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This paper contains a control scheme for power sharing in islanded microgrids with inverter-sourced distributed energy resources that combines robust control and droop control. As the load within the microgrid changes, the inverter-sourced generators share the change in the load; this paper shows that the uncontrolled load sharing among the generators will be arbitrary and methods such as droop control achieve a regulated change. This paper includes a background on control schemes for power sharing and highlights the difficulty in exact reactive power sharing. The performance of the proposed controller is demonstrated using a test microgrid system.

The design of a phase-locked loop (PLL)-based proportional integral (PI) controller for improving the spiral scanning of a piezoelectric tube scanner (PTS), used in an atomic force microscope (AFM), is demonstrated in this paper. Spiral motion of the PTS for scanning of material surfaces or biological samples using an AFM is achieved by applying two sinusoidal signals with a 90 degree phase-shift and of varying amplitudes to the X and Y-axes of the scanner. If there is an exact 90-degree phase shift between the sinusoidal displacements of the two scanner axes, a true circular image is generated. Otherwise, the image will distort into an elliptical shape, which can lead to missing data points or changes in the lattice structure of the sample surface to be scanned. The phase error between the X and Y-axes positions increases with increasing scanning speeds. In this proposed control scheme, the phase error between the displacements of the two lateral axes of the scanner is measured by a phase detector and is minimized using a PI controller. Experimental results for reference tracking and imaging performance confirm the efficiency of the proposed control scheme. Refereed/Peer-reviewed

This paper presents a new nonlinear current control scheme for a single-phase grid-connected photovoltaic (PV) system. The controller is designed using partial feedback linearization which linearizes the system partially and enables the controller design scheme for reduced-order PV systems. The reference current is calculated from the maximum power point tracking system. The proposed current control approach introduces the internal dynamics and the stability of the internal dynamics is a key requirement for the implementation of the controller. In this paper, an energy-based Lyapunov function is used to analyze the stability of internal dynamics of a PV system. The performance of the controller is evaluated based on the tracking of grid current to the reference current by considering the changes in atmospheric conditions. To ensure the suitability of the proposed controller in a real system, a large system similar to a practical system is simulated under different operating conditions such as changes in atmospheric conditions and faults on various parts of the system and compared with conventional controllers. The experimental validation of the proposed control scheme is also presented in this paper.

Active and passive filters are essential to maintain the power quality of a HVDC link. In this paper the Vehicle to Grid (V2G) technology is used to design a virtual active filter based on instantaneous power theory ( p – q theory). The potential of a low-cost solution that utilizes the reactive power and filtering capabilities of plug-in vehicles parked in charging stations is investigated. Simulations are performed for the CIGRE benchmark HVDC network to demonstrate that the proposed virtual active filter improves the power quality maintaining the IEEE Std 519-1992.

This paper presents a robust stabilization scheme for a three-phase grid-connected photovoltaic system to control the current injected into the grid and dc-link voltage to extract maximum power from photovoltaic (PV) units. The scheme is mainly based on the design of a robust controller using a partial feedback linearizing approach of feedback linearization, where the robustness of the proposed scheme is ensured by considering uncertainties within the PV system model. In this paper, the uncertainties are modeled as structured uncertainties based on the satisfaction of matching conditions. The performance of the proposed stabilization scheme is evaluated on a three-phase grid-connected PV system in terms of delivering maximum power under changes in atmospheric conditions.

This paper presents an analysis to investigate the critical factors which affect the dynamic stability of wind energy conversion systems (WECSs) with permanent magnet synchronous generators (PMSGs). In this paper, at first the detail mathematical model of a WECS with a PMSG is developed and then the modal analysis technique is used to identify the critical factors. The sensitivity of these critical factors on the dynamic stability of WECSs with PMSGs, is analyzed in terms of damping ratio with changes in critical factors. The proposed approach is tested on a WECS with single PMSG for different level of wind energy penetration.

A nonlinear controller design technique, for the enhancement of power quality and power system stability in a vehicle-to-grid (V2G) system, is proposed in this paper. The dynamical model of a V2G system is first developed and then the controller is designed based on the partial feedback linearization of the developed model. The control scheme is developed in such a way that converters in V2G systems are capable of injecting both active and reactive power into the grid. The implementation of the proposed controller requires the stabilization of internal dynamics of V2G systems as it transforms the system into a partly linear and an autonomous system with internal dynamics. The stability of internal dynamics of V2G systems is also discussed in this paper. Finally, the performance of the proposed control scheme is evaluated on a simple test system in terms of power quality and system stability enhancement. From the simulation result it is found that the designed nonlinear controller provides excellence performance in improving power quality and stability of whole system.

The complexity of modern day power grid is increasing with penetration of large-scale renewable resources at various levels of the networks. Inclusion of communication networks, to facilitate data transfer for ensuring reliability and security of the power system, with the electricity network extends the complexity to a new scale in a contemporary smart power grid. Any error in the integrated communication network can propagate through the electricity grid initiating large-scale cascading outages. Extensive precautionary measures should be taken in order to avoid such catastrophe. Complex network theory has been very useful in identifying critical components within the system as well as modelling of cascading failures. Complex network theory based percolation methods have been proved to be very useful in assessing power grid vulnerability under random and targeted attacks. In this paper, we extend our network percolation based analysis to explore the functional vulnerability of the existing electricity grid, effect on grid service efficiency, of increasing penetration of renewable energy. Vulnerable regions are identified with a fast computer simulation which helps operators to take quick preventive measures in case of emergency. Various standard IEEE test systems are simulated to test the applicability of the proposed algorithm in a real power system.

This paper presents an experimental demonstration of a novel real-time Energy Management System (EMS) for inverter-based microgrids to achieve optimal economic operation using a simple dynamic algorithm without offline optimization process requirements. The dynamic algorithm solves the economic dispatch problem offering an adequate stability performance and an optimal power reference tracking under sudden load and generation changes. Convergence, optimality and frequency regulation properties of the real-time EMS are shown, and the effectiveness and compatibility with inner and primary controllers are validated in experiments, showing better performance on optimal power tracking and frequency regulation than conventional droop control power sharing techniques.

In this paper, a techno‐economic optimum configuration process is assessed for hybrid power systems in terms of different generation capacities. It will provide a basis for the configuration of a practical microgrid. Initially, the actual power demand in a particular university area, namely, Khulna University of Engineering & Technology in Bangladesh, is measured, and then, the process of designing the optimized model is demonstrated with an initial choice of various parameters and constraints. Its inputs are climate data, electrical loads, technical and economic parameters of the equipment used for generation, sensitivity variables, grid parameters, and project economics and constraints. The best mix of solar photovoltaics (PV) and wind power is determined considering the most profitable size of the PV's inverter for different plants. The optimization results obtained through HOMER show that a specific PV panel does not need an inverter of the same capacity and a smaller one results in a lower investment. The analysis has been carried out by considering annual increase rates of both the load and the grid power price, which makes the result more realistic. The optimal size and control strategy are determined based on the net present cost, levelized cost of energy, increased rates of load and grid price, renewable fraction, and greenhouse gas emissions. A comparative analysis between the fixed and variable data for load and cost demonstrates that an optimal inverter-PV ratio, with the best mix of PV and wind energy, provides an optimum solution for all models. An economically viable plant size of 1.5 MW for the considered case is achieved.In this paper, a techno‐economic optimum configuration process is assessed for hybrid power systems in terms of different generation capacities. It will provide a basis for the configuration of a practical microgrid. Initially, the actual power demand in a particular university area, namely, Khulna University of Engineering & Technology in Bangladesh, is measured, and then, the process of designing the optimized model is demonstrated with an initial choice of various parameters and constraints. Its inputs are climate data, electrical loads, technical and economic parameters of the equipment used for generation, sensitivity variables, grid parameters, and project economics and constraints. The best mix of solar photovoltaics (PV) and wind power is determined considering the most profitable size of the PV's inverter for different plants. The optimization results obtained through HOMER show that a specific PV panel does not need an inverter of the same capacity and a smaller one results in a lower investment...

This paper presents a nonlinear controller design for a DSTATCOM connected to a distribution network with distributed generation (DG) to regulate the line voltage by providing reactive power compensation. The controller is designed based on the partial feedback linearization which transforms the nonlinear system into a reduced-order linear system and an autonomous system whose dynamics are known as internal dynamics of the system. This paper also investigates the stability of internal dynamics of a DSTATCOM as it is a basic requirement to design partial feedback linearizing controllers. The performance of the proposed controller is evaluated in terms reactive power compensation to enhance the voltage stability of distribution with DG.

The existence of critical voltage modes in distribution systems and the key factors responsible for them are presented in this paper. The analysis is carried out over a distribution test system for different types of induction motors. Eigenvalues and participation factors are used to investigate the modal interaction within the system. This study shows that load voltage dynamics significantly influence damping of the voltage modes. These modes have frequencies of oscillations between the electromechanical and subsynchronous oscillations of power systems. Significant parameters of the system which affect the damping and frequencies of the oscillations are identified to provide a clear understanding of the problem. A bifurcation study is performed to determine the dynamic loadability limit of the system. Time-domain simulations are carried out to verify the validity of the modal analysis and provide a physical feel for the types of oscillations that occur in distribution systems. The impact of various distribution network configurations on these modes is also demonstrated through nonlinear simulations.

This paper presents the high-precision lateral positioning of a piezoelectric tube scanner (PTS) used in an atomic force microscope (AFM). The operation of the PTS is affected by various nonlinearities depending upon its operating conditions. An internal reference model-based optimal linear quadratic Gaussian (LQG) controller with a vibration compensator is designed and implemented on the AFM to reduce creep, hysteresis, induced vibration, and cross coupling. This proposed controller has integral action on the error state which makes it possible to track the reference signal and the vibration compensator achieves significant damping of the resonant modes of the PTS in the X- and Y-axes. It also compensates the cross coupling between the X-Y axes dynamics of the AFM system, reducing the artifacts instigated by the system dynamic behavior at high scan rates. The closed-loop frequency responses for both the axes have a high bandwidth. The experimental results are presented which demonstrate the efficacy of the proposed method. Refereed/Peer-reviewed

In stressed power systems with large induction machine component, there exist undamped electromechanical modes and unstable monotonic voltage modes. This article proposes a sequential design of an excitation controller and a power system stabiliser (PSS) to stabilise the system. The operating region, with induction machines in stressed power systems, is often not captured using a linearisation around an operating point, and to alleviate this situation a robust controller is designed which guarantees stable operation in a large region of operation. A minimax linear quadratic Gaussian design is used for the design of the supplementary control to automatic voltage regulators, and a classical PSS structure is used to damp electromechanical oscillations. The novelty of this work is in proposing a method to capture the unmodelled nonlinear dynamics as uncertainty in the design of the robust controller. Tight bounds on the uncertainty are obtained using this method which enables high-performance controllers. An IEEE benchmark test system has been used to demonstrate the performance of the designed controller.

This paper proposes static and dynamic VAR planning based on the reactive power margin for enhancing dynamic voltage stability of distribution networks with distributed wind generation. Firstly, the impact of high wind penetration on the static voltage stability of the system is analysed and then the effect of composite loads on system dynamics is presented through an accurate time-domain analysis. A new index, reactive power loadability (Q-loadability), is used to measure the vulnerability of the network to voltage collapse. Compensating devices are located using Q-loadability to increase the system voltage stability limit. Finally, a cost-effective combination of shunt capacitor bank and distribution static compensator (D-STATCOM) is determined through static and dynamic analyses to ensure voltage stability of the system after a sudden disturbance for different wind penetration levels. This study takes into account the induction motor dynamic characteristics which influence the transient voltage recovery phenomenon. The results show that the proposed approach can reduce the required sizes of compensating devices which, in turn, reduces costs. It also reduces power losses and improves the voltage regulation of the system.

Increasing wind power penetration into the grid justifies the requirement of the analysis of wind power dynamics, especially during transient faults. Quantitative transient stability (TS) assessment is required to provide deeper insight into the TS problems for speeding up the operational decision making process. This can be achieved by evaluating transient stability index (TSI) through the assessment of transient energy function. This paper carries out the quantitative insight of the impact of different generator technologies on the grid by comparatively studying the impacts of the fault clearing time, the grid coupling, the inertia constant, the generator terminal voltage sag and the slip on fault responses with the TSI between synchronous generators and wind turbine generators, such as squirrel cage induction generators and doubly fed induction generators.

This paper proposes the use of a particular class of linear differential inclusion (LDI) for the estimation of regions of attraction of asymptotically stable equilibrium points of nonlinear dynamical systems with time-varying parametric uncertainties bounded by a polytope. In this paper, we provide a systematic procedure based on the mean value theorem in conjunction to a linear matrix inequality based approximation technique to obtain the description of the uncertain nonlinear system via the proposed LDI form, which can be written equivalently as a particular class of a time-varying linear system. Through this suitable system representation in the form of this time-varying linear system, a numerical algorithm based on convex optimization is proposed to determine these regions of stability. Two numerical examples are given to demonstrate the effectiveness of the proposed approach.

This paper presents a new control scheme for the enhancement of the low-voltage ride-through (LVRT) capability of doubly fed induction generators. The LVRT capability is provided by extending the range of operation of the controlled system to include typical postfault conditions. Controllers are designed simultaneously for both the rotor- and grid-side converters using a linear quadratic output-feedback decentralized control strategy. The nonlinear terms in the power system model are represented in this paper by an uncertain term derived from the Cauchy remainder of the Taylor series expansion. A genetic algorithm is used to calculate the bound on the uncertainty. The robust controller resulting from this design provides acceptable performances to enhance voltage and transient stability margins and thereby to limit the oscillations, the peak value of the rotor current, and the dc-link voltage fluctuations. The performance of the designed controller is demonstrated under different operating conditions by large-disturbance simulations on a test system.

In this paper, the problem of practical stability of some classes of continuous-time switched systems is studied. The main results of this paper include some sufficient conditions concerning practical stability of continuous-time switched nonlinear systems without a common equilibria for all subsystems. In this class of switched systems, the equilibrium point varies discontinuously according to a time-dependent switching signal. So, stability with respect to a set, rather than a particular point, is discussed. Using this preliminary result, we present sufficient conditions in the form of linear matrix inequalities (LMIs) for practical stability of a particular class of switched systems without common equilibria: the switched affine systems. An illustrative example in the power system stability area is presented to show the validity of the results.

Summary This paper identifies a new mode called “critical voltage mode" in emerging distribution systems. The small-signal stability analysis indicates that load voltage dynamics significantly influence the damping of the newly identified mode. This mode has frequency of oscillation between the electromechanical and subsynchronous oscillation of power systems. A novel voltage controller is designed to damp this voltage mode of the system. The controller is designed using the linear quadratic Gaussian (LQG) method with norm-bounded uncertainty. The approach considered in this paper is to find the smallest upper bound on the H∞ norm of the uncertain system and to design an optimal controller based on this bound. The design method requires the solution of a linear matrix inequality. The performance of the designed controller is demonstrated on a distribution test system for different types of induction motors. Simulation results show that the proposed controller with a careful uncertainty modeling has significant performance to improve the voltage profile of the distributed generation system compared to the conventional excitation controller and standard LQG controller. Copyright © 2013 John Wiley & Sons, Ltd.

This paper presents the design and experimental implementation of an observer-based model predictive control scheme with a notch filter to achieve accurate tracking and fast scanning for an atomic force microscope (AFM). The proposed controller reduces the tracking error by improving the damping of the resonant modes of the AFM piezoelectric tube scanner (PTS). The design of this controller is based on an identified model of the PTS. A Kalman filter is used to obtain full-state information in the presence of position sensor noise. A comparison of the experimentally obtained scanned images using the proposed controller and the existing AFM PI controller is given. The experimental results demonstrate the efficacy of the proposed controller.

A novel aggregated model for wind farms consisting of wind turbines equipped with doubly-fed induction generators (DFIGs) is proposed in this paper. In the proposed model, a mechanical torque compensating factor (MTCF) is integrated into a full aggregated wind farm model to deal with the nonlinearity of wind turbines in the partial load region and to make it behave as closely as possible to a complete model of the wind farm. The MTCF is initially constructed to approximate a Gaussian function by a fuzzy logic method and optimized on a trial and error basis to achieve less than 10% discrepancy between the proposed aggregated model and the complete model. Then, a large scale offshore wind farm comprising of 72 DFIG wind turbines is used to verify the effectiveness of the proposed aggregated model. The simulation results show that the proposed aggregated model approximates active power (Pe) and reactive power (Qe) at the point of common coupling more accurately than the full aggregated model by 8.7% and 12.5%, respectively, during normal operation while showing similar level of accuracy during grid disturbance. Computational time of the proposed aggregated model is slightly higher than that of the full aggregated model but much faster than the complete model by 90.3% during normal operation and 87% during grid disturbance.

This paper presents a cost-effective reactive power planning for active distribution networks based on a new index called reactive power loadability (Q-loadability). The impact of high renewable energy penetration on the static voltage stability of the system is analysed. The effect of load models in distributed generation planning is also demonstrated through nonlinear simulations. In order to ensure fast voltage recovery after a sudden disturbance, compensating devices are located using Q-loadability to increase the system voltage stability limit. Both static and dynamic analyses are carried out to determine the size of distribution static synchronous compensator (D-STATCOM). The parameters of the controller are also tuned to reduce the rating of D-STATCOM. Simulation results show that the proposed approach can reduce the sizes of compensating devices required which, in turn, reduces costs. The effectiveness of the proposed algorithm is verified through several case studies.

The doubly fed induction generator (DFIG) is interfaced to the AC network through voltage source converters (VSCs) which are considered to be the core of the DFIG system. This paper investigates the impact of different intermittent VSC faults on the overall performance of a DFIG-based wind energy conversion system (WECS). The fault ride through capability of the DFIG under various VSC faults is also investigated. Faults such as open circuit and short circuit across the switches, when they occur within the grid side converter (GSC) and rotor side converter (RSC), are considered and compared in this paper. Short circuit and open circuit across the DC-link capacitor are also considered in this study as common VSC problems. Simulation results indicate that the short circuit faults have a severe impact on the overall performance of the DFIG, especially when they occur within the GSC. This is attributed to the fact that the GSC directly regulates the point of common coupling voltage. The open circuit faults hav...

This paper investigates the critical parameters of power systems which affect the stability of the system. The analysis is conducted on both a single machine infinite bus (SMIB) system and a large multimachine system with dynamic loads. To further investigate the effects of dynamic loads on power system stability, the effectiveness of conventional as well as modern linear controllers is tested and compared with the variation of loads. The effectiveness is assessed based on the damping of the dominant mode and the analysis in this paper highlights the fact that the dynamic load has substantial effect on the damping of the system.

The Microgrid (MG) concept has been proposed as an effective way to achieve the Smart Grid objectives. Although different implementation challenges of the MGs have been overcome, issues related to reactive power sharing control have been researched recently and new trends have been proposed. These new control strategies have in common the use of different cybernetic characteristics including virtual components and communication systems. This paper discusses these new trends based on a cyber physical methodology, where the communication architectures, as well as, cyber-physical (CP) modelling modules are developed to analyse their potential advantages and drawbacks from a cyber physical perspective.

Un-coordinated Electric Vehicle (EV) charging behaviors will impact the power grid and degrade power quality. Smart charging system can optimally allocate the energy among EVs and minimize the impact on grid. IEC 61850 is an international standard for distribution & substation automation and intelligence device communication in smart grid. This paper introduces the extension of IEC 61850 with smart EV scheduling algorithms, considering current multiplexing, power sharing strategies and user behaviors. We have developed an IEC 61850 abstract data model for the information exchanged among components of smart EV charging infrastructures, including the EV charging control center, intelligent Electric Vehicle Supply Equipment (EVSE) and the EV users with mobile applications. Real-world EV usage data on UCLA campus is utilized in the simulation experiment, which is based on the predictive control paradigm. The data model is instantiated by a web service on EV control center by converting the raw data streams from EVSEs in various formats, such as JSON or raw string, etc. into a standardized IEC 61850 SCL file, which contains the critical meter data and charging session parameters. The system cost performance, the interoperability and scalability of smart EV charging infrastructure are greatly improved.

Model predictive control (MPC) is a multivariable control algorithm commonly used when tracking a reference trajectory is the primary goal. It minimizes the steady-state tracking error, increases the closed-loop bandwidth, and enables the controller to track a reference signal, the major requirements for nanopositioning applications. These capabilities motivated this research on improving the positioning performance of the piezoelectric tube scanner (PTS) in an atomic force microscope (AFM) to achieve better imaging at high scanning speed. This paper surveys the effectiveness of an MPC controller for AFM imaging by considering its different features and comparing its results with those obtained from the in-built proportional integral (PI) controller.

This paper investigates the transient stability of power systems under the framework of complex network theory. The studied power system is assumed to be singularly perturbed so that the corresponding reduced-order system is a Kuramoto-oscillator system in complex network theory. A condition is presented to guarantee the bounded synchronization of reduced system with an arbitrary topology so that the original system is transiently stable. The effectiveness of this condition is verified by simulation results on IEEE 57-bus and 118-bus power systems.

The penetration level of distributed energy resources (DERs) especially photovoltaic (PV) system is envisioned to keep on increasing in future distribution grid. Current step voltage regulators (SVRs) equipped with local controls such as line drop compensation (LDC) will experience the increased tap operation in the presence of PV system particularly on a cloudy day. This operational stress will increase the annual maintenance cost and reduce the lifespan of SVRs. To cope with this issue, current volt/VAR control (VVC) schemes need to integrate additional control equipment and adopt different coordinated control schemes. This paper proposes a centralized coordinated control scheme to reduce the SVRs' operational burden by contributing towards voltage support. The centralized coordinated control is ensured by integrating SVRs and battery energy storage system (BESS) into the smart distribution management system (DMS). Particle swarm optimization (PSO) has reduced the tap operation and optimized the charging and discharging operations of BESS. Simulation studies are conducted using modified quasi-static time-series IEEE 34-bus test feeder. The PSO is implemented in MATLAB while DigSILENT PowerFactory is used for quasi-dynamic simulations. Results indicate the effectiveness of BESS in voltage support and considerable decline in operational cost.

Equal rating inverters operating with different power set points may experience circulating power during unpredictable cases such as faults on a heavy load site due to a large mismatch between load consumption and power generation. This momentarily circulating power increases the dc-link voltage of the inverter and exceeds the voltage limit, leading to inverter shutdown for safety purposes. To overcome this issue, this paper proposes a control method that limits the dc-link voltage of an inverter during unusual events by using a series connected resistor with a switch across the dc-link capacitor. A detailed simulation is performed using Matlab/SimPowerSystems to validate the concept presented and justify the effectiveness of the control approach.

This paper provides a comparative study of the dynamic response of variable-speed wind turbine generators, such as Type III and Type IV wind generators, to voltage sags and swells. Both symmetrical and asymmetrical voltage sags and swells are considered. The comparative analysis provides an insight into the relative degree of risk posed by different grid voltage conditions to the functioning of wind turbine generators. It has been found that certain voltage conditions are more harmful than others. This information is particularly useful when designing advanced protection schemes for wind turbine generators. A grid-connected 9-MW Type III wind farm and a 10-MW Type IV wind farm are used for simulation in MATLAB/SimPowerSystems.

This paper analyzes positive and negative impacts of the integration of distributed generation (DG) in unbalanced multi-phase distribution networks. Several aspects, for example, the static voltage stability, power loss, short-circuit and voltage unbalance studies are conducted on an IEEE 13 node unbalanced distribution feeder. Simulation platform used here is DIgSILENT PowerFactory. In this paper, synchronous generators and solar photovoltaic (PV) units are introduced as distributed generators. It is found that, although a DG unit has a positive impact on the voltage stability and power loss of the system, it increases the short-circuit current at all nodes of the feeder. In certain cases, it can impact both positively and negatively on the voltage imbalance phenomenon of a distribution network depending on the single-/three-phase connection of PV units to it.

This paper provides a novel integrated protection and power management scheme for Doubly-Fed Induction Generators (DFIG) to enhance their performance under voltage sags and swells. Both symmetrical and asymmetrical voltage sags and swells are considered. The protection system limits the overcurrent in the Rotor Side Converter (RSC) and keeps the dc-link voltage within an acceptable range; while, the reactive power management supports the grid by either injecting or absorbing reactive power to reduce the magnitude of voltage sags and swells. It has been found that the performance of DFIGs improves considerably under the proposed scheme. A grid-connected 9-MW DFIG wind farm has been used for simulation in MATLAB/SimPowerSystems.

This paper describes a set of algorithms used to detect and analyse resonant modes present in the oscillatory type signals measured in power systems using Wide Area Measurement System (WAMS) technology. To enable easier analysis and extraction of the main signal parameters - frequency, amplitude and damping, described algorithms have been implemented and tested using Matlab based GUI program. Algorithms performance, operation of developed GUI and some initial results are presented in this paper indicating the potential use of this approach and described methods in large, interconnected power systems of today.

In this paper, an innovative agent-based security scheme is proposed for identifying potential impacts of cyber attacks in smart grid protection systems. Smart grids are critical cyber-physical energy systems (CPESs), where potential attacks can manipulate the normal operation of digital relays by injecting malicious control signals. This event could cause the relays to trip at undesired time which in turn results unintentional trippings, even if there are no faults. The proposed scheme identifies the malicious cyber attacks by utilizing cyber and physical properties of power systems. Moreover, the agents further distinguishes attacks from physical faults and their potential is validated through computer simulation using a benchmark power system.

In this paper, droop-based automatic control schemes are presented to control parallel inverter-interfaced distributed generators (DG) in a way that proportional reactive power sharing is possible in islanded microgrids under different structures. This paper modifies the conventional reactive power-voltage (Q-V) droop control strategy used in inductive (L-type) islanded microgrids by implementing voltage control law in overall control operation such that reactive power becomes inversely proportional to the reactive droop gain if the initial values of inverter-interfaced voltage-sources are the same. Reactive power sharing approach for resistive (R-type) islanded microgrids is also included in this paper; in which it is shared depending on rate-of-angle of voltage-sources, i.e., reactive power-frequency (Q-f) droop. The proposed control methods utilize linear modal analysis to design both types of droop-based controllers. A 5-bus microgrid with 4-parallel inverter-connected DG units is considered for simulations under load changing phenomenon where results show the excellency of the designed control schemes.

This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.

This paper considers a typical solar installations scenario with limited sensing resources. In the literature, there exist either day-ahead solar generation prediction methods with limited accuracy, or high accuracy short timescale methods that are not suitable for applications requiring longer term prediction. We propose a two-tier (global-tier and local-tier) prediction method to improve accuracy for long term (24 hour) solar generation prediction using only the historical power data. In global-tier, we examine two popular heuristic methods: weighted k-Nearest Neighbors (k-NN) and Neural Network (NN). In local-tier, the global-tier results are adaptively updated using real-time analytical residual analysis. The proposed method is validated using the UCLA Microgrid with 35kW of solar generation capacity. Experimental results show that the proposed two-tier prediction method achieves higher accuracy compared to day-ahead predictions while providing the same prediction length. The difference in the overall prediction performance using either weighted k-NN based or NN based in the global-tier are carefully discussed and reasoned. Case studies with a typical sunny day and a cloudy day are carried out to demonstrate the effectiveness of the proposed two-tier predictions.

This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA) models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.

The design of a phase-locked loop (PLL)-based proportional integral (PI) controller for compensating the phase error between motions from the lateral axes of a piezoelectric tube scanner (PTS) during spiral scanning for an atomic force microscope (AFM) is proposed in this paper. Spiral motion of the PTS for scanning of material surfaces or biological samples using an AFM is achieved by applying two sinusoidal signals with a 90 degree phase-shift and of varying amplitudes to the X and Y-axes of the scanner. The phase error between the X and Y-axes positions and scanner's vibration due to its mechanical properties increase with increasing scanning speeds which reduce the imaging performance of the AFM at high frequencies. In the proposed control scheme, a vibration compensator is used with the X and Y-PTS to damp the vibration of the PTS at its resonant frequency and the phase error between the displacements of the two lateral axes of the scanner is measured by a phase detector and a PI controller is used to reduce the error. Comparisons of experimental results for reference tracking and imaging performance with the AFM PI controller demonstrate the efficiency of the proposed control method. Refereed/Peer-reviewed

In most nanotechnology applications, speed and precision are important requirements for obtaining good topographical maps of material surfaces using atomic force microscopes (AFMs), many of which use piezoelectric tube scanners (PTSs) for scanning and positioning at nanometric resolutions. However, PTS suffers from various intrinsic problems that degrade its positioning performance, such as: (i) lightly damped low-frequency resonant modes due to its mechanical structure; (ii) nonlinear behavior due to hysteresis and creep; and (iii) the cross-coupling effect between its axes (in 3D positioning systems such as AFMs). This paper presents a survey of the literature on the PTS, an overview of a few emerging innovative solutions for its nanopositioning and future research directions. Refereed/Peer-reviewed

This paper proposes a decentralized control strategy for higher penetration of photovoltaic (PV) units without violating system operating constraints. A systematic procedure is developed and a robust controller is designed to ensure both dynamic voltage and transient stability for a specific PV integration level. The change in the model due to the volatile nature of PV generations is considered as an uncertain term in the design algorithm. Simultaneous output-feedback linear quadratic controllers are designed for PV generators. This designed control scheme is robust with respect to intermittency and enhances the integration level in a sub-transmission and distributed system. The effectiveness of the proposed controller is verified on a 43-bus industrial meshed distribution system under large disturbances. It is found that the designed control scheme enhances stability and increases the renewable integration levels.

This paper presents a novel full-order nonlinear observer-based excitation controller design for interconnected power systems. Exact linearization approach of feedback linearization is used to design the nonlinear observer when the power system is fully linearized. The excitation control law is derived for the exactly linearized power system model. The observed states of power system are directly used as the input to the controller where the control law does not need to be expressed in terms of all measured variables. A single machine infinite bus (SMIB) system is used as test system and all the states are observed for SMIB system. To validate the effectiveness of the proposed control scheme on a large system, a benchmark 3 machine 11 bus system is also simulated. Simulation results show the accuracy and performance of observer-based nonlinear excitation controller by comparing with the exact linearizing controller where the control law is expressed in terms of all measured variables.

This paper develops a robust H ∞ method for fast tracking position control problems arising in an atomic force microscope (AFM). A commercial type NT-MDT AFM is used to generate 3D images of scanned material surfaces at high speeds and accuracies. A major component of this AFM is a piezoelectric tube actuator used for position control in three directions. Due to the nature of the piezoelectric actuator, there is nonlinear hysteresis present which affects the AFM scanning qualities. The original commercial AFM uses traditional proportional-integral-derivative position control and can only obtain good quality images for scanning rates under about 20 Hz in both the x and y directions. In this paper, a robust H ∞ controller is designed based on a physical model of the AFM piezoelectric tube positioner in the x and y directions. On the electrical side of the positioning system, external capacitors are connected in series with the x and y contacts of the piezoelectric tube to provide measured voltages which are proportional to the charge on the actuator. The parameters for a nonlinear model are obtained from measurements of the system frequency response and time domain response. This model also takes into account the time delay resulting from the sensor electronics. This nonlinear model is represented as a linear uncertain system model with norm bounded uncertainty. The uncertain system model is used to design a robust H ∞ tracking controller for the AFM scanning system. Experimental results show that the robust H ∞ controller can improve the AFM scanning quality and increase the scanning speed significantly. The controller performs well in tracking a given reference scanning signal with frequencies up to 125 Hz.

The complexity of power systems has increased in recent years due to the operation of existing transmission lines closer to their limits, using flexible AC transmission system (FACTS) devices, and also due to the increased penetration of new types of generators that have more intermittent characteristics and lower inertial response, such as wind generators. This changing nature of a power system has considerable effect on its dynamic behaviors resulting in power swings, dynamic interactions between different power system devices, and less synchronized coupling. This paper presents some analyses of this changing nature of power systems and their dynamic behaviors to identify critical issues that limit the large-scale integration of wind generators and FACTS devices. In addition, this paper addresses some general concerns toward high compensations in different grid topologies. The studies in this paper are conducted on the New England and New York power system model under both small and large disturbances. From the analyses, it can be concluded that high compensation can reduce the security limits under certain operating conditions, and the modes related to operating slip and shaft stiffness are critical as they may limit the large-scale integration of wind generation.

Since its introduction, the atomic force microscope (AFM) has developed into a ubiquitous tool for 3D imaging and manipulating objects at a nanoscale level. However, the imaging performance of AFMs is limited because of the limitations of its scanning unit, i.e., piezoelectric tube scanner (PTS). This paper addresses the design and experimental implementation of a two-input two-output (TITO) model predictive control (MPC) scheme which aims to overcome the limiting factors of the PTS in order to achieve improved 3D images. The effectiveness of the proposed method is experimentally compared with the existing AFM proportional-integral (PI) controller, the resonant controller, and the single-input single-output (SISO) MPC controller.

This paper presents the development and experimental implementation of a novel two-time scale controller for the hover control of a Rotary wing Unmanned Aerial Vehicle (RUAV). Flapping and servo dynamics, important from a practical point of view, are included in the RUAV model. The two-time scale controller takes advantage of the ‘decoupling’ of the translational and rotation dynamics of the rigid body, resulting in a two-level hierarchical control scheme. The inner loop (attitude control) tracks the attitude commands generated by the outer loop controller and sets the main rotor thrust vector, while the outer loop (position control) tracks the reference position. Hover flight experimental results are presented in this paper using the proposed two-time scale controller.

This paper presents a robust nonlinear state feedback linearization approach for power systems with uncertainties. The uncertainties considered here are a class of bounded perturbations to the state model of power systems. The control law is applied through the excitation system of the synchronous generators connected to the power systems to enhance the stability of the system. In this paper, uncertainties are considered for single machine infinite bus (SMIB) system. A Lyapunov-based concept is used to guarantee uniform ultimate boundedness.

This paper presents a new robust control methodology to improve the power system transient stability and voltage regulation in interconnected power systems including dynamic loads. The inclusion of dynamic load model significantly increases the nonlinearity of the system. The automatic voltage regulation (AVR) and power system stabiliser (PSS) design problems are coordinated for the augmentation of stability. The nonlinear behaviour of power systems has been represented in this paper by an uncertain term, derived from the Cauchy remainder of the Taylor series expansion. An IEEE benchmark test system has been used to demonstrate the performance of the designed controller. Large disturbance simulations demonstrate that the proposed controller enhances voltage stability as well as transient stability of a power system during severe transients.