scholarly journals Differential Algorithm Based Intelligent Protection Scheme for Microgrid

2019 ◽  
Vol 8 (9S3) ◽  
pp. 128-133
Keyword(s):  
Discrete Wavelet ◽  
Time Duration ◽  
New Approach ◽  
Protection Scheme ◽  
Intelligent Technique ◽  
Course Of Action ◽  
Different Types ◽  
Islanded Mode ◽  
Differential Algorithm ◽  
Types Of Faults

Proposed scheme presents intelligent technique in protection of microgrid. This paper gives new approach in feature extraction of faulted current signal using Discrete Wavelet Transform. Furthermore different parameters like TMS(Time Measurment setting),PSM (Plug setting Multiple ) and CTD (coordination time Duration) are computed from featured faulty current. This course of action used to build genetic differential algorithm for deciding best suitable pair of relay with concept of “survival of fittest”. IEEE 9 bus system is considered for studding different types of faults for utilityconnected and islanded mode. Initially primary pair of relay is activated and secondary protection operates on failure of primary. This study gives effective solution for fast operation of pair of relay in optimized time.

scholarly journals A Novel Protection Scheme against Fault Resistance for AC Microgrid

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Xinrui Liu ◽  
Zhiyuan Xie ◽  
Qiuye Sun ◽  
Zhiliang Wang
Keyword(s):  
High Reliability ◽  
High Sensitivity ◽  
Active Power ◽  
Backup Protection ◽  
Protection Scheme ◽  
Fault Resistance ◽  
Different Types ◽  
Islanded Mode ◽  
Resistance Value ◽  
Ac Microgrid

The faults characteristics of the lines in AC microgrid are weakened due to the fault resistance, which may refuse protection action. To solve the problems caused by different types of the faults through fault resistance (FTFR, the faults where the fault point resistance is greater than zero) in AC microgrid, a novel FTFR protection scheme based on the active power of 0-frame component or d-frame component consumed by fault resistance is proposed in this paper as the backup protection of FTFR. This proposed protection scheme utilizes the active power of 0-frame component or d-frame component consumed by fault resistance to identify internal FTFR and external faults. It performs well in grid-connected mode and islanded mode by adopting self-adaptive threshold and is not affected by the factors such as the fault position and the fault resistance value. The theoretical analysis and various simulations show that this protection scheme can identify and isolate different types of internal FTFR in AC microgrid with high reliability and high sensitivity.

scholarly journals A Fast Fault Identification in a Grid-Connected Photovoltaic System Using Wavelet Multi-Resolution Singular Spectrum Entropy and Support Vector Machine

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2508 ◽  
Author(s):  
Ahmadipour ◽  
Hizam ◽  
Othman ◽  
Mohd Radzi ◽  
Chireh
Keyword(s):  
Support Vector Machine ◽  
Wavelet Transform ◽  
Photovoltaic System ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Phase Voltage ◽  
Singular Spectrum ◽  
Intelligent Technique ◽  
Three Phase ◽  
Different Types

A new protection scheme based on applying a combination of wavelet multi-resolution singular spectrum entropy and support vector machine is proposed to identify different types of grid faults in a three-phase grid-tied photovoltaic system. In this technique, discrete wavelet transform with multi-resolution singular spectrum entropy is utilized to extract the unique features of three-phase voltage signals at the point of common coupling. The three-phase voltage signals are decomposed to provide detail and approximation coefficients of wavelet transform. Then, various features between different types of grid faults can be extracted by a combination of multi resolution analysis and spectrum analysis with entropy as the output. The constructed features vector is utilized as input data of a support vector machine classifier to identify and classify various types of faults. The results illustrate that the proposed intelligent technique not only recognizes different types of grid faults correctly, but also performs quickly in identifying grid faults in a grid-connected photovoltaic system. Apart from this, a graphical investigation is executed to observe the effects of different types of grid faults in photovoltaic (PV) operation which highlight the necessity of intelligent protection methods to protect PV systems.

scholarly journals “Artificial Wood” Lignocellulosic Membranes: Influence of Kraft Lignin on the Properties and Gas Transport in Tunicate-Based Nanocellulose Composites

Membranes ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 204
Author(s):  
Ievgen Pylypchuk ◽  
Roman Selyanchyn ◽  
Tetyana Budnyak ◽  
Yadong Zhao ◽  
Mikael Lindström ◽  
...  
Keyword(s):  
Knudsen Diffusion ◽  
Cellulose Nanofibers ◽  
Kraft Lignin ◽  
Separation Processes ◽  
New Approach ◽  
Future Studies ◽  
Different Types ◽  
Molecular Sizes ◽  
Fast Transport ◽  
Cellulose Membranes

Nanocellulose membranes based on tunicate-derived cellulose nanofibers, starch, and ~5% wood-derived lignin were investigated using three different types of lignin. The addition of lignin into cellulose membranes increased the specific surface area (from 5 to ~50 m2/g), however the fine porous geometry of the nanocellulose with characteristic pores below 10 nm in diameter remained similar for all membranes. The permeation of H2, CO2, N2, and O2 through the membranes was investigated and a characteristic Knudsen diffusion through the membranes was observed at a rate proportional to the inverse of their molecular sizes. Permeability values, however, varied significantly between samples containing different lignins, ranging from several to thousands of barrers (10−10 cm3 (STP) cm cm−2 s−1 cmHg−1cm), and were related to the observed morphology and lignin distribution inside the membranes. Additionally, the addition of ~5% lignin resulted in a significant increase in tensile strength from 3 GPa to ~6–7 GPa, but did not change thermal properties (glass transition or thermal stability). Overall, the combination of plant-derived lignin as a filler or binder in cellulose–starch composites with a sea-animal derived nanocellulose presents an interesting new approach for the fabrication of membranes from abundant bio-derived materials. Future studies should focus on the optimization of these types of membranes for the selective and fast transport of gases needed for a variety of industrial separation processes.

scholarly journals An Efficient Neural Network-Based Method for Diagnosing Faults of PV Array

2021 ◽  
Vol 13 (11) ◽  
pp. 6194
Author(s):  
Selma Tchoketch_Kebir ◽  
Nawal Cheggaga ◽  
Adrian Ilinca ◽  
Sabri Boulouma
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Modeling Process ◽  
Photovoltaic Arrays ◽  
Mode Of Operation ◽  
Different Types ◽  
The Neural Networks ◽  
Operational Modes ◽  
Types Of Faults ◽  
Electrical Data

This paper presents an efficient neural network-based method for fault diagnosis in photovoltaic arrays. The proposed method was elaborated on three main steps: the data-feeding step, the fault-modeling step, and the decision step. The first step consists of feeding the real meteorological and electrical data to the neural networks, namely solar irradiance, panel temperature, photovoltaic-current, and photovoltaic-voltage. The second step consists of modeling a healthy mode of operation and five additional faulty operational modes; the modeling process is carried out using two networks of artificial neural networks. From this step, six classes are obtained, where each class corresponds to a predefined model, namely, the faultless scenario and five faulty scenarios. The third step involves the diagnosis decision about the system’s state. Based on the results from the above step, two probabilistic neural networks will classify each generated data according to the six classes. The obtained results show that the developed method can effectively detect different types of faults and classify them. Besides, this method still achieves high performances even in the presence of noises. It provides a diagnosis even in the presence of data injected at reduced real-time, which proves its robustness.

scholarly journals Application of Machine Learning for Fault Classification and Location in a Radial Distribution Grid

2020 ◽  
Vol 10 (14) ◽  
pp. 4965
Author(s):  
Yordanos Dametw Mamuya ◽  
Yih-Der Lee ◽  
Jing-Wen Shen ◽  
Md Shafiullah ◽  
Cheng-Chien Kuo
Keyword(s):  
Machine Learning ◽  
Fault Detection ◽  
Radial Distribution ◽  
Fault Classification ◽  
Discrete Wavelet ◽  
Efficiency Coefficient ◽  
Distribution Grid ◽  
Phase Current ◽  
Three Phase ◽  
Types Of Faults

Fault location with the highest possible accuracy has a significant role in expediting the restoration process, after being exposed to any kind of fault in power distribution grids. This paper provides fault detection, classification, and location methods using machine learning tools and advanced signal processing for a radial distribution grid. The three-phase current signals, one cycle before and one cycle after the inception of the fault are measured at the sending end of the grid. A discrete wavelet transform (DWT) is employed to extract useful features from the three-phase current signal. Standard statistical techniques are then applied onto DWT coefficients to extract the useful features. Among many features, mean, standard deviation (SD), energy, skewness, kurtosis, and entropy are evaluated and fed into the artificial neural network (ANN), Multilayer perceptron (MLP), and extreme learning machine (ELM), to identify the fault type and its location. During the training process, all types of faults with variations in the loading and fault resistance are considered. The performance of the proposed fault locating methods is evaluated in terms of root mean absolute percentage error (MAPE), root mean squared error (RMSE), Willmott’s index of agreement (WIA), coefficient of determination ( R 2 ), and Nash-Sutcliffe model efficiency coefficient (NSEC). The time it takes for training and testing are also considered. The proposed method that discrete wavelet transforms with machine learning is a very accurate and reliable method for fault classifying and locating in both a balanced and unbalanced radial system. 100% fault detection accuracy is achieved for all types of faults. Except for the slight confusion of three line to ground (3LG) and three line (3L) faults, 100% classification accuracy is also achieved. The performance measures show that both MLP and ELM are very accurate and comparative in locating faults. The method can be further applied for meshed networks with multiple distributed generators. Renewable generations in the form of distributed generation units can also be studied.

scholarly journals On the Use of LoRa Technology for Logic Selectivity in MV Distribution Networks

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3079 ◽  
Author(s):  
Leopoldo Angrisani ◽  
Francesco Bonavolontà ◽  
Annalisa Liccardo ◽  
Rosario Schiano Lo Moriello
Keyword(s):  
Cost Effectiveness ◽  
Long Range ◽  
Distribution Networks ◽  
Fault Isolation ◽  
Optimized Design ◽  
Medium Voltage ◽  
Different Types ◽  
The Times ◽  
The Cost ◽  
Types Of Faults

In this paper, a logic selectivity system based on Long Range (LoRa) technology for the protection of medium-voltage (MV) networks is proposed. The development of relays that communicate with each other using LoRa allows for the combination of the cost-effectiveness and ease of installation of wireless networks with long-range coverage and reliability. The realized demonstrator to assess the proposed system is also presented in the paper; based on different types of faults and different locations, the times needed for clearing a fault and restoring the network were estimated from repeated experiments. The obtained results confirm that, with an optimized design of transmitted packets and of protocol characteristics, LoRa communication grants fault management that meets the criteria of logic selectivity, with fault isolation occurring within the maximum allowed time.

scholarly journals Design and construction of a prototype for the analysis of vibrations in an induction motor for the detection of faults

2020 ◽  
pp. 27-33
Author(s):  
Javier Garrido ◽  
Beatris Escobedo-Trujillo ◽  
Guillermo Miguel Martínez-Rodríguez ◽  
Oscar Fernando Silva-Aguilar
Keyword(s):  
Fourier Transform ◽  
Induction Motor ◽  
Wavelet Transforms ◽  
Data Acquisition System ◽  
Time Frequency ◽  
Different Types ◽  
Control Devices ◽  
The Fourier Transform ◽  
And Control ◽  
Types Of Faults

The contribution of this work is to present the design of a prototype integrated by an induction motor, a data acquisition system, accelerometers and control devices for stop and start, to generate and identify different types of faults by means of vibration analysis. in the domain: time, frequency or frequency-time, through the use of the Fourier Transform, Fast Fourier Transform or Wavelet Transforms (wavelet transform). In this prototype, failures can be generated in the induction motor such as: unbalance, different types of misalignment, mechanical looseness, and electrical failures such as broken bars or short-circuited rings, an example of a misalignment failure is presented to show the process of analysis and detection.

scholarly journals Urban, industrial and technological risks. Synthesis of the elements of vulnerability of the city of Hassi-Messaoud

2020 ◽  
Vol 12 ◽  
Author(s):  
Lahcene Bouzouaid ◽  
Moussadek Benabbas
Keyword(s):  
Urban Space ◽  
Job Search ◽  
Population Distribution ◽  
Risk Assessments ◽  
Demographic Development ◽  
New Approach ◽  
Different Types ◽  
Specific Factors ◽  
The City

Abstract Today, Algeria is one of the developing countries that are engaging seriously into a new approach consisting of all kinds of combined risk assessments for better prevention them. Note that, this is a fairly important parameter, that is, the safety of people and property. However, the magnitude of the risk, of whatever nature, affects a variety of diversified aspects (Human, economic, technical and environmental). This study presented a case study, which is sometimes paradoxical, seeing that it is the result of the combination of all risk factors and specific factors related to them connected to a fragile urban environment: Hassi-Messaoud. It is well known that Hassi-Messaoud is one of the most important city for Algeria's economy; in which the demographic development is mainly known by incessant flows of immigrants, motivated essentially by job search. This arbitrary of population distribution exposes this city to a certain danger; especially as Hassi-Messaoud is in a zone subject to a probable risk expressed here by being characteristic of an oil zone. Thus, this article aimed to provide elements of risk assessment related to oil activity. This approach could conclude that, through a schematic scale, the different types and levels of exposure and vulnerability could be identified, that is, characteristics of the urban space in question.

scholarly journals Putting resilient sustainability into strategy decisions – case studies

2018 ◽  
Vol 56 (7) ◽  
pp. 1598-1612 ◽  
Author(s):  
Julie Winnard ◽  
Jacquetta Lee ◽  
David Skipp
Keyword(s):  
Case Studies ◽  
Real World ◽  
Design Methodology ◽  
Strategic Decision ◽  
New Approach ◽  
Content Type ◽  
Industrial Companies ◽  
Different Types ◽  
Strategic Decision Support ◽  
Practical Implications

Purpose The purpose of this paper is to report the results of testing a new approach to strategic sustainability and resilience – Sustainable Resilient Strategic Decision-Support (SuReSDS™). Design/methodology/approach The approach was developed and tested using action-research case studies at industrial companies. It successfully allowed the participants to capture different types of value affected by their choices, optimise each strategy’s resilience against different future scenarios and compare the results to find a “best” option. Findings SuReSDS™ enabled a novel integration of environmental and social sustainability into strategy by considering significant risks or opportunities for an enhanced group of stakeholders. It assisted users to identify and manage risks from different kinds of sustainability-related uncertainty by applying resilience techniques. Users incorporated insights into real-world strategies. Research limitations/implications Since the case studies and test organisations are limited in number, generalisation from the results is difficult and requires further research. Practical implications The approach enables companies to utilise in-house and external experts more effectively to develop sustainable and resilient strategies. Originality/value The research described develops theories linking sustainability and resilience for organisations, particularly for strategy, to provide a new consistent, rigorous and flexible approach for applying these theories. The approach has been tested successfully and benefited real-world strategy decisions.

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