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The synchronization of the Doubly-Fed Induction Generator (DFIG) into the weak AC grid is significantly affected due to the reactive power limitations associated with the built-in converter of the existing Wind Energy (WE) system. This is further restricted due to non-linear loads and Power Quality (PQ) deterioration. Therefore, there is a strong need for a system capable of managing reactive power without disturbing the existing infrastructure of WE sources. This paper proposes a novel reactive power-based solution for synchronizing the DFIG to the weak grid with high WE penetration by mitigating PQ disturbances and managing reactive power at the interconnection point using an additional Distribution-Static Compensator (DSTATCOM). A feed-forward second-order-based adaptive algorithm controls this reactive power compensator. The adaptive control extracts the active and reactive weights of load current to generate the reference signals by continuously tracking grid voltage, wind generation, and DC-link voltage. The proposed novel approach has been successfully implemented in MATLAB and validated with a laboratory-based experimental setup. The transient and steady-state analysis reveals the practical applicability of a proposed novel synchronization approach with a high WE penetration level. • Synchronization of DFIG into the weak AC grid with high WE penetration efficiency and the presence of non-linear load has been achieved within 0.9 s. • Incorporating a feed-forward wind block in the adaptive algorithm to compute WE output power leads to accurateness as high as 99%. • Accurate tracking and adaptive capability of the proposed control can manage reactive power injection, thereby reducing the DSTATCOM size by 65%. • The conventional PLL-based voltage synchronization method causes side-band oscillations with low SCR at the fundamental grid frequency. This paper introduces a PLL-less adaptive synchronization method to address this issue. [ABSTRACT FROM AUTHOR]

This paper demonstrates the viability and effectiveness of a novel adaptive control approach applied to power electronic converters. A methodology based on the formulation of a Lyapunov-based approach is showcased to represent the operation of a new adaptive controller for the regulation of two power converter topologies (Buck and Boost). The models of the Buck and Boost converter topologies include the parasitic parameters that represent the non-ideal components. The basic idea of the control approach is to demonstrate adaptive stabilization for the proposed non-linear system. The most important design specification to stabilize the system is to track the reference trajectory in such a way that the error on the output variable converges asymptotically to zero. This adaptation mechanism is explicitly designed so that the asymptotic stability of the equilibrium condition is guaranteed according to the Lyapunov theorem and sensitivity theory. The details of the design algorithm are explained in the paper. The proposed control approach has been compared to other Lyapunov-based control techniques proposed in literature for the same non-ideal converters. The results show that the proposed controller provides better level of robustness and performance than the other well-established Lyapunov based controllers. To verify the effectiveness of the controller in real time, a test bench has been set up with prototypes of both converters and the controller has been implemented using the Arduino microcontroller and the control system driven through the Matlab/Simulink platform. • Proposal of a novel adaptive control approach for DC–DC power electronic converters. • The controller is asymptotically stable according to Lyapunov. • Inclusion of the parasitic parameters in the converter models. • First application of the proposed control approach to DC–DC converters. • Successful performance of the proposed control proven by experimental results. [ABSTRACT FROM AUTHOR]

This paper proposes a voltage compensator for converters in multi-converter DC microgrids (MG), which enhances the DC-MG behavior under fault conditions. Among the four existing categories in the classification of the faults, this paper focuses on those faults that affect voltage generation of converter-based distributed generation units (DGUs). Such faults conceptually occur from the terminal voltage reference to actual voltage generated by DGUs. To compensate the adverse effects of the faults, an adaptive scheme is proposed, which considers the most general case of the faults by using the time-varying multiplicative and additive fault models. The proposed scheme benefits from an integrated structure, which does not require separate fault detection, isolation, and identification blocks. As an advantage of the proposed approach, it is designed independent of the primary and secondary controllers of DGUs, and hence its performance is not affected by using different primary and secondary controllers. The effectiveness of the proposed scheme is verified under various fault conditions and uncertainty in the system parameters. Using the proposed scheme, the results show that the performance of system under the fault condition is similar to that of the normal operation. • An adaptive voltage control compensator scheme is proposed for DC microgrid. • The considered faults affect the voltage generation of DGUs. • The faults are modeled by time-varying multiplicative and additive components. • The proposed scheme does not need any separate fault detection and isolation modules. • To validate the conducted analysis, various case studies are provided. [ABSTRACT FROM AUTHOR]

• Frequency adaptive: multioscillatory control and repetitive control are studied. • Methods are applied for a grid-tie converter. • Memory and computational burden analysis of both methods are presented. • A linear prewarping for frequency adaptive multioscillatory control is proposed. • Practical implementation hints are provided. The paper describes two main approaches of periodic control under variable frequency conditions: frequency adaptive multioscillatory control (FAMOSC) and fractional delay repetitive control (FDRC). The methods are applied in the control system of a grid-tie converter to increase the quality of phase currents in case of distorted grid voltages. The paper compares structures, performance and implementation of FAMOSC, FDRC and the conventional approach of repetitive and multioscillatory control. Performances of the control systems are illustrated with experiments on a laboratory test bench. The article describes tuning process of FDRC and FAMOSC with the usage of Particle Swarm Optimization algorithm. A detailed analyse and research of the techniques in terms of computational complexity is presented. Practical hints for implementation and resource optimization of both techniques on DSP are included. For FAMOSC a fast implementation of prewarping is proposed. [ABSTRACT FROM AUTHOR]

• An adaptive droop method based on a superimposed frequency is proposed to balance the SoC among distributed BEUs. • By using the introduced AC reactive power to adjust the reference voltage according to differences in line resistance. • Voltage restoration is performed to maintain the average output voltage of the BEU at the nominal value. The conventional droop method for load sharing control in DC microgrid suffers from poor power sharing and voltage regulation, which affects the State of Charge (SoC) balance of distributed Battery Energy Units (BEUs). In this paper, an adaptive droop method based on superimposed frequency is proposed to balance the SoC among distributed BEUs. Accurate current sharing is achieved by using the introduced AC reactive power to adjust the reference voltage according to differences in line resistance. With the proposed SoC balance control method, the SoC balance among BEUs can be guaranteed by the accurate current sharing regardless of the different line resistances in the DC microgrid. In addition, voltage restoration is performed to maintain the average output voltage of the BEU at the nominal value. The effectiveness of the proposed control system is verified by simulation and HIT experimental tests. [ABSTRACT FROM AUTHOR]

• The paper proposes a novel grid simulator and control strategy that can generate various fault waveforms with high performance. • The proposed simulator structure and control strategy are modular and adopt a single three-phase PWM module and an H-bridge module with a shared DC bus. • Model predictive control (MPC) generates high-quality, fast voltage waveforms for accurate voltage tracking. • Model reference adaptive control (MRAC) is used to estimate the network side inductance value, which improves the system's robustness. • A switching distribution method is proposed for feedforward control to enhance reliability. • Simulation and experimentation demonstrate that the proposed simulator can effectively generate various fault waveforms, making it ideal test equipment for renewable energy or power electronic equipment. • The research showcases technical innovation and has practical applications for renewable energy grid connection. The rapid and large-scale renewable energy development poses new challenges for the traditional power grid, particularly with the increasing utilization of high-power electronic interfaces. To address this, a novel grid simulator topology and its control strategy are proposed, which can generate various required waveforms with high performance. The grid simulator adopts a modular multilevel structure, a three-phase PWM module, and an H-bridge module with a shared DC bus. Model predictive control (MPC) outputs high-quality, fast voltage waveforms for accurate voltage tracking. Additionally, the model reference adaptive control (MRAC) is integrated into the PWM converter in the pre-stage to estimate the network side inductance value, which is used to improve the system's robustness. Moreover, a switching distribution method is proposed for feedforward control to enhance reliability. Through simulation and experiment, it is verified that the proposed power grid simulator and its control strategy can effectively and accurately generate various fault waveforms such as voltage drop, voltage abrupt change, and abrupt frequency change. As a result, it can be used as test equipment for renewable energy or power electronic equipment. [ABSTRACT FROM AUTHOR]

Highlights • API controller is developed to balance Neutral Point voltage in PV fed NPC inverter. • API controller is mathematically modelled and tested with closed loop stability. • API balances the NP voltage with less settling time and reduces grid current THD. • A dq axes power controller is also implemented for power balance along with MPPT. • The performance of the controller is validated in simulation and experimentation. Abstract In the context of current harmonics mitigation in inverter, neutral point clamped (NPC) inverter is the promising one because of its robustness. Owing to the advantages of NPC inverter, this paper considers a PV fed grid connected NPC inverter. However, the main concern with the NPC inverter is the unbalance in the DC link capacitor voltage due to non-idealities such as DC offset in modulating signals, dissimilarities in the DC link capacitors and asymmetric gating signals, which lead to non-zero neutral point voltage. To address this issue, this paper proposes a simple adaptive proportional integral (API) controller and operates in conjunction with the dq axes power controller for PV fed Grid connected NPC inverter. Comprehensive mathematical expressions are derived for the design of API controller and the control parameters are adjusted continuously based on maximum PV power, PV voltage and modulation index for achieving the faster dynamic response. The closed loop stability of the proposed API controller is verified under the deviation in neutral point voltage using root locus plot. The effectiveness of the API with dq axes power controller is analysed and validated through MATLAB simulations and experimentation under the various dynamic operation of the PV- grid interactive system. [ABSTRACT FROM AUTHOR]

Highlights • The applied control strategy does not depend on any tuning parameter. • The converter does not require any separate output filter. • The series transformer impedance is controlled indirectly by flux (voltage) injection to its secondary. • This system does not require any signal analysis tool for voltage disturbances extraction. • The "smart branch" can conduct the harmonics directionally. Abstract A novel "Smart Branch" is introduced in this paper which compensates for various power quality disturbances. This "Smart Branch" includes a series transformer which its impedance is controlled indirectly by voltage injection to its secondary. By using a finite control set-model predictive controller (FCS-MPC), the "Smart Branch" can be controlled adaptive, flexible and straightforward. The "Smart Branch" is installed at the PCC, where the load current and the PCC voltage can be measured locally without using a communication channel. The "Smart Branch" controller tracks pure sinusoidal waveforms as its references. Thus the "Smart Branch" hardly produces harmonics and therefore its output filter can be eliminated. The controller can be used for multi-objective optimization of power quality in power systems and especially in microgrids. A droop based method is developed for adjusting the objectives' weightings in the cost function of the MPC. In the last part of the paper, by using the extensive simulations and scenarios, the figure of merits of the "Smart Branch" is proved. [ABSTRACT FROM AUTHOR]

Highlights • The paper presents a PMU-based autoreclosing method. • The paper presents a comprehensive auto-reclosing method for all fault types. • The proposed method can enhance the reliability of distribution systems. • Effects of thermal stress and stability indices are investigated before reclosing. • The proposed method has been evaluated using real-time HIL simulation method. Abstract This paper presents an adaptive auto reclosing scheme (AARS), applicable to active distribution systems, which are equipped with Phasor Measurement Units (PMUs). The scheme differentiates between temporary and permanent faults by taking into account the operational conditions of the network when determining the reclosing dead time. The performance of the proposed scheme is assessed through a real-time hardware-in-the-loop (HIL) simulation test setup. [ABSTRACT FROM AUTHOR]

The significant penetration of renewable energy sources (RES) makes the AC/DC hybrid system a typical low-inertia and poor-damping system. The multi-terminal direct current system (MTDC) is critical in connecting multiple AC systems and transferring bulk power among different AC regions. Conventional control often involves a tradeoff between response time and damping oscillations. To solve these issues, an AI-designed adaptive dynamic reference (ADR) control is investigated in this paper. It is designed with a controllable settling time and is able to mitigate the power oscillation during step change of power reference. In detail, an ADR module is utilized to generate the reference signal, which is input to dual closed-loop control. Raw data is generated from the simulation to build a data-driven surrogate model to map ADR parameters directly to settling time and overshoot in dynamic response. Once the surrogate model is trained, it is able to evaluate VSC's dynamic performance within 0.003s, which is much faster in comparison with online simulation. A meta-heuristic optimization method is then adopted to find the optimal control parameters based on the surrogate model. The effectiveness of the proposed ADR control and its AI-aided parameter design is validated by the real-time digital simulation and hardware-in-loop experiment. • An ADR-DCLC strategy is proposed for the modular multilevel converter-based voltage source converters (MMC-VSCs) in an MTDC system. • The data-driven model is developed to reflect the direct mapping relationship between ADR parameters and dynamic performance index. • An AI-aided parameter optimization method is implemented. [ABSTRACT FROM AUTHOR]

For islanded microgrids with inverter-based distributed generators (DGs), this article focuses on the fast finite-time secondary voltage and frequency control problem considering system uncertainties. The distributed controller is designed based on the command filtered backstepping procedure, and a disturbance observer is constructed to estimate the lumped system uncertainties (including parameter perturbations, unmeasurable variables, etc.). In addition, the singularity issue derived from differentiating the virtual control law is avoided by using a smooth switch function. The proposed controller guarantees that the tracking errors of voltage and frequency converge to a small region around the origin in a finite time, while achieving desired active power sharing ratio. Case studies are conducted on a microgrid system to demonstrate the effectiveness of the proposed strategy in the presence of load changes and parameter perturbations. • This paper aims at achieving fast finite-time secondary control of islanded microgrids. • The proposed method is free of chattering and singularity issues. • The disturbance observer is constructed to enhance the robustness of voltage control. • Case studies are conducted to verify the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

• Increased share of new energy generation leads to increased VSG adoption. • The effects of inertia and damping are elucidated through the transfer function. • Adaptive control is introduced on the basis of the original MPC-VSG control. • Adaptive control includes inertia damping control and weight coefficient control. • Improved MPC-VSG control can optimize the dynamic response of the power and frequency. For the power imbalance caused by the load switching in microgrids (MGs), which in turn causes the frequency crossing limit problem. In this paper, we propose an improved model predictive control (MPC) based on the existing MPC-VSG control, combining adaptive inertia damping control and adaptive weight coefficient control for joint control, and adjusting the inertia damping coefficient of VSG in real-time by adaptive inertia damping control. In MPC control, the measured parameters at the current moment are used to predict the state quantities at the future moment, and then the target function is designed with the angular frequency deviation and the VSG power output as performance indicators, and the weight coefficients in the target function are updated in real-time by detecting the frequency deviation. After solving the objective function to obtain the required power compensation, the power reference value of the VSG is updated to optimize the dynamic response of the frequency. Experiment and comparison analysis with two existing methods show that the proposed method can further optimize the frequency response and smooth the output power of other power supply components in the microgrid when they are disturbed. [ABSTRACT FROM AUTHOR]

This paper introduces a new adaptive control strategy for power-sharing in a hybrid AC/DC microgrid (HMG). The existing interlink converter (ILC) control methods exhibit limitations under heavy load and contingency conditions. To overcome this limitation, a bidirectional control strategy is proposed for the ILC, which effectively coordinates battery energy storage systems (BESSs) in both sub-grids while mitigating stress on the ILC and BESSs. The control strategy utilises the state of charge (SoC) and instantaneous power of the BESSs to stabilise frequency and DC voltage on the AC and DC sub-grids, respectively, enabling autonomous operation and plug-and-play capability. Stability analysis employing root locus and a stress level relaxation index for BESSs are presented. Performance evaluation based on the moving mean square error criterion validates the effectiveness of the control strategy. Simulation results using MATLAB/SIMULINK demonstrate the superior performance of the proposed strategy in regulating both voltage and frequency within the system over the existing control approaches. Furthermore, the proposed approach significantly reduces stress levels on the BESSs in different operation conditions. • Enhancing the stability of hybrid AC/DC microgrid. • Proposing a new adaptive strategy for ILC control. • Proposing an autonomous control system based on BESS characteristics. • Easing Stress on the BESSs by deploying an adaptive power management scheme. • Assessing stress level relaxation and voltage and frequency regulation deviations. [ABSTRACT FROM AUTHOR]

The paper presents a data-mining model based adaptive protection scheme enhancing distance relay performance during power swing for both compensated and uncompensated power transmission networks. In the power transmission network, the distance relays are sensitive to certain system event such as power swings, which drive the apparent impedance trajectories into the protection zones of the distance relay (zone-3) causing mal-operation of the distance relay, leading to subsequent blackouts. Further, three-phase balanced symmetrical fault detection during power swing is one of the serious concerns for the distance relay operation. This paper proposed a new adaptive protection scheme method based on data-mining models such as DT (decision tree) and RF (random forests) for providing supervisory control to the operation of the conventional distance relays. The proposed scheme is able to distinguish power swings and faults during power swing including fault zone identification for series compensated power transmission network during stress condition like power swing. The proposed scheme has been validated on a 39-bus New England system which is developed on Dig-Silent power factory commercial software (PF4C) platform and the performance indicate that the proposed scheme can reliably enhance the distance relay operation during power swing. [ABSTRACT FROM AUTHOR]

Voltage source inverters (VSIs) are connected to the weak grid in parallel. The interaction between VSIs and the grid can result in frequency coupling oscillations, threatening the stable operation of the system. The conventional methods of oscillation suppression are unable to automatically adjust the parameters in response to changing systems, nor can they effectively adapt to multi-mode frequency coupling oscillations. This paper proposes a novel adaptive control strategy to suppress frequency coupling oscillations. The strategy in the suppression device enables automatic adjustment of the oscillation current's reference value, allowing it to adapt to diverse operational conditions of the grid-connected system. The strategy is not limited by the modeling precision and the steadiness of the controller structure. Furthermore, the self-stability and interactive stability are analyzed by using the generalized Nyquist criterion (GNC). It is found that the influence of the interactive current on the stability analysis cannot be ignored. Finally, considering the number of VSIs, load mutation, and existing suppression method, the suppression effect of the proposed adaptive control strategy is verified by experiments. • A novel adaptive control is proposed to suppress frequency coupling oscillation. • The strategy is applied to the plug-and-play device and is adapted to various cases. • The strategy is not limited by the modeling precision and the controller structure. • It is found that the interactive current badly affects the stability of the system. [ABSTRACT FROM AUTHOR]

• The UIPC is used as the main component for interconnecting of AC and DC sub-grids. • A robust nonlinear model reference adaptive control strategy is offered for controlling the UIPC. • A novel configuration for the DC link power converter is suggested. • A harmonic-based modeling method is used to model the UIPC's power converter. This paper focuses on the control of unified interphase power controller (UIPC) in isolated hybrid microgrids (HmGs), where the UIPC is used as the main component for interconnecting of AC and DC sub-grids. The investigated HmG encompasses two AC sub-grids and one purely storage DC sub-grid (PSDC) and multiple adjustable loads. A robust nonlinear model reference adaptive control (NMRC) strategy is offered for controlling the UIPC, keeping an acceptable two-way power exchange control with uncomplicated topology. Further, a novel configuration for the DC link power converter is suggested using the dual-active-bridge topology. Also, a harmonic-based modeling method is used to model the UIPC's power converter. The proposed configuration provides bidirectional power flow, increased power density, straightforward adaptation of zero-voltage switching, and direct access to cascading and parallelism to increase the ratings and reliability of UIPC. The simulation results illustrate the feasibility of the suggested topology for isolated HmGs. [ABSTRACT FROM AUTHOR]

This paper presents the stability augmentation of pitch angle control for a permanent magnet synchronous generator (PMSG)-based wind turbine system (WTS) with pitch actuator uncertainty via L 1 adaptive scheme. To do this, a novel L 1 adaptive scheme is firstly proposed to regulate the pitch angle at above-rated wind speed conditions and maintain the rated rotor speed in the presence of pitch actuator uncertainties in the obtained pitch system. Next, a non-affine PMSG system with uncertainties is utilized to represent the pitch regulated variable-speed WTS. Then, the L 1 adaptive scheme is proposed as a stability augmentation system. At this time, the bound conditions are presented to prove the stability and performance evaluation of the proposed L 1 adaptive scheme. Finally, through the simulation of the 20 − MW PMSG-based WTS, the proposed algorithm proves its efficiency and applicability compared to the existing control methods. • This study is to effectively regulate the pitch angle and extract the maximum power from the 20MW WTS. • The proposed adaptive control scheme introduces the SAS method to improve the transient and steady-state performance of the system. • The proposed stability augmentation scheme minimizes the frequency of adaptation estimations and gain values required. • The proposed scheme is evaluated under various environmental conditions, such as gust wind, step wind, and varying wind speed. • The proposed algorithm is provided to prove its efficiency and applicability compared to existing control methods through MATLAB/SIMULINK simulation of the 20 − MW PMSG-based WTS. [ABSTRACT FROM AUTHOR]

Highlights: [•] This paper presents an adaptive chaotic artificial bee colony (ACABC) algorithm. [•] Chaotic local search is adopted to avoid premature convergence in this method. [•] A constraints handling method for SHS is introduced in this paper. [•] The efficiency of ACABC had been compared with established algorithms. [•] The performance of ACABC had been verified by a hydrothermal power system. [ABSTRACT FROM AUTHOR]

Abstract: The transient behavior of many large scale systems is heavily influenced by perturbations and in particular, usually, due to changes in operating points. Load Frequency Control (LFC) in power systems is very important in order to supply reliable electric power with good quality. The goal of LFC is to maintain zero steady state errors for frequency deviations in each control area. Several control strategies, such as classical control, optimal control, suboptimal control, adaptive control, variable structure control etc. have been employed in the past to explore an optimum controller for LFC. In practice LFC systems use simple Proportional Integral (PI) controllers, Proportional Integral Derivative (PID) controllers etc. This paper presents a method based on Type-2 Fuzzy System (T2FS) for Load frequency control (LFC) of power systems including Superconducting magnetic energy storage (SMES) units of a two-area interconnected reheat thermal system. This paper proposes a Type-2 (T2) fuzzy approach for load frequency control of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC), Boiler Dynamics (BD) and SMES. The salient advantage of this controller is its high insensitivity to large load changes and plant parameter variations even in the presence of non-linearities. The proposed method is tested on a two-area power system to illustrate its robust performance with various area load changes. The performance of the Type-2 (T2) fuzzy controller is compared with optimal PID (Khamsum’s optimal PID) controller and Fuzzy PI Controller (Type-1 Fuzzy) controller in the presence of GRC, BD and SMES. Simulation results confirm the high robustness of the proposed SMES controller with small power capacity against various disturbances and system uncertainties in comparison with SMES in the previous research. [Copyright &y& Elsevier]

Highlights • An adaptive active fault-tolerant control strategy is proposed to improve work reliability. • A new generalized-perturbation based dynamic model for MPPT control is established. • The control law doesn't require specific information about actuator's fault pattern or degree. • The control law gains can adaptively adjust by feedback to reduce fault compensation delay. • It ensures a smooth and robust control process whether in actuator normal or fault condition. Abstract In order to improve the dynamic performance and reliability of the maximum power point tracking (MPPT), this paper proposes an adaptive active fault-tolerant control (AFTC) strategy of the wind power generation system to overcome uncertain problems, including potential partial loss of actuator effectiveness, unknown modeling errors and external disturbances. The AFTC method is designed according to a new dynamic model of angular speed tracking for wind power generation system based on generalized perturbation. It neither requires the actuator fault information detection, nor relies on the system model parameters and external disturbance identification. In terms of the on-line estimation of the disturbance boundary amplitude and the nonlinear state feedback based on MPPT tracking error, the gain of the switching control is adaptively adjusted to speed up the convergence of the system and reduce the delay of the fault compensation. A first-order integral process is involved in the AFTC law to further weaken the chattering of output signal amplitude, hence smooth the torque and improve the tracking accuracy during generation. In addition, the global stability of the closed-loop control system based on AFTC is proved by the Lyapunov approach. By comparing with the conventional linear PID control and the nonlinear dynamic state feedback control (NDSFC), the case studies simulation results validate the great MPPT fault-tolerant capability even subject to partial loss of actuator effectiveness, and separately show the strong robustness and self-adaptation of the proposed adaptive AFTC method. [ABSTRACT FROM AUTHOR]

Highlights • It is proposed the application of a novel technique, such as the differential evolution for tuning a fuzzy logic control for synthetic inertia. • It is applied to two different power systems in order to understand the differences and the impact of the controller. • It is included a full model of a wind farm including the power interface. In this way, it is observed several differences compared to an ideal case. Abstract The transformation of the traditional transmission power systems due to the current rise of non-synchronous generation on it presents new engineering challenges. One of the challenges is the degradation of the inertial response due to the large penetration of high power converters used for the interconnection of renewables energy sources. The addition of a supplementary synthetic inertia control loop can contribute to the improvement of the inertial response. This paper proposes the application of a novel Fuzzy Adaptive Differential Evolution (FADE) algorithm for the tuning of a fuzzy controller for the improvement of the synthetic inertia control in power systems. The method is validated with two test power systems: (i) an aggregated power system and its purpose is to understand the controller-system behavior, and (ii) a two-area test power system where one of the synchronous machine has been replaced by a full aggregated model of a Wind Turbine Generator (WTG), whereby different limits in the tuning process can be analyzed. Results demonstrate the evolution of the membership functions and the inertial response enhancement in the respective test cases. Moreover, the appropriate tuning of the controller shows that it is possible to substantially reduce the instantaneous frequency deviation. [ABSTRACT FROM AUTHOR]

In this paper, an online adaptive optimal controller is firstly designed to optimize the performance of an automatic voltage regulator (AVR). Towards this end, an optimal quadratic tracking problem is defined based on the error between the synchronous generator’s terminal voltage and its desired value. Then, this optimal control problem is solved using an adaptive dynamic programming (ADP) method, called the policy iteration technique. Using this technique, the optimal performance is achieved without knowledge of the AVR parameters. To eliminate the steady state error between the AVR output and its desired value, a modification is made in the original policy iteration technique base on the integral action control and another adaptive optimal controller is designed. In addition, an approach is proposed to represent a large-scale power system through several Single-Machine Infinite-Bus (SMIB) systems. The equivalent SMIB system then may be linearized through modal analysis to be employed by the proposed control scheme. Simulation results show that the designed adaptive optimal controllers are so effective and can be used in practical power systems. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a generalized formulation to determine the optimal operating strategy and cost optimization scheme for a MicroGrid. Prior to the optimization of the MicroGrid itself, models for the system components are determined using real data. The proposed cost function takes into consideration the costs of the emissions, NO x , , and , start-up costs, as well as the operation and maintenance costs. A daily income and outgo from sold or purchased power is also added. The MicroGrid considered in this paper consists of a wind turbine, a micro turbine, a diesel generator, a photovoltaic array, a fuel cell, and a battery storage. In this work, the Mesh Adaptive Direct Search (MADS) algorithm is used to minimize the cost function of the system while constraining it to meet the customer demand and safety of the system. In comparison with previously proposed techniques, a significant reduction is obtained. [Copyright &y& Elsevier]

• The stability of the proposed controller is proved by considering I/O saturations. • The controller is reflected to solve LFC problem in multi-area power system. • The frequency stability is provided without using the model of power plant. In this paper, a Data-Driven Adaptive Controller is proposed for wide-area Multi-Input and Multi-Output (MIMO) non-linear systems featuring input–output saturations. Complexity has always been a major concern in the modeling and control of real-world industrial processes. Traditionally, researchers look for simplified and enough precise models of these systems. However, with the significant advancement in sensor and communication technologies, a considerable amount of data is available from the process which may compensate for the lack of precise models. The emerging data-driven control systems perform both identification and control actions based on data collected from the process, making the system less dependent on a pre-identified model. In this context, an efficient MIMO Data-Driven Adaptive Control (MIMO-DDAC) is designed in this paper for stabilizing a class of unknown non-linear systems. A recursive modeling/control process is proposed for the MIMO systems in the presence of saturation in sensors and actuators, and its stability and performance are mathematically proved. This approach is applied to the load frequency control problem in an interconnected multi-area power grid in the presence of governor saturation, load and parametric uncertainties. Simulation results reveal the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive control technique for the variable series capacitor using a recurrent neural network (RNN). Since, the parameters of the controller are determined by Genetic Algorithm (GA), which is one of the optimization algorithms, they are optimum only for that operating point and it is not possible to obtain good control performance against variations in the operating and fault point. The adaptive controller proposed in this paper consists of an optimum controller using GA and an RNN. As the RNN was on-line training, robust control performance can be achieved for various operating conditions. The effectiveness of this control method is demonstrated by considering simulation of a multi-machine power system. [Copyright &y& Elsevier]

To enhance the delay-dependent stability of interconnected microgrids, a novel adaptive control strategy is designed in this paper. Firstly, an adaptive robust control model is established to coordinate multi-MGs energy management. By regulating control parameters, Lyapunov stability without delay can be guaranteed. Secondly, stability evaluation methods considering uncertainty, such as mode perturbation and communication failure, are proposed to analyze delay-independent system. On this basis, to eliminate the adverse effects of delay caused by wide-area measurement, an active disturbance rejection stabilizer is designed here, which can be self-adjust adaptively via delayed time, and doesn’t require multiple iterations in the parameters regulation. Through Schur complement theorem, the analytic expression of feedback gains is obtained from linear matrix inequalities. Finally, with an IEEE 118-node test feeder as an example, the numerical simulation verifies the feasibility of the proposed stabilizer under the cases of long delays. [ABSTRACT FROM AUTHOR]

• Establishing the adaptive VSG control-based electromechanical transient model for energy storage. • Establishing a small-signal model and analyzing the dynamic characteristics of VSG output caused by grid fluctuations. • Proposing adaptive control of VSG to provide frequency support and maintain SOC of BESS. With the steady deployment of intermittent generation, the inertia of the grid decreases, and the stability problem is becoming increasingly critical within system operation. The virtual synchronous generator (VSG) control is a means to control battery energy storage systems (BESS) to retain the dynamics of conventional synchronous generators and ensure a smooth transition toward converter-dominated power systems. Since the parameters in the VSG control can be varied, it can be turned to be an alternative to obtain an optimal response for the overall performance of frequency when the operating conditions change. In this paper, the adaptive VSG control is proposed to improve the dynamic characteristic of active power at a certain capacity. For this purpose, firstly, the electromechanical transient model of BESS based on VSG control is built. Afterward, the effect of inertia under grid disturbance by transfer function is analyzed, and the influence of key parameters on dynamic stability is identified. Finally, the proposed adaptive VSG control is verified in the modified IEEE 4-machine 2-area system and an actual power grid example. The simulation results show the effectiveness and great potential of this model in improving frequency stability. [ABSTRACT FROM AUTHOR]

In this paper, a robust predictive dual-loop control method based on Lyapunov function stability and energy equilibrium for active power filter (APF) is proposed to improve the anti-interference performance and self-adaptive capability of system. The proposed control method mainly includes robust predictive current control based on Lyapunov function stability (RPCC-LFS) in the inner current loop and energy equilibrium proportional-integrator (PI) control in the outer dc-link voltage loop. The RPCC-LFS is proposed to enhance self-adaptive capability when the output filter inductors vary, speed up the dynamic response, and improve the tracking accuracy when the loads fluctuate. The energy equilibrium PI controller is proposed to maintain the dc-link voltage stable and suppress the transient impulse. The stability and dynamic response of the proposed control system are analyzed in detail, and the proper control parameters are selected. A specific hardware and software design program based on double-core processors DSP + FPGA is thoroughly given out. Finally, the comparative simulations and experiments verified the validity of the proposed method. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of controlling power systems that contain Voltage Source converters based on High Voltage Direct Current (VSC-HVDC). Specifically, the system under study consists of two power grids and two VSC stations connected via a long HVDC cable. Using the backstepping design technique, we design a nonlinear controller that meets three control objectives: (i) tight output voltage regulation of the HVDC cable; (ii) guarantee the power factor correction (PFC) at both sides of the HVDC system; (iii) regulation of the active power at the inverter station. Furthermore, we design a high-gain observer that provides the controller with online estimates of all states based on the measurements of the HVDC input voltage and current in the cable. Finally, one provides a stability analysis of the output feedback controller and simulation results highlighting its performances. • A nonlinear control strategy for a VSC HVDC transmission system is proposed. • A nonlinear observer is employed for the online estimation of the HVDC cable state. • Output feedback is performed based on the online estimation provided by the nonlinear observer. • The robustness of the output feedback controller is validated by simulation. [ABSTRACT FROM AUTHOR]

• Programmed trajectory motion control (PTMC) performs secondary generation control. • PTMC achieves the target state faster, compared to conventional methods. • PTMC is well suited for synchronization of islands with the mains udder disturbances. The paper presents the concept of adaptive control in electrical power systems, based on programmed trajectory motion of synchronous generators. The feasibility of the method is tested in a range of simulation experiments. The key feature of the technique is the use of a simple reference model which defines the dynamics of the controlled parameters. As a result, the voltage vector angle, velocity and acceleration are delivered to the exact, rather than approximate, target values in a predictable, coordinated, robust and efficient manner. Compared to other adaptive methods, such as model predictive control, the technique makes a more efficient use of computational resources, which makes it particularly beneficial if implemented at lower levels of control system hierarchy. It also shows a promising level of robustness against disturbances during the control process. We envisage that the most relevant practical applications are the stabilization and synchronization of small to medium size synchronous machines connected to distribution grid, and management (corrective control and resynchronization) of islanded sub-systems, such as microgrids. Simulations also indicate relatively short control time and improved stability against perturbations. With a proper choice of reference model, the need for bi-polar control action does not arise and the target values are achieved by uni-polar action only. Both the stabilization and the synchronization tasks are accomplished by means of one control algorithm, which improves the quality of control, especially in post-emergency operating conditions. The time-domain modeling results reported in the paper were obtained from software-based simulators. [ABSTRACT FROM AUTHOR]

• A DRL based approach is applied to adaptive control of STATCOM-ADC parameters. • An ANN-based estimator is proposed for system identification. • The proposed novel control agent is adaptive and robust. • An online application strategy is proposed to avoid frequent parameter adjustment. Due to the fluctuation characteristics of the wind turbine (WT) production, the design of the control system needs to ensure the stability of the power system at different wind speeds. In this context, a WT-oriented adaptive robust control agent for a static synchronous compensator having additional damper controller (STATCOM-ADC) is proposed in this paper. An artificial neural network based estimator for system identification which can identify the equivalent transfer function of the whole system in real time is used in this paper. Then a Deep Deterministic Policy Gradient (DDPG) algorithm is adopted to train the agent on learning the adaptive robust control strategy for STATCOM-ADC. Compared with other control strategies, the proposed method has modelled self-learning abilities, and the parameter settings provided by the agent for one operation state of the system are still applicable to other states. Simulation results on the actual wind farm located in China Ningxia province show that the proposed method can enhance the stability of the system under different fault conditions and wind speeds. [ABSTRACT FROM AUTHOR]

• Adaptive drooping control scheme is proposed based on the variable droop constant values. • The variable droop constant is evaluated according to the converter headroom with DC voltage deviations. • The proposed variable droop constant values switch the operating modes of the inverter and rectifier sides VSCs for accomplishing the proposed objectives. • A ±400 kV four-terminal test network has been developed in the PSCAD simulation platform to verify the designed control method. Simulation results have validated the performance of proposed control technique in the converter outage with inverter and rectifier side and fault at WF-VSC and GS 1 -VSC. • The simulation results have verified that the proposed strategy worked effectively and control the DC voltage deviation and maintain the active power-sharing among VSCs in the MTDC system. The generated power from multiple renewable energy sites can be collected and integrated into the conventional alternating current grid by using a multi-terminal high voltage direct current (MTDC) system based on the voltage source converter (VSC). Following the converter outage or large disturbance, this system with a fixed drooping control scheme suffers overloading of the power converter, resulting in the imbalance of active power-sharing and large deviation of direct current voltages. To improve control performance, this paper proposes a novel adaptive drooping control approach according to the variable droop constant to keep balance active power-sharing and manage the alternation of DC voltage in huge power disturbances. The designed scheme is implemented on the both rectifier side and inverter side converters. The variable droop constant is evaluated according to the converter headroom with DC voltage deviations. The performance of the planned control method is compared with the fixed and variable droop control techniques. A 400 kV four-terminal VSC-MTDC test network is developed to verify the effectiveness of the designed control method. The proposed control technique, based on the PSCAD simulation results, can achieve good performance in the rectifier and inverter converter outage and faults operating scenarios. [ABSTRACT FROM AUTHOR]

Overall block diagram. [Display omitted] • An equivalent SMO to suppress the chattering and accelerate the reaching rate. • An adaptive back EMF to estimate back EMF signal. • An improved PLL with signal suppressor to observe the speed and position. To achieve high-precision speed and position control for the surface-mounted permanent magnet synchronous motor (SPMSM), this paper proposes a sensorless vector control strategy based on a composite sliding-mode observer (SMO) and an improved phase-locked loop (PLL) structure. Different from the existing sensorless methods, the proposed control strategy can further improve the accuracy of observation position and speed. First, a new sliding-mode function and the equivalent control are introduced to weaken the chattering and accelerate the reaching rate. Then, a sliding-mode current observer based on an adaptive law control is designed to observe the back electromotive force (back EMF). Meanwhile, the adaptive law can ensure the stability of the system in different states and reduce the system chattering. Second, an adaptive back EMF observer is presented to accurately observe the estimated back EMF. Furthermore, the stability of the two observers is proved by employing the Lyapunov second method. Next, the variable gain PLL with the signal suppressor is used to obtain an accurate rotor position and speed. Finally, the simulations and experiments are implemented to validate the performance of the proposed control strategy, in terms of speed and position tracking as well as anti-disturbance ability. [ABSTRACT FROM AUTHOR]

In order to ensure that the wind power system (WPS) can realize maximum power point tracking (MPPT) under generator side fault, an MPPT control system with adaptive active fault tolerance capability is proposed in this paper. The basic idea of the proposed control strategy is that a perturbation term containing model uncertainties, system nonlinearities and unknown disturbances (generator actuator failure and disturbance torque) is estimated in real-time by a designed observer. The estimated perturbation is used for the compensation of actual perturbation. Then, an adaptive feedback linearizing control of variable-speed wind turbine (VSWT) system can be realized. Therefore, the control strategy neither requires detailed system model and full state measurements, nor relies on fault detection, diagnosis and isolation techniques when the generator actuator fails. Simulation results show that the proposed control scheme has smaller tracking error and better dynamic performance than the traditional PI control and MPPT control, and higher robustness against system parameter uncertainties, disturbance torque and generator actuator failure than the nonlinear static state feedback based MPPT (NSSF-MPPT) control, traditional PI control and MPPT control. • An adaptive fault-tolerant MPPT control (AAFT-MPPTC) is proposed for wind turbine. • The AAFT-MPPTC increases energy conversion efficiency of WT under time-varying wind. • The AAFT-MPPTC enhances robustness against generator actuator failure. • The AAFT-MPPTC does not require the detailed system model and full state measurements. • Simulation results verify the effectiveness of the proposed AAFT-MPPTC scheme. [ABSTRACT FROM AUTHOR]

Forced disturbances (FDs) with non-stationary frequencies can sequentially resonate from electromechanical modes (EMs) to sub/super synchronous modes (SSMs) and thus lead to non-stationary forced oscillations (FOs). Previous FO damping controllers designed for specified frequency bands may not be able to suppress the non-stationary FOs. This paper proposes a unified FO damping controller design method to deal with all oscillations caused by non-stationary FOs. The model of a power system with non-stationary FOs is obtained by a continuous model detection and identification of measured signals, which does not require any value of the system parameters. Accordingly, four stability indices, i.e., robustness, interaction, frequency, and damping ratio of the EMs and SSMs, can be calculated from the estimated model. At each operating point, these indices are monitored and used to optimally design the unified FO damping controller. The effectiveness of the proposed unified FO damping controller is verified in the modified Southeast Australian power system with converter controlled-based generations under various operating points and FO conditions. • Investigating the dominant modes under the non-stationary forced oscillation (FO). • Mathematical analysis of a new non-stationary FO. • Evaluating the impacts of non-stationary FO on the small-signal stability. • Introducing an adaptive robust control strategy to mitigate the non-stationary FO. • Comprehensive comparison of the proposed control design with existing methods. [ABSTRACT FROM AUTHOR]

To address the requirement of improved power capacity, reliability and operation, parallel converters have been widely applied in micro-grid. However, the connections between DC and AC sides of different parallel converters may lead to the surge of zero-sequence circulating current (ZSCC), which would result in the deterioration of system functionality. Regarding the stated problem above, this paper proposes an improved data-driven based model predictive control for parallel converters. Specifically, a model-free adaptive control (MFAC), which is based on the measured input/output data, is incorporated into the finite control-set model predictive control (FCS-MPC) framework with multi-objective constraints, thus allowing for the suppression of ZSCC and the improvement of robustness performance. Furthermore, to avoid the tuning of weighting factors, a novel cost function is constructed based on the multi-objective decision making method. The main contribution of the proposed methodology relies on the fact that no knowledge of any model parameters and weighting factors in whole control process are required, which leads to a significant enhancement in the robustness and reliability of the control system in the presence of parametric uncertainties. Furthermore, by this proposal, the accurate current tracking and ZSCC suppression can be achieved. Finally, the validity of the proposed FCS-MPC scheme is verified by comprehensive case studies. • Parallel converters may lead to the surge of zero-sequence circulating current. • An improved data-driven based model predictive control is proposed. • No need for model and parameters, only based on the measured input/output data. • Accurate current tracking and zero-sequence circulating current can be achieved. • Avoidance of the weighting factors tuning and enhanced robustness is realized. [ABSTRACT FROM AUTHOR]

This paper presents a nonlinear model predictive control scheme for residual current compensation inverters in rapid earth fault current limiters to inject appropriate current to the neutral so that the fault current is compensated in distribution networks. The proposed nonlinear model predictive controller is designed to limit the fault current within a level that powerline bushfires do not ignite due to single line-to-ground faults on power distribution systems in bushfire prone areas. The nonlinear model predictive controller is designed for a T-type residual current compensation inverter in rapid earth fault current limiters based on its dynamical model where the control objective is to inject current for compensating the fault current. The control law for the residual current compensation inverter is obtained by solving an optimal control problem while using the concept of the receding horizon control scheme. The performance of the controller is evaluated through standard software-based computer and processor-in-loop simulations where results are benchmarked against backstepping and sliding mode controllers in terms of compensating both faulty phase voltage and fault current. • A nonlinear model predictive controller is designed for RCC inverters. • The optimal control problem is formulated to ensure fast convergence. • The controller effectively eliminates the fault current. • The controller satisfies the requirement for the bushfire mitigation. [ABSTRACT FROM AUTHOR]

This paper presents the development of a discrete-time Robust Adaptive One Sample Ahead Preview controller, based on the combination of a Robust Model Reference Adaptive Controller (RMRAC) with the One Sample Ahead Preview controller (OSAP), which is a particular case of the Deadbeat controller. This control structure is applied to grid-side current control of a grid-tied voltage-source inverter (VSI) with an LCL filter. The developed controller is robust enough to be designed considering the LCL filter as a first order model, which is commonly modelled as a third order transfer function, considering the neglected dynamics as unmodelled dynamics on controller design thanks to its adaptive identifier, which is a modified Gradient algorithm. Furthermore, the controller can deal properly with grid impedance uncertainties, which change the resonance peak frequency of the LCL filter, which affects the controller performance and can induce the closed-loop to instability, by incorporation of a majorant signal and the σ -function into the adaptive law, turning it robust. In addition, the predictive nature of the controller, which aims to regulate the current tracking in the minimum time possible (one sample) impacts straightforwardly in the reduction of harmonic distortion on grid-injected currents, improving energy quality, because the transient regime is reduced thanks to the fast dynamics of the adaptive predictive control strategy. To corroborate the controller's performance and discuss its robustness, Hardware-in-the-Loop and experimental results using a grid-tied 5.5 kW VSI with an LCL filter are presented • The controller is robust enough to control grid injected currents considering a first order transfer function of the LCL filter. • The adaptive One Sample Ahead Preview Controller is robust to unmodelled dynamics, grid uncertainties and parametric variations. • The discrete-time adaptive One Sample Ahead Preview Controller provided fast currents regulation, feasible for grid-tied power systems. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive power oscillation damping (APOD) scheme for the superconducting magnetic energy storage (SMES) device to suppress the interarea oscillation in the inter-connected power system. The APOD scheme is designed based on the generalized predictive control (GPC) and model identification approaches. A recursive least-squares algorithm (RLSA) with a varying forgetting factor is utilized to identify a reduced-order model of the power system online. Based on this identified model, the GPC scheme considering control output constraints can yield an optimal control action by performing an optimization procedure over a prediction horizon. Owing to the usage of the RLSA, the proposed APOD controller can effectively adapt to the variations of operating conditions and parameter uncertainties of the power system. Case studies are undertaken on the New England 10-machine 39-bus power system. Simulation results verify the proposed APOD can consistently provide better damping performance than that of the conventional lead–lag POD, over a wide range of operating conditions and different disturbances. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive fuzzy power system stabilizer is developed based on robust synergetic control theory and terminal attractor techniques. The main contribution consists in making the dynamic system insensitive to parameters variation. This aim is achieved using a new synergetic controller design such that power system states start, evolve and remain on a designer chosen attractor toward the equilibrium point therefore avoiding transient mode. Rendering the design more robust, fuzzy logic systems are used to approximate the unknown power system dynamic functions without calling upon usual model linearization and simplifications. Based on an indirect adaptive scheme and Lyapunov theory, adaptation laws are developed to make the controller handle parameters variations due to the different operating conditions occurring on the power system and to guarantee stability. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results show the effectiveness and robustness of the proposed stabilizer in damping power system oscillations under various disturbances and better overall performance than classical PSS and some other types of power stabilizers. [ABSTRACT FROM AUTHOR]

Modern energy transmission systems suffer from great voltage dropping due to enormous loads. Therefore appropriate schemes should be devised to regulate the voltage. FACTS devices such as Static Var Compensator are often used for this purpose. However, SVC at mid-point of transmission line may leads to deteriorate of distance relay operation, resulting in inaccurate estimation of faults locations i.e. over-reach or under reach for different cases. This paper proposed a new algorithm that utilizes synchronized phasors measurement (SPM) to enhance the operation of distance protection zone in many aspects. The proposed method is tested for 230 kV system simulated in EMTDC/PSCAD with Bergeron model of transmission line. The results prevailed for adaptive approach scheme are more accurate, victor and robust in equivalence with usable transmission line distance protection with SVC. [ABSTRACT FROM AUTHOR]

This paper describes daily peak load forecasting using an adaptive hybrid two-stage methodology. Because the time series of electricity consumption is mainly influenced by seasonal effects, the double seasonal Holt–Winters exponential smoothing method is firstly used for next-day peak electricity demand forecasting. In the second stage, the secondary forecasting model is applied taking into account the benefits of Fuzzy c-means clustering; K-nearest neighbors algorithm; Wavelet packet decomposition; and Adaptive Neuro-Fuzzy Inference System, for further improvement in forecasting accuracy. The whole architecture of the proposed model will be presented and the results will be compared with neural networks and stand-alone adaptive neuro-fuzzy inference system based approaches by using a gathered data from the Algerian power system. The results show that: (1) the proposed methodology is the best among all the considered schemes, (2) the FKW-ANFIS has satisfactory performance in both normal and special daily conditions. [ABSTRACT FROM AUTHOR]

In this paper, a decentralized nonlinear coordinated excitation and steam valve adaptive control combined with a modified high-order sliding mode differentiator is designed for multi-machine power system stability enhancement. The proposed control scheme is based on Lyapunov’s direct method and requires only local information on the physically available measurements of relative angular speed, active electric power and terminal voltage with the assumption that the power angle and mechanical power input are not available for measurement. Each synchronous generator is considered as a classical fifth order model that includes turbine dynamics. The simplicity of the proposed scheme and its robustness with respect to large perturbations, change in operating point and parameter uncertainties constitute the main positive features. Simulation results in the case of the Kundur 4-machines 2-area power system show the effectiveness, robustness and superiority of the proposed scheme over the classical AVR/PSS. [ABSTRACT FROM AUTHOR]

• A data-driven voltage control method is proposed for M−SOPs based on DDPG. • A multi-dimensional action masking approach is designed for action space of M−SOPs. • A DDPG agent is built to mitigate the voltage violation caused by DG fluctuations. The integration of highly penetrated distributed generators (DGs) aggravates the rise of voltage violations in distribution networks. Connected by multi-terminal soft open points (M−SOPs), distribution networks gradually evolve into an interconnected flexible architecture with high controllability. Distribution networks with M−SOPs can exchange active power flexibly, and M−SOPs can provide local reactive power support to alleviate voltage violations. However, conventional model-based M−SOP optimization methods cannot regulate voltage profiles adaptively owing to the rapid fluctuations of DGs. In this paper, a data-driven voltage control method is proposed for M−SOPs using a deep deterministic policy gradient network (DDPG). First, the data-driven voltage control framework is proposed for M−SOPs based on DDPG. The M−SOP−based voltage control problem is reformatted as a Markov decision process (MDP) to construct the DDPG agent. Based on real-time measurement, the DDPG agent can adaptively regulate the M−SOP operation to address the frequent DG fluctuations. Then, a multi-dimensional and dynamic boundary action masking approach is proposed to address the complex coupling in the action space of M−SOPs. Finally, the effectiveness of the proposed method was verified using the IEEE 33-node system. The results show that the proposed method can adaptively alleviate the voltage fluctuations caused by rapid DG power variations. [ABSTRACT FROM AUTHOR]

• A new centralized control scheme is presented to accurately stabilize the load voltage. • A new centralized control scheme is presented to seamlessly share the load power among inverters. • A new recursive filter is introduced to estimate the voltage harmonics and fundamental. • The experimental results are obtained through the rapid control prototyping. This paper presents a new combination of adaptive controllers and recursive filters for the operation of the microgrid with different balanced, unbalanced, and nonlinear loads. The suggested control scheme has the cascaded structure of voltage and current loops for positive- and negative-sequence control. The suggested adaptive controllers are the single-perceptron-based PI controller (the 1st adaptive controller) and the least mean fourth-based PI controller (the 2nd adaptive controller). The 1st adaptive controller is employed with the voltage control loop, while the 2nd adaptive controller is integrated with the current control loop. The Gauss-Newton algorithm is newly formulated to recursively estimate the voltage fundamental/harmonics at the load side. The suggested adaptive controllers are compared with other controllers for the same microgrid operation. The practical implementation of the suggested control scheme along with its adaptive controllers and recursive filters is validated using the dSPACE-SCALEXIO platform using rapid control prototyping. [ABSTRACT FROM AUTHOR]

Buck DC–DC converters are broadly used in DC microgrids to provide a constant dc voltage for generation and storage components. Changing of load condition affects the quality of voltage in the buck DC–DC converters. When constant power loads (CPLs) are used, the stability of these power electronic devices is at risk due to negative impedance characteristics of the CPLs. In such condition, an efficient control method is required to ensure the proper operation of the converter. For this purpose, development of an adaptive control methodology is essential to evaluate the accurate values of controller parameters in the shortest time to damp the ripples quickly. This paper develops a backstepping controller with nonlinear disturbance observer to regulate the output voltage of a dc/dc converter feeding a CPL. An artificial neural network (ANN) methodology is used to estimate the backstepping control parameters of the buck converter. The training ability of the ANN technique prevents the existing controller from depending on the working point of the microgrid. The ANN methodology adapts the controller with various changes and reflections of uncertainties in the microgrid. Case studies are conducted on a dc/dc buck converter in MATLAB/Simulink environment, and the results are verified by the OPAL-RT real-time simulator. • Applying a backstepping controller to regulate the output voltage of a dc/dc converter. • Developing a nonlinear disturbance observer to estimate the variation of uncertainty. • Using ANN to optimally tune the backstepping control parameters. • Verifying the simulation results by the OPAL-RT real-time simulator. [ABSTRACT FROM AUTHOR]

• A proposed design of a hierarchical multi-agent control system for a hybrid-energy isolated microgrid is presented. • The control system efficiently manages the energy resources to achieve optimal cost. • The designed system is decentralized and adaptive. • The control scheme ensures security and resiliency of the microgrid. Multi-agent control is widely recognized as an effective management system for modern microgrids. This paper proposes a hierarchical distributed multi-agent control system for an islanded microgrid with hybrid-energy resources and a battery-storage bank. The dispatchable dispersed generators are to be online-controlled to stabilize the islanded microgrid and minimize operation cost. A non-dispatchable agent is assigned to each bus with a non-dispatchable generator or a load. A dispatchable agent is assigned to each bus with a dispatchable generator. The control scheme is organized into three layers. The primary control layer comprises only the agent which runs the very fast local voltage/frequency droop-control of the battery-storage bank. It achieves a quasi-instantaneous power balance under any disturbance to maintain the frequency and voltage stability of the microgrid. The secondary control layer is formed by fast control algorithms on the dispatchable agents working at 2 ms time step. It is responsible for regulating the islanded microgrid frequency and voltage at minimum participation time of the battery-storage bank. The tertiary control layer is made by relatively slow control algorithms on the dispatchable agents working at a time step of 200 ms. It copes with the economic operation of the microgrid. Each agent behaves autonomously and shares data with others via communication links. The architecture and control algorithms of each layer are presented. Besides, the coordination protocol between different layers is described. The scheme is implemented by a parallel Matlab-Jade computing setup. Results of a case study islanded microgrid are analysed and compared to literature. [ABSTRACT FROM AUTHOR]

The problem of controlling three-phase shunt active power filters (SAPF) is addressed in presence of nonlinear loads. Previous works generally design control for SAPF based on standard models that assume the involved magnetic coil to be linear. In reality, the magnetic characteristics of these components are nonlinear (especially in the presence of large magnetic flux density in the ferromagnetic core). In this paper, a new oriented control model for SAPF-load system, taking into account for the nonlinearity of coil characteristics, is developed. The control objective is twofold: (i) compensating for the current harmonics and the reactive power absorbed by the nonlinear load; (ii) regulating the inverter DC capacitor voltage. To this end, based on the new model, a nonlinear controller is developed, using the backstepping technical design. It is therefore able to ensure good performances over a wide range of variation of the load current. Moreover, the controller is made adaptive for compensating the uncertainty on the switching loss power. The performances of the proposed adaptive controller are formally analyzed using tools from the Lyapunov stability and the averaging theory. The supremacy of the proposed controller with respect to standard control solutions is illustrated through simulation. [ABSTRACT FROM AUTHOR]

Performance of a Fuzzy logic controller is dependent on sufficient and accurate knowledge base. As the number of rules in a knowledge base increases, its complexity increases which in turn affects the computation time and memory requirements. To overcome these problems, a Polar Fuzzy logic controller is proposed. The aim of the Polar Fuzzy Controller (PFC) is to restore the frequency and tie-line power in a smooth way to its nominal value in the shortest possible time if any load disturbance is applied to any area of power system. In this paper, the PFC is made adaptive using a Genetic algorithm-fuzzy system (GAF) approach. Performance of the simple PFC and adaptive PFC using GAF is compared with fuzzy and conventional PI controllers on a three area system. [ABSTRACT FROM AUTHOR]

This paper presents design of an auto-tuning based adaptive maximum power point tracker (ATAMPPT) for a photovoltaic (PV) system. The maximum power point (MPP) of a PV system varies continuously in accordance with changing weather conditions. To cope up with fast varying weather conditions, there is a necessity of an adaptive MPPT system in which MPP of the PV system needs to be quickly estimated and tracked. The proposed ATAMPPT comprises of a DC/DC boost converter equipped with an adaptive MPPT algorithm. This ATAMPPT is incorporated between the PV system and load. In this new MPPT system, a polynomial curve-fitting approach is employed to model the PV system whose parameters are identified on-line using a Recursive-Least-Square (RLS) algorithm. Further, the real-time performance of the proposed MPPT system is validated by using a prototype PV control system set-up developed in our laboratory. The performances of the proposed ATAMPPT have been compared with that of three existing MPPTs namely Perturb and Observe (P&O) and an adaptive P&O MPPT. From the obtained results it is observed that the overall approach of the proposed ATAMPPT control is simple, user-friendly and it exhibits accurate MPP tracking. [ABSTRACT FROM AUTHOR]