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Wind power systems (WPs) are complex non‐linear systems with varying parameters affected by environmental changes, including wind speed fluctuations. Extracting maximum power from WPs poses a significant challenge due to these factors. Direct power control (DPC) is a highly effective technique known for its simplicity and ease of implementation. However, it suffers from power ripples caused by the use of hysteresis comparators and switching tables that operate at variable frequencies. To address this issue, this paper presents the robust neural controller (NC) based on DPC, which replaces the switching tables. The Double‐Fed Induction Generator (DFIG) is the chosen generator for the studied WP system due to its advantageous features. The NC‐DPC effectively regulates the exchange of active and reactive powers between the DFIG and the system, maximizing power extraction from the WP system while reducing Total Harmonic Distortion and enhancing overall system quality. The effectiveness of the NC‐DPC is evaluated through MATLAB simulations and further supported by experimental data obtained using the Real‐Time Interface of the dSPACE‐DS1104 Controller card. [ABSTRACT FROM AUTHOR]

The increasing interactivity between energy carrier networks such as electrical, natural gas (NG), and heating can be appropriately used for improving the operation optimality along with overcoming some challenges of those systems. With such a view, this paper studies the practical issue of power transmission lines congestion management in integrated multicarrier energy systems (MCESs) and makes a comparison with the only electrical operation mode. The MCES consisting of electrical and NG network infrastructures with exchanged energy between them is modelled by considering the several local energy hubs and their electrical and heat loads. Rescheduling of energy sources (power plants and gas wells) and demand side management in both electrical and NG networks have been utilized as the two important tools in the developed congestion alleviation framework. The proposed method confirms that the provided flexibility in the integrated operation of the MCESs can lead to a remarkable reduction in the congestion management cost index. Implementing the proposed congestion management framework on an assumed test MCES with a combined 39‐bus New England power system and 20‐node Belgium NG system demonstrates its effectiveness and applicability for the system operators. The issue of power transmission lines congestion management in integrated multi‐carrier energy systems (MCESs) has been studied. The proposed method confirms that the provided flexibility in the integrated operation of the MCESs can lead to reduction in the congestion management cost. [ABSTRACT FROM AUTHOR]

A wide range of remedial action schemes (RAS) have been developed and deployed in field to take automated control actions to maintain system reliability and stability during adverse system conditions. According to the regulatory standards from North American Electricity Reliability Corporation (NERC), RAS applications deployed in field and their functionalities are required to be tested periodically. To do testing for the RAS, regular process that requires taking critical components offline is usually labor‐intensive and time‐consuming, especially for complex applications utilizing multiple measurement units and controllers from different substations. To overcome these challenges, this paper presents a remote testing architecture for remedial action schemes. Our proposed remote testing architecture is capable of accessing test signal generators, phasor measurement units (PMUs), RAS control units from multiple substations, managing tests for both centralized and distributed implementations of RAS. To address the effectiveness of the remote testing architecture, this paper presents the minimal wind curtailment applications with detailed alternative formulations of optimization models for RAS and highlights performance of the proposed remote testing of RAS. Simulation results for an IEEE standard test system and representative industry test cases demonstrate effective performance of the developed RAS testing mechanism. [ABSTRACT FROM AUTHOR]

This paper proposes a WECS based on a back to back diode‐clamped multilevel inverter systems (DCMLI) fired comparatively by sinusoidal pulse width modulation (SPWM) and third harmonic injection pulse width modulation (THIPWM) techniques. DFIG performance is compared using these technologies for different wind speed under normal operation condition. The proposed approach shows that the DCMLI systems generate a nearly sinusoidal voltage with reduced total harmonic distortion (THD) thus upgrading the power quality of that produced by DFIG. As SPWM and THIPWM MLI are most common usage techniques in research, we applied them in the system to discuss a comparison of using those techniques to determine the number of levels that achieve the IEEE 519 criteria of THD which is less than 5% for both techniques (5th level for SPWM and 4th level for THIPWM) in all operation wind speed. Compared with simple PWM, and THIPWM have many advantages as lower THD, minimal number of switching to decrease switching losses and the output fundamental voltage is increased. Lastly, the paper investigates the variation of the frequency of induced rotor voltage and the active power flow due to the wind speed change when the rotor speed changes from super‐synchronous to sub‐synchronous speeds. [ABSTRACT FROM AUTHOR]

A cluster with multiple AC or DC microgrids (MGs) based on flexible DC interlinking and distributed energy storage systems is studied in this paper, which has been identified to have the following issues in terms of its primary control scheme: coordinated power control among slack terminals in the MG cluster, seamless operation mode transition for the interlinking converters and the common DC bus voltage control. A novel flexible control scheme that unifies the control of all the MGs only using local measured signals without further communications is proposed in this paper, which aims to improve control stability, and operation reliability and flexibility. Theoretical introduction and analysis are presented to explain the proposed control. The detailed average value model and small‐signal model of an MG cluster with two AC MGs and two DC MGs are simulated, respectively, with the proposed control in power systems computer‐aided design/electro‐magnetic transient design and control to verify the effectiveness in control stability and flexibility enhancement, and the impact of control parameters on the small‐signal stability of the considered cluster is analysed through root locus. [ABSTRACT FROM AUTHOR]

Microgrid inverters in the presence of faults, unavoidable modelling uncertainties, disturbance and harmonic current resulting from nonlinear loads should have small steady state tracking error, small THD and high robustness hence this subject has turned one of the motivations of this investigation. To achieve the stated goals, fractional adaptive sliding mode controller (FASMC) is proposed in this paper. The proposed controller increases the robustness, flexibility and degree of freedom. As far as in practice it is not easy to define the bounds of disturbances and guarantee the system stability, hence in next step, to overcome this challenge the adaptation laws are suggested. Then for the problem of determining the controller parameters, Particle Swarm Optimization (PSO) algorithm is used. The performance of the proposed technique is investigated for an islanded microgrid under different disturbances, also to verify the advantages of the proposed controller, the results are compared with other controllers. Finally, the proposed controller and PID controller are implemented experimentally on Arduino mega 2560 microcontroller. [ABSTRACT FROM AUTHOR]

Uncertainities and variations of power generation through photovoltaic (PV) sources are major challenges for their integration with the distribution grid. Voltage rise and voltage drop issues limit the increase in PV penetration and loading levels, respectively. Moreover, it is important to maintain voltage levels as per grid code while ensuring that the PV power generation is not curtailed. In this paper, a voltage control method using smart transformer (ST) via dynamic optimal setpoints and limit tolerance is proposed in a residential distribution network. Performance indicators are developed to understand the impact of the proposed method on the system voltage profile. A method to determine the optimal inputs for voltage control methods depending on the day-ahead predictions of load demand and PV power profiles is developed. Further, a voltage control method of switching among three setpoints based on the voltage that determines the load side ac reference voltages for ST is proposed. The proposed method is compared with the method of switching between two setpoints based on current. The proposed method provides an improved voltage profile in the distribution network, which is tested on a CIGRE low voltage residential distribution network using PSCAD [ABSTRACT FROM AUTHOR]

This research presents a robust model predictive controller of two microgrids (MGs) interconnected via tie‐line (TL) power. Power system operations continue to face new challenges due to the large integration of renewable energy generation with an active load demand uncertainty and the management and control of bidirectional power flow between MGs and others uncertainties and system nonlinearities due to the power system operating condition. To handle these uncertainties and system nonlinearities a robust model using predictive control scheme is presented in this paper to achieve the control of the active power between two MGs when considering three disturbances scenario models. In the design process, uncertainties and nonlinearities of the system were taken into account and contributed to the robustness of the closed‐loop system. Robust control scheme development considering power system nonlinearities and uncertainties were used to improve the online close‐loop robustness. The model helped to achieve a desired active power regulation by coordinating the MGs and active power over‐shoot and under‐shoot time were reduced outstandingly. A Comparison was made between open‐loop and close‐loop simulation results, which indicate that the model can handle robustness while settling power deviation of the interconnected system. MATLAB environment was used to solve the optimisation problem. [ABSTRACT FROM AUTHOR]

Recently, microgrids (MGs) present a vital role in the transformation of the existing power networks to the smart grids. Connecting MGs to construct the multi-microgrid (MMG) system enhances the robustness of the system against disturbances and upgrades overall network performance. In this paper, the MMG, as a source of self-healing support to the distribution networks, is analysed extensively. In fact, the MMG strengthens the self-healing of the network by participating in the restoration of disturbed loads. In this study, an operational framework is proposed for the self-healing problem in radial interconnected MGs based on two-stage cyber communication network architecture. In the first stage, the local control system (LCS) within each MG, schedules the accessible resources according to the local power consumption target. In the second stage, a number of LCSs are communicated globally to perform self-healing action. The communication of LCSs is accomplished using a consensus algorithm. Nevertheless, when a fault takes place in MG and a line is eliminated, the healthy MGs, due to demand and supply information in the first stage, supply the on-outage loads as far as possible. To validate the effectiveness of the proposed framework, two benchmark distribution networks (the 33-bus and the 119-bus) are employed. [ABSTRACT FROM AUTHOR]

Recently, microgrids (MGs) present a vital role in the transformation of the existing power networks to the smart grids. Connecting MGs to construct the multi‐microgrid (MMG) system enhances the robustness of the system against disturbances and upgrades overall network performance. In this paper, the MMG, as a source of self‐healing support to the distribution networks, is analysed extensively. In fact, the MMG strengthens the self‐healing of the network by participating in the restoration of disturbed loads. In this study, an operational framework is proposed for the self‐healing problem in radial interconnected MGs based on two‐stage cyber communication network architecture. In the first stage, the local control system (LCS) within each MG, schedules the accessible resources according to the local power consumption target. In the second stage, a number of LCSs are communicated globally to perform self‐healing action. The communication of LCSs is accomplished using a consensus algorithm. Nevertheless, when a fault takes place in MG and a line is eliminated, the healthy MGs, due to demand and supply information in the first stage, supply the on‐outage loads as far as possible. To validate the effectiveness of the proposed framework, two benchmark distribution networks (the 33‐bus and the 119‐bus) are employed. [ABSTRACT FROM AUTHOR]

The variable step size modified least mean square (VSSMLMS) learning algorithm based multifunctional double‐stage grid interactive photovoltaic (PV) system is implemented in this paper which feeds power to the grid and the load, ensures unity power factor operation and compensates reactive power. Along with this, it mitigates high grid neutral current during unbalanced loading condition. This algorithm uses variable step sizes to have a smooth dynamic and steady state performances. The boost converter (booster) is used in the first stage to extract peak power from a PV array using perturb and observe peak power point tracking technique. Next to this, a four leg voltage source converter (VSC) is placed to interlink the solar PV system to the grid and the loads. VSSMLMS‐based control technique is used to filter the fundamental component of load current and hence gate pulses are generated for the four‐leg VSC. This system is simulated in SIMULINK/MATLAB software under several working conditions and the obtained simulation results are validated on a developed laboratory prototype. The performance of the VSSMLMS‐based control technique is compared with that of the traditional LMS‐based technique. All results validate the IEEE‐519 standard. [ABSTRACT FROM AUTHOR]

With the proliferation of intermittent renewable energy sources, power systems need to withstand an increasing number of disturbances that may affect system frequency. In this paper, we focus on the effects of high penetration level of wind turbine‐generators (WTG) on the power system operational planning from the frequency point of view. Specifically, an exact formulation for the minimum frequency calculation is presented to increase accuracy and speed of analyses. Then, the effect of WTG's frequency response on the power system frequency stability is investigated to compute the maximum acceptable generation outage as a function of penetration level. Finally, as an application to power system operational planning, the obtained frequency dynamics of the power system and the wind turbine frequency response are integrated into the unit commitment problem. Simulations are performed on the IEEE 39‐bus test system to study the effects of the WTGs on the frequency stability of the system. Results illustrate a more secure and reliable operation of the power system when the wind turbines participate in the frequency regulation task. Moreover, including the frequency response of the wind turbines in the unit commitment problem can reduce the ancillary cost, meanwhile increase the frequency stability of the system. [ABSTRACT FROM AUTHOR]

Inertial and droop control are common methods for improving grid frequency control. Using the first‐order derivative of the frequency in the inertial control loop only investigates the rate of frequency variation, while other useful information is not taken into consideration. Accordingly, in this study, the application of a fractional‐order derivative (between 1 and 2) in the inertial control loop is proposed to have more useful frequency‐based information. To achieve this goal, firstly continued fraction approximations and secondly, the discretization is adopted by using the Tustin Method with Prewarping. Inertia loop and droop loop gain have a significant impact on the operation of the wind turbines and the power system frequency control. Therefore, in this paper, a novel method for the adaptive adjusting of droop and inertia control loops gains in DFIG is proposed. To utilize more frequency error information, fractional‐order adaptive law is proposed to update the loop gains and the inertia control loop. In order to have a robust system, which is permanently stable for every fractional order (FO), is used parameter space method. Simulation results demonstrate the proper performance of the FO‐based adaptive approach to increase the frequency nadir (FN) and decrease the frequency variations. [ABSTRACT FROM AUTHOR]

This work focuses on Distributed Secondary Control (DSC) technique, for frequency regulation and Economic Load Dispatch of Microgrid (MG). The fluctuating nature and large quantity of Distributed Energy Resources (DER) in an autonomous MG result in complex control requirements, demanding fast and robust response. The contemporary DSC schemes are mostly based on Distributed Averaging Integration techniques, with slow response. This paper proposes Distributed Model Predictive based Secondary Control (DMPSC) which effectively complies with the control requirements of MG. DMPSC requires each DER‐node to solve a local optimization problem with the cost function penalizing the deviation of states from their desired values and the differences between the assumed and predicted values. The desired‐states are based on local intermediate‐optimum values, computed using local and neighbouring information. Equality based terminal constraints are introduced to ensure the stability, where each node is forced to reach the desired‐state value at the end of prediction horizon. The terminal‐consensus of the network affirms convergence of the desired‐states to a global optimal point of the network. The asymptotic stability of the proposed control is proved by using the sum of local cost‐functions as a candidate Lyapunov function. Simulation results validate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper presents the voltage‐controlled oscillator (VCO) less phase‐locked loop (PLL)‐based control of voltage source converter. It is used in the distributed power generation system for improved power quality. This control extracts the fundamental component from the sensed load current using three phases to alpha–beta transformation without using VCO, unlike synchronous reference frame–PLL, where fundamental component extraction needs two transformations with the use of VCO. Owing to the absence of VCO in the proposed method, the computational burden of trigonometric operations is very less that results in a faster dynamic response under variable conditions. This characteristic makes it suitable for the distributed power generation system, where fast changes occur frequently. In this study, wind‐based distributed generation system has been taken for study, which comprises of self‐excited induction generator feeding non‐linear load with varying electrical conditions. Using the proposed control, the reactive power compensation, harmonics reduction and load balancing are carried out in the system. In addition to it, neutral current compensation is also accomplished with the help of star–delta transformer connected at the load end. The system performances are investigated under steady state as well as in transient state and results are found satisfactory. [ABSTRACT FROM AUTHOR]

One of the main subjects of Microgrid (MG) islanded operation is its stability. Using the Energy Storage Systems (ESSs) in MGs, the stability can be improved. To ensure the proper operation of the ESSs, their State of Charge (SoC) should be monitored and controlled. In this paper, a new decentralized control method based on the conventional droop method is proposed which considers different types of ESSs used in islanded MG, i.e. ESSs with high power density and high energy density. In the proposed method, the ESS units are divided into two main categories. The master ESS is the main primary frequency control unit and the other ESSs respond to active and reactive power variations of the load and participate in the secondary control of frequency. For each of these categories, a new control method is proposed. The proposed method, including the primary and secondary control, is decentralized, and based on local measurements. Moreover, in the proposed method, a SoC equalization of ESSs is considered. To assess the stability of the MG, a small signal stability model is developed. Three scenarios are simulated to verify the effectiveness of the proposed method in MG frequency control and ESSs SoC balancing. [ABSTRACT FROM AUTHOR]

This paper deals with the modeling of discrete automatic gain control (AGC) controllers for an interconnected power system. The AGC supplementary controllers continuously try to reduce the ACE signal to zero by sending control commands/signals to the speed governor set points. Typically, control signals are sentin the form of discrete control pulses to adjust the generating unit outputs in discrete steps. However, in the preceding AGC studies, ZOH circuit has been misplaced in discrete supplementary controller models. Therefore, control signals feed to the speed governor set points no longer remains in discrete mode or in other words, controller action no longer remains in discrete steps. Therefore, the results and inferences drawn in these studies are erroneous and unrealistic. This paper presents the realistic model of discrete AGC controllers and removes the anomaly in existing works. Furthermore, it is also discovered that inappropriate selection of sampling period of ACE signal degrades the system dynamic performance or even cause system instability. Surprisingly, no proper guidelines/method has been provided yet to select the appropriate sampling period of ACE signals for discrete AGC operation. Here, a maiden attempt has been made to obtain the suitable values of ACE signal&s sampling periods using Shannon&s sampling theorem. [ABSTRACT FROM AUTHOR]

This paper deals with the design and analysis of a virtual synchronous generator (VSG) control strategy applied to a renewable‐based system devoted to energy production in a stand‐alone microgrid context. The studied hybrid energy production system consists of renewable‐based energy production systems, a diesel power plant (DPP), and an energy storage system (ESS). The first part of the study will deal with the design of a single renewable energy source controlled using the VSG control strategy. In the second part, multiple renewable energy sources, similar to the one presented in the first part, will be connected in parallel to form a renewable farm. Finally, in a third part, the studied renewable farm will be integrated in a full hybrid system. In each part of the proposed study, the system power output will be evaluated and the voltage and frequency variations will be carefully analysed. [ABSTRACT FROM AUTHOR]

This paper presents a multi‐time hierarchical stochastic predictive control (MHSPC) scheme for an island microgrid, in which electric vehicles (EVs) can be used as mobile energy storages to improve power balance and realise load‐frequency control (LFC) with micro‐turbines (MTs). At the upper layer, a stochastic model predictive control is proposed to handle the EVs uncertainties on a long time scale, while optimising controllable power adjustment of MTs, the charge/discharge energy of the battery electric storage (BES) unit and guaranteeing EVs to be fully charged at the expected plug‐out time. At the lower layer, the coordination between EVs and MTs for LFC is achieved by a standard MPC framework on a short time scale. In this way, the power balance is met, and the frequency fluctuation is inhibited. Finally, simulation results are presented to illustrate the satisfactory operation of the island microgrid. [ABSTRACT FROM AUTHOR]

The microgrid concept has gained enormous popularity in the power industry due to recent advances in the power electronic converter (PEC) technology and environmental concerns over green‐house gas emissions from power generation. Among microgrids, the hybrid AC/DC microgrid concept has been promoted as a viable concept to reduce energy conversion losses. However, hybrid AC/DC microgrids are susceptible to stability issues during high penetration of dynamic loads (e.g. induction machines). The non‐linear dynamics of induction machines result in sustained voltage/frequency oscillations following disturbances in the microgrid, which is a major challenge for stable operation of the hybrid AC/DC microgrid. The PEC‐based energy storage systems (ESSs) are used as an effective solution for power balancing in the microgrid; hence with the fast response of the PEC, microgrid voltage/frequency could be stabilised rapidly. Thus, a supplementary power oscillation damping (POD) controller is proposed in this paper for the ESS to damp low‐frequency oscillations (LFOs) in the hybrid AC/DC microgrid. The effectiveness of the proposed damping controller is verified using non‐linear simulations considering different penetration levels of dynamic loads and disturbances in a hybrid AC/DC microgrid. Results indicate that the proposed supplementary POD controller can significantly damp the LFOs in the hybrid AC/DC microgrid. [ABSTRACT FROM AUTHOR]

In this paper, real‐time parameter estimation based intelligent controller has been proposed for the optimum automatic generation control (AGC) operation of multi‐area interconnected power system. In earlier AGC studies, supplementary controllers were designed for presumed power system dynamic conditions, such as constant system loadings, fixed values of power system dynamic model parameters. However in practical AGC system, these power system model parameters, namely frequency bias parameter B, steam chest and reheater time constants TSC & TRH, power system time and gain constants Tp & Kp, load sensitivity factor D, etc., continuously varies depending upon the consumer's load demand and number of power generating units participating in AGC. The controller's operation no longer remains optimum as these system parameters changes from their initial values. In view of the above, parameter estimation based real‐time intelligent controller has been designed which automatically adjusts its controller gain settings to its optimum conditions in real‐time after sensing changes in power system model parameters. At first, different methodologies are presented to estimate dominant power system model parameters. Then, presented methodologies are utilised in the design of intelligent controller for AGC system. The proposed controller is successfully tested upon IEEE 39 bus system with various case studies. [ABSTRACT FROM AUTHOR]

The conventional hierarchical control in an islanded microgrid (MG) does not consider the long time‐span dynamics of distributed storages (DSs). The main challenge in control of battery energy storage systems (BESSs) is different levels of stored energy in terms of state of charge (SoC). In power droop control, the energy of the BESSs with lower initial SoC is drained earlier, and their capacities become unachievable. Moreover, using droop control to balance the SoC of BESSs, deviates the steady state frequency and voltage from the nominal values. However, restoration of the MG frequency employing the conventional distributed secondary controllers disturbs SoC‐balancing, since SoC of BESSs are ignored. In this paper, a new distributed storage secondary controller (DSSC) scheme is designed for restoration of the voltage and frequency of a stand‐alone MG, and to provide power‐sharing and SoC‐balancing, using a distributed cooperative architecture. The cooperative DSs are controllable and exchange the information with neighbor DSs through a communication network. The unknown output power of the uncooperative renewable distributed generation (DG) is considered as external disturbance to the DSSC. The designed DSSC is robust against the variation of the communication configuration, and eliminates the necessity to communicate with uncontrollable DGs and loads. [ABSTRACT FROM AUTHOR]

The ability of riding through the grid disturbances can increase the integration of microgrids into the distribution system. Consequently, a grid‐connected microgrid should provide ancillary services such as low voltage ride‐through (LVRT) capability and reactive power support to sustain the power system operations during abnormal grid conditions. The objective of this paper is to propose an LVRT scheme that improves the power quality of the entire microgrid. The developed method is implemented as the controller of the interface voltage‐sourced converter (VSC) of a distributed energy resource and consists of primary and secondary control levels. The former includes the cascaded voltage and current control loops and the droop controller, while the latter controls the reactive power injection during the balanced/unbalanced voltage sags/swells. The proposed scheme is developed based on the independent control of each phase and does not require calculation of symmetrical components. Moreover, it can be employed in the VSC control systems with various reference frames and is effective for droop‐based grid‐connected microgrids with both single‐phase and three‐phase four‐wire configurations. The proposed strategy is implemented using the hierarchical control system and preserves the plug and play capability. Several case studies are presented to verify the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

This paper investigates on an additional active power compensation of a microgrid to a weak grid using fuzzy‐supervisory control. This reduces the economic penalty of microgrid for going over‐contract with the grid in terms of power demand. The objectives of this work are (a) to maximise grid support during periods of over‐contract, (b) to minimise distortions and increase dynamic stability of dc link voltage and (c) to improve the total harmonic distortion (THD) of the dispatched power. The microgrid comprises of a wind energy conversion system (WECS) and Li‐ion battery energy storage system (BESS). During variations in wind speed, power feed into the point of common coupling (PCC) depends upon deviations in the wind power, dc link voltage, violations in grid contract power and the state of charge (SOC) of the battery. The deviations in these inputs are utilised by the supervisory controller to compute additional power support to the grid, by discharging the battery. Performances of the fuzzy‐supervisory controller are compared with a classical‐supervisory controller with similar power dispatch parameters. Further, inverter currents are regulated using a fuzzy proportional‐derivative and integral (FPD + I) controller to reduce distortions and improve dynamic response of the dispatched power. [ABSTRACT FROM AUTHOR]

Till this moment, the model of interconnected power systems in the automatic generation control (AGC) loops relies only on the synchronous generating units. In today's world, a high level of penetration of renewable energy sources (RES) is integrated to the power grids. This paper presents a novel power system model, which includes both conventional generating units and RES for studying the AGC problem of such systems. The control strategy in the AGC loops is based on the proportional–integral–derivative (PID) controller, which is optimally designed by the whale optimization algorithm (WOA). It represents a great challenge to this controller to deal with the RES uncertainties. The effectiveness of the WOA‐based PID controller is compared with other computation evolutionary algorithms‐based PID controller. The system performance is evaluated under different operating conditions. For achieving a realistic study, 1) real wind speed data that extracted from Zafarana location in Egypt are used, 2) solar irradiation and temperature data that extracted from a field test are implemented, and 3) an irregular wave energy condition is applied. The validity of the control strategy is verified using the simulation results, which are carried out using MATLAB environment. [ABSTRACT FROM AUTHOR]

This paper describes an intelligent sensor fault detection and compensation (FDC) scheme for a hybrid grid involving renewable energy (RE) sources with power electronic interfaces. To evaluate the sensor FDC scheme, a wound rotor induction generator (WRIG)‐based wind energy system connected to the hybrid grid is examined. The system employs a WRIG with excitation from DC RE grid via a single, rotor side converter. To analyse the dynamic performance, a decoupled voltage vector control is employed. The sensors involved in the control algorithm may not be ideal and if fault occurs might lead to system collapse. To overcome electrical sensor failure, a robust, intelligent sensor fault control scheme is proposed with ANFIS. A hardware‐free solution with PLL block is proposed for mechanical sensor fault. The ANFIS‐based FDC scheme involves a bank of observers that computes residuals, detects and isolates faults. When fault occurs, the observer output is utilised for the execution of control algorithm thereby avoiding system collapse. The focused system is simulated in MATLAB and experimentally tested with a dSPACE controller for various fault scenarios. The results show the effectiveness of the FDC scheme. [ABSTRACT FROM AUTHOR]

Energy poverty limits the economy and social development throughout the world. Wind turbine reduces the energy costs and facilitates the development of renewable energy industry, which provides an effective solution to energy crisis and environment pollution and develops rapidly in recently years. In this paper, a radial basis function neural network (RBFNN) optimisation model predictive control (MPC) was proposed for large wind turbines. In accordance with the complexity and uncertainty of wind turbine operation, a linear model based on the blade element momentum theory was established and the influencing factors of the proposed model were evaluated. The MPC taking into full account three degrees of freedom control multivariate was enforced by RBFNN prediction model, which meets the requirements of specified operation region. Additionally, the RBFNN prediction model with the memory of complicated rules and changed trend was trained by a great deal of historical data. The RBFNN in combination with MPC solves global optimisation problems and improves the dynamic performance of system. Simulation results for three‐bladed 5 MW onshore wind turbine verified the effectiveness of the proposed method and confirmed the fact that the fatigue loads were significantly reduced in the turbine tower. [ABSTRACT FROM AUTHOR]

In this paper, a decentralized control strategy for inverter‐based distributed generation (DG) is proposed to enhance the accuracy of power sharing under unbalanced load conditions in low‐voltage microgrids. The proposed method includes two important saliences: (1) accurate unbalanced current injection from DGs, and (2) reduction of circulating real and reactive powers in an islanded microgrid. The features are complied with the proposed droop strategy utilized in the control system of each phase of DG converters. Based on the proposed triple‐droop control strategy, the real power sharing in an AC low‐voltage microgrid is significantly improved via P–V control strategy and the reactive power sharing accuracy is enhanced via Q–f control strategy. By this method, the amplitude of the output voltage of each phase of the converters is determined based on the amount of load connected to that phase. In addition, the efficiency of the microgrid is increased due to the circulating current reduction between DGs. A virtual impedance concept is also utilized to improve the accuracy of the proposed power sharing method. The feasibility and effectiveness of the proposed strategy are validated using MATLAB/SIMULINK software for International Council for Large Electric Systems (CIGRE) low‐voltage distribution network benchmark. [ABSTRACT FROM AUTHOR]

This study presents a method for integrating power sharing and participation in primary frequency response of power system for distributed energy resources in microgrids. This controller is based on power‐angle droop and results in thorough power sharing in islanded mode and constant power in grid connected state. It can be employed in microgrids along with the feature of plug and play for any kind of distributed generation resources involving synchronous generators. Also, this paper analyses the stability of the proposed controller and the conventional power‐angle droops in a microgrid with modelling in state‐space form and linearising around an operating point. It has been shown that the proposed controller results in more stability and accuracy than the conventional controllers. Also, eigenvalues are evaluated to find the best controller parameters for the microgrid stability. Finally, the controller response in different operating conditions of a test microgrid is assessed. [ABSTRACT FROM AUTHOR]

The studied isolated hybrid distributed generation (IHDG) model of this paper consists of a wind turbine generator and a diesel engine generator. This work presents a study for improving both frequency and power deviation profiles of the studied IHDG model with the help of capacitive energy storage (CES) unit. A novel derivative‐free meta‐heuristic method, termed as quasi‐oppositional harmony search (QOHS) algorithm, is applied to determine the optimal frequency and power deviation responses by tuning the tunable parameters of the studied IHDG model. The two fuzzy logic controllers (FLCs) are used (one at diesel unit and the other at wind generator side) to generate the output levelling frequency and power command. Each fuzzy control has two inputs, either frequency or power deviation and their respective derivatives. The two proposed FLCs are designed with QOHS algorithm for the studied CES equipped IHDG model. Performance study of the model has been carried out under different perturbation conditions. The results presented in this study demonstrate that minimum frequency and power deviations have been achieved by using the two proposed FLCs for the CES equipped studied IHDG model. [ABSTRACT FROM AUTHOR]

SUMMARY This paper presents a new nonlinear polynomial controller for wind turbines that assures stability and maximizes the energy produced while imposing a bound in the generated power derivative in normal operation (guarantees a smooth operation against wind turbulence). The proposed controller structure also allows eventually producing a transient power increase to provide grid support, in response to a demand from a frequency controller. The controller design uses new optimization over polynomials techniques, leading to a tractable semidefinite programming problem. The ability of the wind turbine to increase its power under partial load operation has been analysed. The aforementioned optimization techniques have allowed quantifying the maximum transient overproduction that can be demanded to the wind turbine without violating minimum speed constraints (that could lead to unstable behaviour), as well as the total generated energy loss. The ability to evaluate this shortfall has permitted the development of an optimization procedure in which wind farm overproduction requirements are divided into individual turbines, assuring that the total energy loss in the wind farm is minimum, while complying with the maximum demanded power constraints. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]