Hierarchical Control of Paralleled Voltage Source Inverters in Islanded Single Phase Microgrids

Bennia, Ilyas; Daili, Yacine; Harrag, Abdelghani

doi:10.1007/978-3-030-63846-7_30

Cited by 7 publications

(6 citation statements)

References 22 publications

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“…Simulation results of the developed small-signal model (X (t) = Xeq + ΔX ) are compared to the detailed model described in figure (2), which is developed using MATLAB SimpowerSystem components. The inverters are modeled as an ideal voltage source in Simulink environment with a simple time equal to 10 -3 s, the parameters of the simulation are listed in Table (I).…”

Section: Resultsmentioning

confidence: 99%

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Small-signal modelling and stability analysis of island mode microgrid paralleled inverters

2021

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The autonomous operation mode of paralleled inverters in microgrids can be intentional or unintentional in order to ensure the continuity of supply. In this mode the voltage and frequency magnitudes are held by local controllers using droop control, this latter is generally considered to be the most adopted technic for the primary layer in a multilayer control structure due to their main feature of sharing the power equally between inverters, without needing communication infrastructure, the design of droop parameters is very crucial because a bad design can lead to the instability of the system. This paper presents a small-signal analysis for an MG composed of parallel-connected inverters in island mode and controlled using the droop method, aiming to analyze the stability by performing eigenvalues and sensitivity analysis which allows obtaining the behavior of the system, analyze the interaction between the different elements and study the influence of the droop parameters on this later which helps in the design procedure, small-signal model and Simulink block model was developed and simulated. Simulation results show a high correspondence and agreement between the model developed using Matlab Simulink-SimPowerSystem library and the developed small-signal model which confirms the validity of this later.

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Section: Resultsmentioning

confidence: 99%

“…The multilayer control composed of three layers, each one is in charge of a task, the primary control carry on the voltage and frequency control with the power-sharing, the secondary layer allows the compensation of the voltage and frequency deviation, and finally the tertiary layer responsible of managing the power flow [2].…”

Section: Introductionmentioning

confidence: 99%

Small-signal modelling and stability analysis of island mode microgrid paralleled inverters

2021

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“…In MG's with mismatched inductive/resistive feeder impedance, the virtual impedance loop, acting as an optional loop, plays a role in improving the power quality and power-sharing accuracy of GFM systems [21]. Drawbacks such as steady-state error and deviations in frequency and voltage amplitude are associated with the GFM droop control mechanism [22]. Consequently, a secondary control is introduced to mitigate these deviations [23].…”

Section: Related Workmentioning

confidence: 99%

Design, Modeling, and Validation of Grid-Forming Inverters for Frequency Synchronization and Restoration

Bennia,

Elbouchikhi,

Harrag

et al. 2023

Energies

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This paper focuses on the modeling, analysis, and design of grid-forming (GFM) inverter-based microgrids (MGs). It starts with the development of a mathematical model for three-phase voltage source inverters (VSI). The voltage and current controllers consist of two feedback loops: an outer feedback loop of the capacitance-voltage and an inner feedback loop of the output inductance current. The outer voltage loop is employed to enhance the controller’s response time. The inner current loop is used to provide active damping for the resonance created by the LCL filter. A two-layer control scheme is adopted for the GFM inverter control. The primary decentralized control uses droop control and virtual impedance loops to share active and reactive power. Simultaneously, the centralized secondary control addresses frequency and amplitude deviations induced by the droop control. Additionally, a synchronization loop is proposed for seamless reconnection of GFM inverters to the MG and to connect the GFM-controlled MG to the main grid. It has the advantage that the inverter operates in GFM mode even after the synchronization has occurred. The simulation results have shown that the voltage controller ensures a 0.005 s settling time and maintains the steady-state error at its minimum value of 0.1 V. Similarly, the current controller ensures a 0.006 s settling time with a 10−5 steady-state error. The system with the designed controller has a low total harmonic distortion (THD) of 1.46% and improved power quality of the output voltage. Furthermore, a quick restoration time is observed during load steps and tripping events, with a restoration time of 1 s with 10−10 steady-state error. Synchronization is achieved within 0.8 s for the incoming inverters and requires 3 s to synchronize the MG with the main grid, maintaining a steady-state error of 10−9.

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“…The rules base plays an important role in the behavior of the fuzzy controller, hence a good design of the table of rules leads to better performances, generally the construction of the interference table is based on qualitative analysis of the process. From the previous study [11] of the closed-loop system behavior using a PI controller and based on the expertise, fuzzy rules are established to tie the inputs and output. The general form of the step response and the derivative of the error are shown in Figure 5(b).…”

Section: Figure 3 Primary and Secondary Control Actionsmentioning

confidence: 99%

“…To verify and confirm the superiority of this method, the fuzzy logic controller is compared with the conventional PI controller used in [11]. The comparison investigates the dynamic response of the system and the compensation time, as can be seen in Figure 8(c).…”

Section: Comparative Study Of Dynamic Responsementioning

confidence: 99%

Decentralized secondary control for frequency regulation based on fuzzy logic control in islanded microgrid

Bennia

Harrag

Daili

et al. 2022

IJEECS

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This paper presents a fuzzy-based decentralized secondary control for frequency restoration and active power-sharing in an islanded microgrid, this controller uses the local frequency error to generate an extra term for compensating the deviation and maintaining accurate active power-sharing. No communication infrastructures are needed, event detection, time dependent-protocols, and state estimation are not required. Its design and implementation are straightforward, also, it offers quick dynamic frequency recovery with accurate active power-sharing. To verify the validity of the proposed controller, several tests have been carried out: frequency restoration and active power-sharing during load disturbances, synchronization with plug and play (PnP) ability, as well the communication latency impact. Moreover, the effect of data drop-out and interferences were analyzed in real-time simulation using Truetime. The results have shown the high capability and the fast response of frequency restoration while maintaining the active power-sharing, no oscillations and ripples were presented in steady-state response, likewise, a smooth dynamic response during PnP test is observed. The communication latency and interferences have no impact on the proposed controller that showing a significant improvement in settling time 50% without frequency packet losses and 81%, 90% in the presence of 30% and 70% of frequency packet losses respectively.

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Hierarchical Control of Paralleled Voltage Source Inverters in Islanded Single Phase Microgrids

Cited by 7 publications

References 22 publications

Small-signal modelling and stability analysis of island mode microgrid paralleled inverters

Small-signal modelling and stability analysis of island mode microgrid paralleled inverters

Design, Modeling, and Validation of Grid-Forming Inverters for Frequency Synchronization and Restoration

Decentralized secondary control for frequency regulation based on fuzzy logic control in islanded microgrid

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