Distributed energy storage system‐based nonlinear control strategy for hybrid microgrid power management included wind/PV units in grid‐connected operation

Holari, Yaser Toghani; Taher, Seyed Abbas; Mehrasa, Majid

doi:10.1002/2050-7038.12237

Cited by 24 publications

(14 citation statements)

References 48 publications

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“…This voltage is coupled to the grid via 3Ф voltage source inverter (VSI) and filter circuits. As multilevel inverter [ 31 , 32 ] and z-source inverter [ 33 , 34 ] employment makes the circuit complex and costly and reduces the system efficiency, a conventional VSI with LC filter is implemented in our system. Moreover, hybrid system facilitates continuity in power flow, thereby improving the reliability [ 35 , 36 ] (Fig.…”

Section: Introductionmentioning

confidence: 99%

ANN-based dynamic control and energy management of inverter and battery in a grid-tied hybrid renewable power system fed through switched Z-source converter

2021

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The multidimensional purposes of grid-tied hybrid renewable system such as tracking of maximum power, increasing the power conversion efficiency, reducing the harmonic distortions in the injected current and control over power injected into the grid are presented in this paper by developing a laboratory-scale setup. To ensure continuous current operation at the shoot through mode of grid connected inverter, a switched Z-source converter is utilized at the PV side. The PWM rectifier connected with the wind turbine transforms AC power into dc. Individual power converters with conventional PI controllers have been dedicated for each power source, and control strategy uses only one reference voltage so as to increase the maximum power tracking speed from both PV and wind sources. The battery energy management is performed by artificial neural network (ANN) to enhance the stable power flow and increase the lifespan of the storage system. Finally, the voltage at the point of common coupling is fed to ANN-based space vector-modulated three-phase inverter and the converted AC power is injected to the grid. The overall system performance is measured by estimating the quality of injected power. A stable operation of the proposed microgrid system is verified by varying input and load at the grid. A continuous-time simulation model is realized in MATLAB and is validated using experimental prototype. This benchmark system provides various research scopes for the future smart grids.

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Section: Introductionmentioning

confidence: 99%

ANN-based dynamic control and energy management of inverter and battery in a grid-tied hybrid renewable power system fed through switched Z-source converter

2021

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“…Holari et al 34 have performed a control approach depending on combination of Lyapunov's theory and input–output feedback linearization (IOFL) for providing stable operation of hybrid DC/AC microgrid in unbalanced generations of AC drives. The DC link of the considered hybrid microgrid was provided with bidirectional DC/DC converters based on lithium batteries (LB‐based) and photovoltaic (PV) buckles.…”

Section: Introductionmentioning

confidence: 99%

Improving the performance of grid‐connected doubly fed induction generator by fault identification and diagnosis: A kernel PCA‐ESMO technique

Stallon¹,

Rajkumar

2021

Int Trans Electr Energ Syst

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Summary In this manuscript, a novel Kernel PCA‐ESMO technique is proposed for protecting the system and diagnosing the exact fault occuring in the DFIG. The proposed method is joined implementation of Kernel principal component analysis (Kernel PCA) and enhanced Spider Monkey Optimization SMO (ESMO) technique, and, hence, it is named Kernel PCA‐ESMO approach. Here, two phases are considered for fault analysis; they are fault identification and diagnosis. Primarily, the first phase identifies the system fault conditions of DFIG in grid‐connected system using Kernel PCA approach. After that, the ESMO classifies the type of fault that has occurred in the DFIG. The major scope of the proposed Kernel PCA‐ESMO method is to guarantee the system with less complexity for fault identification and diagnosis for enhancing the power quality of whole system. The implementation of proposed model is made at MATLAB/Simulink, and implementation is evaluated by existing techniques. The statistic analysis of proposed and existing systems of mean, median, and SD is analyzed. The efficiency of proposed and existing technique is also evaluated. The obtained values for percentage recall and precision that are enhanced using proposed technique are 97.8% and 98%. Consequently, the simulation outcome indicates that the efficiency of proposed technique and implementation of proposed strategy is compared to existing systems.

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“…The idea of MG has become increasingly popular as it demands low cost in case of power generation from RPS, enhances local reliability, compensates feeder losses, and provides voltage support/voltage sag correction (Badal et al, 2019;Armin et al, 2020;Rizi and Eliasi, 2020). Several types of MG like AC MG, DC MG and hybrid source of AC/DC MG can be found in power system (Sarkar et al, 2018b;Toghani Holari et al, 2020). Among them, the hybrid source of AC/DC MG with energy technologies are brought up new opportunities for the use of renewable energy sources as it can operate in both cases.…”

Section: Introductionmentioning

confidence: 99%

A Robust Control Method for Damping and Tracking of Secondary Network Voltage of a PV Based Hybrid AC/DC Microgrid

et al. 2020

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Distributed energy storage system‐based nonlinear control strategy for hybrid microgrid power management included wind/PV units in grid‐connected operation

Cited by 24 publications

References 48 publications

ANN-based dynamic control and energy management of inverter and battery in a grid-tied hybrid renewable power system fed through switched Z-source converter

ANN-based dynamic control and energy management of inverter and battery in a grid-tied hybrid renewable power system fed through switched Z-source converter

Improving the performance of grid‐connected doubly fed induction generator by fault identification and diagnosis: A kernel PCA‐ESMO technique

A Robust Control Method for Damping and Tracking of Secondary Network Voltage of a PV Based Hybrid AC/DC Microgrid

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