An Online Grid Impedance Estimation Using Recursive Least Square For Islanding Detection

Jarraya, Imen; Hmad, Jihed; Trabelsi, Hafedh; Houari, Azeddine; Machmoum, Mohamed

doi:10.1109/ssd.2019.8893148

Cited by 7 publications

(7 citation statements)

References 27 publications

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“…The study of Islanding Detection Methods (IDMs) in the field of DG has been presented under different names over the years. These names include islanding detection, nonislanding, anti-islanding (AI), and unintentional islanding [125]. In the literature, several IDMs have been proposed to effectively detect the islanding mode.…”

Section: Islanding Detection Methods (Idm)mentioning

confidence: 99%

“…Numerous publications have raised concerns about unplanned islands. In fact, multiple factors could lead to unintentional islanding, including [123][124][125][126]:…”

Section: Islanding Detection: Conceptmentioning

confidence: 99%

“…They may result in significant risks of damage to utility equipment or customer-connected loads due to transient conditions occurring between the islanding event and the eventual disconnection of the DG inverter from the grid. [125,127].…”

Section: Islanding Detection: Conceptmentioning

confidence: 99%

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A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids

et al. 2023

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Microgrids technologies are seen as a cost effective and reliable solution to handle numerous challenges, mainly related to climate change and power demand increase. This is mainly due to their potential for integrating available on-site renewable energy sources and their flexibility and scalability. The particularity of microgrids is related to their capacity to operate in synchronization with the main grid or in islanded mode to secure the power supply of nearby end-users after a grid failure thanks to storage solutions and an intelligent control system. The most critical operating case occurs when a sudden transition from grid-connected (GC) to stand-alone operation (SA) happens. During the transition, the system experiences abrupt changes that can result in a malfunction of the control system and a possible failure of the power system. The transition issue attracted considerable attention from researchers. Indeed, many research works are proposed to address this issue by proposing detection and transition techniques that ensure a smooth transition at the islanding time. Although there are several approaches to dealing with this issue, a categorization of the proposed methods in the literature and their differences is useful to assist engineers and researchers working on this topic. Thus, this study proposes a comprehensive review to summarize these approaches and point out their advantages and limitations.

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Section: Islanding Detection Methods (Idm)mentioning

confidence: 99%

“…Numerous publications have raised concerns about unplanned islands. In fact, multiple factors could lead to unintentional islanding, including [123][124][125][126]:…”

Section: Islanding Detection: Conceptmentioning

confidence: 99%

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A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids

et al. 2023

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“…The FF-RLS method is used in various applications such as estimation ofO 2 gas-liquid mass-transfer in the chemical industry, in financial studies, biomedical applications for estimating the ECG signals, predicting the torque and speed parameters in mechanical studies as well as recent application of RLS to estimate unknown parameters such as resistance, inductance, and capacitance in electrical circuits. The proposed method is more accurate and stable than others, with low computational time and high robustness which is proven in [43][44][45][46]. Equation ( 23) can be modified as:…”

Section: Recursive Least Squares With Forgetting Factormentioning

confidence: 99%

A new protection scheme for PV-wind based DC-ring microgrid by using modified multifractal detrended fluctuation analysis

Anjaiah

Dash

2022

Prot Control Mod Power Syst

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This paper presents fault detection, classification, and location for a PV-Wind-based DC ring microgrid in the MATLAB/SIMULINK platform. Initially, DC fault signals are collected from local measurements to examine the outcomes of the proposed system. Accurate detection is carried out for all faults, (i.e., cable and arc faults) under two cases of fault resistance and distance variation, with the assistance of primary and secondary detection techniques, i.e. second-order differential current derivative $$\left( {\frac{{d^{2} I_{3} }}{{dt^{2} }}} \right)$$ d 2 I 3 d t 2 and sliding mode window-based Pearson’s correlation coefficient. For fault classification a novel approach using modified multifractal detrended fluctuation analysis (M-MFDFA) is presented. The advantage of this method is its ability to estimate the local trends of any order polynomial function with the help of polynomial and trigonometric functions. It also doesn’t require any signal processing algorithm for decomposition resulting and this results in a reduction of computational burden. The detected fault signals are directly passed through the M-MFDFA classifier for fault type classification. To enhance the performance of the proposed classifier, statistical data is obtained from the M-MFDFA feature vectors, and the obtained data is plotted in 2-D and 3-D scatter plots for better visualization. Accurate fault distance estimation is carried out for all types of faults in the DC ring bus microgrid with the assistance of recursive least squares with a forgetting factor (FF-RLS). To verify the performance and superiority of the proposed classifier, it is compared with existing classifiers in terms of features, classification accuracy (CA), and relative computational time (RCT).

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“…Regarding the improvement of control robustness, two roadmaps are usually considered: one is to design nonlinear controllers (e.g., the sliding mode control (SMC) [9]) having inherent robustness to the parameter variation of control plant; for the case of grid-tied VSC system, the variation of control plant mainly refers to the variation of grid impedance. Another way of improving control robustness is to adaptively adjust the controller's parameters following the changing grid impedance, where the variation of grid impedance (e.g., RL-based) can be estimated online by various time/frequency-domain approaches, e.g., using the extended Kalman filter [10], the Recursive Least Square (RLS) [11] [12], and the broadband signal injectionbased methods [13]. Adaptive controls achieved by such online parameter tuning approaches can be historically referred to as the auto-tuning technique [14].…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network-Based Pole-Tracking Method for Online Stabilization Control of Grid-Tied VSC

Zhang

Mijatović

Cai

et al. 2022

IEEE Trans. Ind. Electron.

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An Online Grid Impedance Estimation Using Recursive Least Square For Islanding Detection

Cited by 7 publications

References 27 publications

A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids

A Review on Mode Transition Strategies between Grid-Connected and Standalone Operation of Voltage Source Inverters-Based Microgrids

A new protection scheme for PV-wind based DC-ring microgrid by using modified multifractal detrended fluctuation analysis

Artificial Neural Network-Based Pole-Tracking Method for Online Stabilization Control of Grid-Tied VSC

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