[PDF] Top 20 Knowledge-based Neural Network for Line Flow Contingency Selection and Ranking

Knowledge-based Neural Network for Line Flow Contingency Selection and Ranking

... power line-flow (PFL), pre-outage terminal voltages of the contingent line (VT1, VT2), angles at the contingent line (ANG1, ANG2), and total real power demand (TPD) are taken as input ... See full document

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KNOWLEDGE-BASED NEURAL NETWORK FOR LINE FLOW CONTINGENCY SELECTION AND RANKING

... The Line flow Contingency Selection and Ranking (CS & R) is performed to rank the critical ...Artificial Neural Network based method for MW security assessment ... See full document

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Location of UPFC in Electrical Transmission System: Fuzzy Contingency Ranking and Optimal Power Flow

... Load Flow method is performed to estimate post –contingencies of line flows and bus voltages for other contingency ...cases. Based on system operator’s past experience, each post-contingent ... See full document

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Contingency Analysis to Detect Weak Links in the Network

... purpose contingency analysis is very ...the network by contingency analysis and then going to take necessary precautions to overcome the problem, ...transmission line outages so that ... See full document

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Steady state security of a power system as a survey by contingency analysis

... load flow or the sensitivity based method. DC load flow can improve computational efficiency by only calculating branch MW flows, but there are large computational errors which are realized under ... See full document

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Transmission Reliability Cost Allocation Based on Contingency Filtering by Economic Indices in Large Power Systems

... Contingency ranking or filtering is an important step in power system security and reliability analysis, by which the solution can be ...of contingency ranking is highly dependent on the ... See full document

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Contingency Ranking and Analysis Using Mipower

... the knowledge about the system state in the event of a ...contingency. Contingency analysis technique is being widely used to predict the effect of outages like failures of equipment, transmission ... See full document

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Contingency Ranking for Power System Using Multilayer Feed Forward Neural Network

... load flow (NRLF) method.N-1 line outage contingencies are used as input features to train the neural network models, to predict the performance indices for unseen network conditions and ... See full document

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Location Identification for FACTs Device

... transmission line have to transfer power at their maximum transmission limits because of the competitive scenario of the electric market hence secured operation of power system has become one of the most issue of ... See full document

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Fast Voltage and Power Flow Contingency Ranking Using Enhanced Radial Basis Function Neural Network

... power line overloading have been responsible for power system ...function neural network (RBFNN) approach for on-line ranking of the contingencies expected to cause steady state bus ... See full document

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Contingency Analysis and Ranking on 400 Kv Karnataka Network by Using MIPOWER

... of contingency analysis and ranking using Fast Decoupled Load Flow method in this paper by using MiPower tool has been ...possible contingency cases is very large for 400kV KPTCL Bus system, ... See full document

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AN EFFICIENT SUPER PEER SELECTION ALGORITHM FOR PEER TO PEER (P2P) LIVE STREAMING NETWORK

... the Neural Network times series in MATLAB toolbox, number of neurons and number of delay considered the important variables to generate the nonlinear model for NARX and NAR models after specifying number of ... See full document

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Sentiment Neural Network(SNN) for Knowledge based Recommender System

... Recommender systems had developed a lot of importance in both academic and industry research communities. RS works as a recommendation of products to customers which would destined to their interest. The growth of an ... See full document

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A Neural Network Component for Knowledge-Based Semantic Representations of Text

... metric based on the relations of terms in some knowledge base, interpreted as a ...is based in the assumption that words which are connected by short paths in a knowledge base should have ... See full document

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Contingency Ranking Method using Fuzzy Controller

... using neural networks, two types of approach being used MFFN and ...RBF neural network yields faster result than expected in the case of performance indices ... See full document

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The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method

... passenger flow, and selects BP neural network com- bined with the characteristics of sectional passenger flow ...passenger flow of the Beijing subway Line 2 and make com- ... See full document

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STOCK MARKET PREDICTION USING BIO-INSPIRED COMPUTING: A SURVEY

... were obtained by applying these bio inspired algorithms into the field of computer science broadens the scope and viability of Bio Inspired Algorithms (BIAs) exploring new areas of application and more opportunities in ... See full document

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Research on Freeway Passenger Flow Prediction Based on Neural Network

... independence[15]. Based on results of other papers,we choose the following six factors which have an impact on the highway passenger flow as input variables, year, GDP per capital, total industrial output, ... See full document

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Artificial Neural Network Based Fault Classifier for Transmission Line Protection

... biological neural networks. A neural network is an adaptive system changing its structure due to learning phase and responds to new events in the most appropriate manner on the basis of experiences ... See full document

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Design of a nonlinear self tuning parameters algorithm for different types of PID controllers based on artificial intelligent

... self-tuning neural network PSO algorithm have stable, smooth, and optimal nonlinear values as shown in Figure (9-a and b) in order to improve the transient response of the feedback control system and ... See full document

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