could save $5M for a small system like the IEEE 37-bus distribution network which would have been necessary under current conservative practice. [ABSTRACT FROM AUTHOR]

The change in environmental conditions and dynamic loading distort the smooth and stable MPPT operation. Conventionally, boost and boost-derived converters are used for MPPT operations, which inherently display right half plane zero (RHPZ). The presence of RHPZ causes a transient undershoot and overshoot in the output voltages. A tradeoff between bandwidth and stability is another issue with such converters. In order to address these issues, a minimum-phase bipolar converter (MPBC) is proposed to facilitate the MPPT operation. The MPBC is derived by combining the Ćuk and SEPIC converters with some circuit modifications in both of them. These circuit modifications eliminate RHPZ from the proposed MPBC. Due to the minimum-phase behavior, the proposed MPBC can achieve high bandwidth with improved phase margin, which is required for the fast and stable MPPT operation. MPBC can operate at the high load current and provides wide operating ranges for the MPPT operation due to its buck and boost capabilities. The transient analysis of the proposed MPBC is carried out to compare its performance with the conventional bipolar converter. A 600-W scaled-down laboratory prototype is developed and implemented using Texas Instrument TMS320F28335 processor to validate the performance of the MPBC for photovoltaic systems. [ABSTRACT FROM AUTHOR]

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]

Online assessment of conservation voltage reduction (CVR) has great effects on the performance of CVR-based applications, especially for real-time CVR-based controls. The challenges of online CVR assessment mainly come from time-varying load composition and inevitable noise. Besides, the dynamic process resulting from motors further complicates this problem. This article proposes a micro-perturbation based load-to-voltage (LTV) process identification method to online assess the CVR effects. In particular, we construct a well-designed pseudo-random-binary-sequence voltage perturbation to excite the CVR process continually and fully. With the experimental data, the CVR factor and transfer function of LTV are estimated by the cross-correlation method, which can reflect both steady-state and dynamic CVR effects without being affected by noise. The proposed method is verified on a specific hardware-in-the-loop testbed under various cases. In addition, through the energy-saving and power smoothing applications, the impact of CVR assessment on performance of CVR-based applications is also analyzed, which further verify the validity and economic benefits of the proposed assessment method. [ABSTRACT FROM AUTHOR]