1,720,976 research outputs found
A review of islanding detection techniques for renewable distributed generation systems
No full textIslanding detection of distributed generations(DGs)is one of the most important aspects of inter-connecting DGs to the distribution system.Islanding detection techniques can generally be classified as remote methods,which are associated with islanding detection on the utility sides,and local methods,which are associated with islanding detection on the DGside.This paper presents a survey of various
islanding detection techniques and their advantages and disadvantages.The paper focused on islanding
detection using a conventional and intelligent technique.A summary table that compares and contrasts
the existing methods is also presented
An Optimal Load Shedding Methodology for Radial Power Distribution Systems to Improve Static Voltage Stability Margin using Gravity Search
No full textVoltage stability is one of the major concerns in operational and planning of modern power system. Many strategies have been implemented to avoid voltage collapse, which the load shedding considered as the last option. However, optimization is needed to estimate the minimum amount to shed so as to prevent voltage instability. In this paper, an effective method is presented for estimating the optimal amount of load to be shed in a distribution system based on the gravitational search algorithm (GSA). The voltage stability margin (VSM) of the system has been considered in the objective function. The optimization problem is formulated to maximize the VSM of the system and at the same time satisfying the operation and security constraints. The optimum solution depends on the predefined constraints such as the number of load buses available to shed and the maximum amount of load permitted to shed. Simulation result conducted on the IEEE 33 bus radial distribution system shows that the system voltage stability can be improved by optimally shedding the loads at critical system buses. The results also indicate that the numbers of load buses available for load shedding does not have a significant impact on voltage stability margin, but it is highly dependent on the maximum amount of load permitted to shed
Estimation of Real Power Transfer Allocation Using Intelligent Systems
Get PDFThis paper presents application artificial intelligent
(AI) techniques, namely artificial neural network (ANN), adaptive neuro fuzzy interface system (ANFIS), to estimate the real power transfer between generators and loads. Since these AI techniques adopt supervised learning, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of both AI methods compared to that of the MNE method. The mean squared
error of the estimate of ANN and ANFIS power transfer allocation methods are 1.19E-05 and 2.97E-05, respectively. Furthermore, when compared to MNE method, ANN and ANFIS methods computes generator contribution to loads within 20.99 and 39.37msec respectively whereas the MNE method took 360 msec for the calculation of same real power transfer allocation
PATTERN RECOGNITION OF ISLANDING DETECTION USING TT-TRANSFORM
No full textIslanding is a condition where a part of the distribution system becomes electrically isolated from the remainder of the power system. The islanding detection for distributed generation (DG) units becomes an important issue in power system where the DG installations must be managed and protected during the islanded mode of operation. This paper proposed a new signal processing technique by introducing TT-transform in detecting islanding condition. This proposed method can detect the islanding condition by extracting the features of the voltage signals from the targeted DG location. The proposed technique has been simulated and analyzed in SimPowerSystem/MATLAB® simulation software. The results of the three-phase fault and islanding event were represented using 2D TT transformed plots of the original signals. The finding shows that each event case has a unique pattern so that it is possible to detect islanding conditions with accurate and faster manner
An Effective Islanding Detection and Classification Method Using Neuro-Phase Space Technique
Get PDFThe purpose of planned islanding is to construct a
power island during system disturbances which are commonly
formed for maintenance purpose. However, in most of the cases
island mode operation is not allowed. Therefore distributed
generators (DGs) must sense the unplanned disconnection from the
main grid. Passive technique is the most commonly used method for
this purpose. However, it needs improvement in order to identify the
islanding condition. In this paper an effective method for
identification of islanding condition based on phase space and neural
network techniques has been developed. The captured voltage
waveforms at the coupling points of DGs are processed to extract the
required features. For this purposed a method known as the phase
space techniques is used. Based on extracted features, two neural
network configuration namely radial basis function and probabilistic
neural networks are trained to recognize the waveform class.
According to the test result, the investigated technique can provide
satisfactory identification of the islanding condition in the
distribution system
Islanding detection in a distributed generation integrated power system using phase space technique and probabilistic neural network
No full textThe high penetration level of distributed generation (DG) provides numerous potential environmental benefits, such as high reliability, efficiency, and low carbon emissions. However, the effective detection of islanding and rapid DG disconnection is essential to avoid safety problems and equipment damage caused by the island mode operations of DGs. The common islanding protection technology is based on passive techniques that do not perturb the system but have large non-detection zones. This study attempts to develop a simple and effective passive islanding detection method with reference to a probabilistic neural network-based classifier, as well as utilizes the features extracted from three phase voltages seen at the DG terminal. This approach enables initial features to be obtained using the phase-space technique. This technique analyzes the time series in a higher dimensional space, revealing several hidden features of the original signal. Intensive simulations were conducted using the DigSilent Power Factory® software. Results show that the proposed islanding detection method using probabilistic neural network and phase-space technique is robust and capable of sensing the difference between the islanding condition and other system disturbances
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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