Robust Power Sharing and Voltage Stabilization Control Structure via Sliding-Mode Technique in Islanded Micro-Grid

Zhang, Quan-Quan; Wai, Rong‐Jong

doi:10.3390/en14040883

Cited by 13 publications

(12 citation statements)

References 36 publications

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“…As an efficient nonlinear control method, the total sliding-mode control (TSMC) has been extensively investigated in various fields for its merits of fast dynamic response and strong robustness to uncertainties [45]- [46]. In this study, the TSMC technique is integrated into the distributed cooperative secondary control framework to achieve the properties of fast convergence and the strong robustness against uncertainties for the voltage restoration and the optimal active power sharing, as shown in Fig.…”

Section: Problem Formulationmentioning

confidence: 99%

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Design of Adaptive Distributed Secondary Control Using Double-Hidden-Layer Recurrent-Neural-Network-Inherited Total-Sliding-Mode Scheme for Islanded Micro-Grid

Zhang

Wai

2022

IEEE Access

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This study proposes an adaptive double-hidden-layer recurrent-neural-network (DRNN)-based distributed secondary control (ADRNN-SC) scheme for the voltage restoration and the optimal active power sharing in an islanded micro-grid (MG). Based on the dynamic model composed of MG network model and primary control, a total-sliding-mode (TSMC)-based distributed secondary control (TSMC-SC) scheme is firstly developed for the properties of fast convergence and overall robustness during the control process, where the issues of voltage restoration and optimal active power sharing are converted to local-neighborhood synchronization and tracking problems. Meanwhile, focused on the problems of the control chattering phenomenon and the model dependence, a model-free DRNN structure is used to mimic the designed TSMC-SC law and to inherit its robust performance. The double-hidden-layer neural network (NN) in the DRNN structure needs less neuron nodes than the one with a single hidden layer at the same control performance because of its strong presentation ability. Thus, the computational complexity of the proposed ADRNN-SC scheme can be reduced. Moreover, the recurrent loop in the DRNN structure delivers the feedback signals of the output layer to the input layer, which possesses associative memory and accelerates the convergence process. Therefore, the DRNN structure can engage with a strong approximation ability and superior dynamic performance. In addition, the network parameters are online tuned adaptively to enhance the network learning ability. Furthermore, based on the small-signal model of the proposed control method embedded with communication delays, the delay margin and the influence of control parameters are also investigated. The effectiveness of the proposed control method is verified by numerical simulations.INDEX TERMS Double-hidden-layer recurrent-neural-network (DRNN), islanded micro-grid (MG), distributed secondary control, small-signal analysis, total sliding-mode control (TSMC).

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Section: Problem Formulationmentioning

confidence: 99%

“…The stability and dynamic performance of the distributed control system in ( 44) can be analyzed by observing the roots of its characteristic equation in (45). det( ) 0…”

Section: B Influences Of Control Parameters and Time Delays On System Performancementioning

confidence: 99%

Design of Adaptive Distributed Secondary Control Using Double-Hidden-Layer Recurrent-Neural-Network-Inherited Total-Sliding-Mode Scheme for Islanded Micro-Grid

Zhang

Wai

2022

IEEE Access

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“…The power demanded by the load should be shared proportionally to the ratings of the inverters while the voltage and the frequency are maintained within the desired ranges. This problem has been addressed in the literature by using different control methods, for example [35], has redesigned a conventional P − ω and Q − V droop controller based on a total sliding-mode control (TSMC) technique. In the proposed method in this article, an accurate power sharing is achieved by the novel virtual flux droop control.…”

Section: Power Sharing Controlmentioning

confidence: 99%

A Novel Power Sharing Strategy Based on Virtual Flux Droop and Model Predictive Control for Islanded Low-Voltage AC Microgrids

et al. 2021

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The droop control scheme based on Q − ⍵ and P − V characteristics is conventionally employed to share the load power among sources in an islanded low-voltage microgrid with resistive line impedances. However, it suffers from poor active power sharing, and is vulnerable to sustained deviations in frequency and voltage. Therefore, accurate power sharing and maintaining the frequency and voltage in the desired ranges are challenging. This paper proposes a novel microgrid control strategy to address these issues. The proposed strategy consists of a virtual flux droop and a model predictive control, in which the virtual flux is the time integral of the voltage. Firstly, the novel virtual flux droop control is proposed to accurately control the power sharing among DGs. Then, the model predictive flux control is employed to generate the appropriate switching signals. The proposed strategy is simple without needing multiple feedback control loops. In addition, pulse width modulation is not required and tuning challenges for PI regulators are avoided. In order to evaluate the effectiveness of the proposed microgrid control strategy, simulation analysis is carried out in Matlab/Simulink software environment. The results show that accurate power sharing is achieved while a good dynamic response is provided. Furthermore, the voltage and frequency deviations are significantly improved.

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“…Computer simulations demonstrate, that the proposed observer ensures faster and more accurate estimation than using a model reference adaptive system (MRAS) speed identification. The authors of [13] consider sliding mode control for power sharing and voltage stabilization for parallel operation of several inverters. Such operation usually occurs in islanded microgrid systems.…”

Section: Introductionmentioning

confidence: 99%

Reaching Law Based Sliding Mode Control of Sampled Time Systems

Leśniewski

Bartoszewicz

2021

Energies

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In this paper, discrete time reaching law-based sliding mode control of continuous time systems is considered. In sliding mode control methods, usually the assumption of bounded absolute values of disturbances is used. However in many cases, the rate of change of the disturbance is also bounded. In the presented approach, this knowledge is used to improve the control precision and reduce the undesirable chattering. Another advantage of the proposed method is that the disturbance does not have to satisfy the matching conditions. In the paper two new reaching laws are analyzed, one of them ensures the switching quasi-sliding motion and the other the non-switching motion. For both of them, the robustness is assessed by calculating the quasi-sliding mode band width, as well as the greatest possible state error values. Specifically, the state errors are not considered only at the sampling instants, as is usual for discrete time systems, but the bounds on the continuous values “between” the sampling instants are also derived. Then, the proposed approaches are compared and analyzed with respect to energy expenditure of the control signal.

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Robust Power Sharing and Voltage Stabilization Control Structure via Sliding-Mode Technique in Islanded Micro-Grid

Cited by 13 publications

References 36 publications

Design of Adaptive Distributed Secondary Control Using Double-Hidden-Layer Recurrent-Neural-Network-Inherited Total-Sliding-Mode Scheme for Islanded Micro-Grid

Design of Adaptive Distributed Secondary Control Using Double-Hidden-Layer Recurrent-Neural-Network-Inherited Total-Sliding-Mode Scheme for Islanded Micro-Grid

A Novel Power Sharing Strategy Based on Virtual Flux Droop and Model Predictive Control for Islanded Low-Voltage AC Microgrids

Reaching Law Based Sliding Mode Control of Sampled Time Systems

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