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The rapid introduction of electric vehicles (EVs) in the transportation market has initiated the concept of vehicle-to-grid (V2G) technology in smart grids. However, where V2G technology is intended to facilitate the power grid ancillary services, it could also have an adverse effect on the aging of battery packs in EVs. This is due to the instant depletion of power during the charge and discharge cycles, which could eventually impact the structural complexity and electrochemical operations in the battery pack. To address this situation, a median expectation-based regression approach is proposed for parameter estimation of vehicle batteries in V2G systems. The proposed method is built on the property of uncertainty prediction of Gaussian processes for parameter estimation while considering the cell variations as an exogenous function. First, a median expectation-based Gaussian process model is derived to predict the fused and individual cell variations of a battery pack. Second, a magnitude-squared coherence model is developed by the error matrix to detect and isolate each variation. This is obtained by extracting the cross-spectral densities for the measurements. The proposed regression-based approach is evaluated using experimental measurements collected from lithium-ion battery pack in EVs. The parametric analysis of the battery pack has been verified using D-SAT Chroma 8000ATS hardware platform. Performance evaluation shows an accurate estimation of these dynamics even in the presence of injected faults. [ABSTRACT FROM AUTHOR]

This article focuses on the implementation of peer-to-peer (P2P) energy trading and planning of a grid-connected multi-microgrid system based on an advanced optimization approach. The proposed architecture is comprised of three microgrids (MGs) with combinations of distributed energy resources (DERs), including wind turbines, photovoltaic panels, and storage batteries, to meet the load requirement. A game theory technique, Nash equilibrium, is used to structure the proposed model for multiobjective optimization, where the main objectives are used to determine the correct sizing of DERs and optimum payoff values. Due to the variability of DERs, to maintain lower energy costs, the reliability index (IR) and levelized cost of energy are the benchmarks considered for optimization. The proposed model is analyzed, and rigorous comparison is carried out for both peer-to-grid and P2P energy trading schemes, considering the Australian profiles for wind speed, solar irradiation, and residential load. The simulation model is built in MATLAB software, and the particle swarm optimization algorithm is exploited for the optimization. The results illustrate that P2P energy trading reduces the payoff value of the multiobjective function (MOF) to 36%. The robustness of MOF is validated and analyzed with different combinations of constant coefficients K1 and K2. In the end, the most economical and suitable models with DERs are proposed for each MG, and the results are verified with sensitivity analysis. [ABSTRACT FROM AUTHOR]

Data-driven condition monitoring reduces downtime of wind turbines and increases reliability. Wind turbine operation and maintenance (O&M) cost is a significant factor that calls for automated fault detection systems in wind turbines. In this manuscript, the anomaly detection problem for wind turbine gearbox is formulated based on adaptive threshold and twin support vector machine (TWSVM). In this work, SCADA data from wind farms located in the U.K. is considered with samples from twelve months before failure, and from one month before failure. Gearbox oil and bearing temperatures are used as two univariate time-series for analyzing adaptive threshold. The effectiveness of the proposed method is compared with standard classifiers like support vector machines (SVM), k-nearest neighbors (KNN), multi-layer perceptron neural network (MLPNN), and decision tree (DT). Anomaly detection of wind turbine gearbox using TWSVM and adaptive threshold results in an accurate performance, thus increasing the reliability. The missed failure and false positive rate that indicate the proposed methodology’s ability is also investigated to discriminate between false alarms, and comparison with previous studies shows superior performance. [ABSTRACT FROM AUTHOR]

Although the use of a series capacitor increases the transmission line (TL) capacity, it inverts the voltage/current and creates a sub-harmonic frequency that results in unintended operation of the protection devices, which further decreases the transient stability under fault conditions. Restoring the transient stability requires an accurate diagnosis of faults in TLs, which further requires exploration of in-depth features. This imposes challenges for the existing approaches as they demand a large amount of data. In this paper, a self-attentive weight-sharing capsule network (WSCN) is proposed to achieve robust and high classification performance while utilizing a limited amount of data. The capsule network, with the weight-sharing mechanism delivers robust performance in detecting and classifying the faults in the TL domain. Simultaneously, the self-attention layer highlights the more dominant features that make the network work upon the limited data effectively. A Western-System-Coordinating-Council WSCC 9-bus and 3-machine test model, which was modified with the series capacitor was studied to quantify the robustness of the self-attention WSCN. The results were compared with those of others networks to confirm the explicit classification ability of the proposed network. A study on real-world data obtained from power network was also conducted to validate the proposed self-attention WSCN. [ABSTRACT FROM AUTHOR]

The significant penetration of renewable energy resources and ever-rising load demand has gradually aggravated the safe operation of the interconnected power system. A generalized extended state observer and fractional-order theory based integral sliding mode control strategy is introduced in the interconnected power system to minimize the frequency deviation by controlling the governor of the generation unit. The generalized extended state observer is designed to estimate the disturbance from system uncertainty, load demand, and wind power fluctuation to improve the robustness of the interconnected power system. The fractional-order integral sliding mode control relieves the chattering of frequency deviation and tie-line power deviation. Besides, the superconducting magnetic energy storage and the wind model, as the ancillary frequency regulation devices, are implemented in the interconnected power system. The novel sliding mode controller based on generalized extended state observer is designed for the interconnected power system with the addition of the superconducting magnetic energy storage and the wind model. Stability proof and simulation comparison with the integer-order sliding mode control and other three control schemes are carried out as well. [ABSTRACT FROM AUTHOR]

This article proposes a novel technique for the detection of forced oscillation (FO) in a power system with the uncertainty in the measured signals. The impacts of communication uncertainties on measured signals are theoretically investigated based on the mathematical models developed in this article. A data recovery method is proposed and applied to reconstruct the signal under the effects of communication losses. The proposed FO detection with communication uncertainties is evaluated in the modified 14-machine Southeast Australian power system. A rigorous comparative analysis is made to validate the effectiveness of the proposed data recovery and FO detection methods. [ABSTRACT FROM AUTHOR]

This paper presents a frequency regulation approach applied to a renewable penetrated isolated power grid in the presence of a large number of Electric Vehicles (EVs). A disturbance observer is initially designed for a reduced-order model of the system to produce a supplementary frequency control signal for the aggregated EVs. The reduced order model is obtained by combining the variations in the load, wind, photovoltaic systems, and aggregated EVs in order to yield a lumped disturbance to be estimated by the proposed disturbance observer. A tube-based Model Predictive Control (MPC) is then proposed to provide efficient control signals for improving the response of the aggregated EVs. The control signals are produced so as to obtain the least value of frequency deviation error with a minimum control effort while taking a variety of operational and physical constraints into consideration. The proposed control strategy offers the capability to cope with the uncertainties caused by the external disturbances by coordinating the charging and discharging of aggregated EVs. The impact of the delay in communication links is also investigated by conducting a stability analysis to obtain the delay margin. Simulations are conducted on an isolated system to illustrate the effectiveness of the designed observer, and also to examine the advantage of the presented tube-based MPC over a conventional MPC, a fuzzy proportional-integral control, and a linear quadratic regulator control. [ABSTRACT FROM AUTHOR]

This paper proposes a robust control scheme to involve the distributed Battery Energy Storage Systems (BESSs) in Load Frequency Control (LFC) through BESS aggregators with sparse communication networks. In order to cope with the uncertainties associated with system operation, a two-layer Model Predictive Control (MPC) is developed so that more efficient control signals are provided to improve the response of BESSs to make larger contribution to the LFC. The outer layer in the proposed structure produces the command signal for the aggregator based on signals which are produced by the inner layer as well as the signal provided from the actual system. These command signals are provided so as to achieve the least value of error in Area Control Error (ACE) with a minimum control effort taking a variety of operational and physical constraints into consideration. Optimization procedures are also carried out to compute the optimal value of weighting coefficients contained in the objective functions. The capability of controller to cope with uncertainties is compared with a conventional single-layer MPC. In addition, the delay caused by propagation channels in delivering control signals to BESSs is modeled, and its impact on the performance of frequency regulation is evaluated. An intelligent fuzzy coordination control is then developed to coordinate the BESS aggregator and conventional power plants to avoid extra power injection/withdrawal by the conventional power plants in case of long delays. Case studies are conducted to illustrate the effectiveness of the proposed structure in controlling distributed BESSs with diverse energy capacities, rated powers, charging/discharging coefficients and time constants; and State of Charges (SoCs). [ABSTRACT FROM AUTHOR]

The deployment of advanced sensors has strengthened the monitoring capability of power plants. In the context of the cogeneration process, the plant cooling is performed by the cooling towers using the condensation process on exhaust steam. However, the computer networks and industrial control systems built on this sensor-based digital layer may become vulnerable to cyberattacks. This may eventually raise a concern on the performance and security of these energy utilities. To resolve this issue, an inoculated subobserver-based fusion filter is proposed. It improves the resilience against malicious attacks in combined cycle power plants with desalination units, which are usually functioning in a closed-loop environment and infected with injected attacks. A time-delay-based state representation is considered for the system. To access latency in a closed-loop environment, a subsystem-based set of subobservers are introduced. Information from each sensor is then gathered using the interacting-multiple-model-based fusion process. The stability of the system has been proved and kept in-check at two different implementation levels of the procedure using functional equivalence and Lyapunov stability criteria, respectively. Performance evaluation is then conducted on a water-level system. Results show that the proposed scheme accurately extracted the system parameters from the contaminated measurements in the presence of multiple system disturbances and cyber intervention. [ABSTRACT FROM AUTHOR]

This article examines the dynamic and transient performances of a battery energy storage system (BESS) connected with the output of a wind energy conversion system to smoothen the short-term fluctuations in the output power. A low-power experimental real-time testbed, using battery storage and representative power converters, is interfaced with a real-time digital simulator for the reduced-scale power hardware-in-the-loop simulation. Different configurations, where the energy storage system is integrated on the ac side via static synchronous compensator and directly at the dc link of the frequency converter using back–to–back converters, are examined under both constant and variable references. For each case, the resulting error in the net power flow, the operation of the battery, and the conduction losses in the power conversion stage are examined. The performances using the constant and variable reference of the storage device with full and reduced-order hardware stage of a storage element are demonstrated. The low-voltage transient performance of the BESS is also tested and the results are presented. The novel approach of the real-time low-power BESS testbed opens the door for in-lab testing of the energy storage devices for large wind or solar photovoltaic farms to save time and money. [ABSTRACT FROM AUTHOR]

Real-time power line outage detection (POD) and localization is an important monitoring task for the modern smart grid. Reliable monitoring of power lines status plays a critical role in the system-wide blackout prevention. In this paper, the main aim is to address the multiple POD problems by exploiting the compressive system identification—a time-efficient approach in a complex network analysis. A typical power network is considered as a single graph, and the mathematical formulation of the POD problem is initialized using the dc power-flow model and graph theory concepts. Next, a sparse representation-based formulation for this problem (POD-SRP) is reported and further improved and generalized in case of multiple large-scale outages. Practical and technical challenges associated with this sparse recovery problem are partially addressed by developing new SRP solvers. Furthermore, a new sparse-based mathematical formulation for POD is introduced and termed as “Binary-POD-SRP,” which specifically deals with two particular issues, namely, the high coherence and the signal dynamic outrange. Finally, the identification performance of the proposed framework is evaluated by a variety of case studies, which are modeled using IEEE standard test-beds. We specifically discuss how the inherent challenges within large-scale multiple-outages can be solved by applying these new techniques and formulations. [ABSTRACT FROM AUTHOR]

Penetration rate of grid-connected photovoltaic (PV) generation to the existing utility grid is rapidly increasing over the years. Since the power generated from PV systems fluctuates according to the weather condition, e.g., cloud passing, this can significantly disturb the stability of a weak utility grid. The integration of energy storage devices and its ramp-rate control technique are required to reduce the impact of PV systems output fluctuations and augment the stability of the utility grid. In this paper, ramp-rate control is applied to the direct connection of energy storage devices in PV generation system configuration. The direct connection of supercapacitors string and battery combination scheme is proposed to reduce the number of power converters so that the efficiency of the system is increased. In this work, the PV system output is controlled by directly controlling the energy storage system (ESS) to limit the changing rate of the PV output to a desired ramp-rate value, hence reducing the battery charge/discharge cycles and extending the expected lifetime of the ESS. The performance of the proposed direct connection scheme of the ESS and its ramp-rate control strategy is verified using a 1-kW PV system prototype. [ABSTRACT FROM AUTHOR]

This paper proposes a novel unified expandable low switch power electronic converter architecture for grid integration of direct drive variable speed wind turbine (VSWT) system using permanent magnet synchronous generator (PMSG). The proposed unified expandable power converter can interface two or more bidirectional output ports, such as wind generators, energy storages, and grid. The size of the power converter is compact because of fewer number of power electronic switches and protection devices, and its architecture is easily expandable to accommodate more outputs, i.e., in this case, the wind turbines. A generalized sequential space-vector modulation technique is developed based on the operational principle of the proposed converter to control the outputs autonomously in order to track the maximum power point for individual VSWTs-driven PMSGs. It is expected that the proposed approach will reduce the cost of power electronic converters in a wind farm, compared to both ac- and dc-link-based topologies, which are available for the moment. [ABSTRACT FROM AUTHOR]

Monitoring and control of electrical power grids are highly reliant on the accuracy of the digital measurements. These digital measurements reflect the precision of the installed sensors, which are vulnerable to the injection of unknown parameters in the form of device malfunction and cyberattacks. This may question the operational security and reliability of many cyberphysical infrastructure such as smart grid. To resolve this issue, a multisensor temporal prediction based wide-area control scheme is proposed in this paper. The feasibility of the designed scheme is verified in an advanced synchrophasor measurements based wide-area monitoring and control system (WAMCS). This WAMCS adopts a flexible ac transmission system device (the primary controller) for controlling the smart grid's voltage profile. The algorithm is validated in a real-time environment with an innovative software-in-the-loop testing setup. The performance of the proposed technique in the presence of false-data-injection attacks shows promising results. [ABSTRACT FROM AUTHOR]

This paper comprehensively analyzes the stability of a grid-interfacing inverter with the LCL -filter in the discrete domain, where the LCL-filter, along with the controller, is modeled in a polar coordinate. System open-loop and closed-loop poles are analytically studied and expressed in the z -domain. Through the poles movement and distribution analysis, the relationship between system stability and the ratio of resonance frequency over sampling frequency is mathematically revealed and calculated as well as the system control gain limit. Moreover, this paper demonstrates that a grid-voltage feedforward regulator would significantly alter the inverter stability in a weak power system. By means of Jury stability criterion, the stability status under different filter resonance frequency is given. The selection of resonance frequency and filter parameters makes a considerable difference on system behavior. Finally, to improve the robustness against grid inductance variation, a conservative design recommendation of filter parameters and control gain is given. Through the tests on a laboratory-scale prototype, the theoretical analysis is validated by experimental results. [ABSTRACT FROM AUTHOR]

A proportional–integral (PI) controller is the most frequently used control technique for adjustable speed-motor drives. The main advantage of a PI controller is its ability to ensure zero steady-state error under low-frequency disturbances and model uncertainties as long as the closed-loop system is stable. However, the transient performances, under a PI regulator, are highly dependent on the machine parameters, the external disturbances, and the input constraints. This brief proposes the design process of a novel PI speed controller that is capable of preserving almost the nominal transient performance under the parameter variation and external disturbances such as the load torque. The controller also suppresses the effect of input saturation that may occur because of the armature current limitation. Simulation and experimental tests are carried out to verify the validity of the proposed design process. The results revealed that the proposed PI controller is effective regarding nominal performance recovery and input constraints handling. [ABSTRACT FROM AUTHOR]

This paper discusses the impact of small dc capacitance in a motor drive using a floating capacitor H-bridge topology. The proposed topology is intended for applications where variable frequency control is not required. Special attention is paid on investigating the second-order dc capacitor voltage ripples, whose influence on the induction motor as well as on the motor drive itself is of importance. This issue is addressed in this paper through rigorous mathematical formulations. It is found that by inverting the second-order dc ripple voltage using the conventional SVPWM, no harmful harmonics will be generated in the motor line voltage. This demonstrates the possibility of drastically reducing the dc capacitance of the proposed system. Induction motor as well as H-bridge performance with respect to different dc capacitance values is demonstrated by experiments, which lays the foundation for cost reduction and reliability enhancement of the proposed system. [ABSTRACT FROM PUBLISHER]

This paper addresses the time-delay effects of the wide-area monitoring and control systems (WAMCS) in smart power grids which may critically impact system stability. The main purpose is to conduct a detailed delay analysis of the WAMCS in case of grid contingences. This analysis is performed via an advanced WAMCS testbed where a flexible ac transmission system (FACTS) device is utilized and controlled via a wide-area controller (WAC). Phasor measurements units (PMUs) are adopted to collect the real-time measurements for the WAC. The testbed results from an interface of four main segments known as the WAC; the actual FACTS device, the local area controller, and the power grid system along with the PMUs are simulated via a real-time digital simulator. To mimic the real case scenario, both hardware-in-the-loop and software-in-the-loop schemes are adopted in the experimental testbed, considering time-delay effects. The results obtained clarify the effect of delay in WAMCS in case of smart grid contingences. [ABSTRACT FROM PUBLISHER]

This paper presents a robust continuous-time model predictive direct power control for doubly fed induction generator (DFIG). The proposed approach uses Taylor series expansion to predict the stator current in the synchronous reference frame over a finite time horizon. The predicted stator current is directly used to compute the required rotor voltage in order to minimize the difference between the actual stator currents and their references over the predictive time. However, as the proposed strategy is sensitive to parameter variations and external disturbances, a disturbance observer is embedded into the control loop to remove the steady-state error of the stator current. It turns out that the steady-state and the transient performances can be identified by simple design parameters. In this paper, the reference of the stator current is directly calculated from the desired stator active and reactive powers without encompassing the parameters of the machine itself. Hence, no extra power control loop is required in the control structure to ensure smooth operation of the DFIG. The feasibility of the proposed strategy is verified by the experimental results of the grid-connected DFIG and satisfactory performances are obtained. [ABSTRACT FROM PUBLISHER]

This paper presents the design, implementation, and performance testing of a nonlinear proportional-integral (PI) predictive controller for a grid-tied inverter used in photovoltaic systems. A conventional cascade structure is adopted to design the proposed controller, where the outer loop is used to regulate the dc-link voltage, and the inner loop is designed as a current controller for adjusting the active and reactive powers injected into the grid. For each loop, the controller is derived based on combining a continuous-time nonlinear model predictive control and nonlinear disturbance observer techniques. It turns out that the composite controller reduces to a nonlinear PI controller with a predictive term that plays an important role in improving tracking performance. The salient feature of the proposed approach is its ability to approximately preserve the nominal tracking performance during the startup phase. Both simulation and experimental results are provided to demonstrate the effectiveness of the proposed approach in terms of nominal performance recovery, disturbance rejection, and current control. [ABSTRACT FROM AUTHOR]