Sharif Digital Repository

This chapter presents the optimal switch deployment in distribution systems. First, an explanation regarding different types of switches and their functionality is introduced. Then, a fundamental description of fault management procedure in distribution networks is presented. Thereafter, the mathematical formulation of optimal fault management process is described. Optimal switch deployment problem is formulated in the format of mixed integer programming (MIP). The impact of remote controlled switch (RCS) and manual switch (MS) is scrutinized on the interruption cost once they are installed either individually or simultaneously. The concept of switch malfunctions is explained and the... 

Fault indicator (FI) plays a crucial rule in enhancing service reliability in distribution systems. This device brings substantial benefits for fault management procedure by speeding up fault location procedure. This paper intends to develop a new optimization model to optimally deploy FI in distribution systems. The proposed model aims to consider a tradeoff between the total customer interruption cost and FI relevant costs, including capital investment, installation, and maintenance costs. As the main contribution of this paper, the problem is formulated in mixed integer programing, which guarantees global optimum solution achieved in an effective runtime. Moreover, the model takes... 

The inclusion of smart grid features such as demand response (DR) and network automation for capacity planning of substation transformers may provide substantial monetary savings. This paper proposes an optimization model for quantification of the savings in capacity management of substation transformers over long-run. The proposed model incorporates the DR as a resource to decrease the outage cost during contingencies while considering existing switching types for load transfer between substations. The model provides optimal selection and scheduling of multistage transformer installations and their refurbishments by considering all the costs associated with them including investment,... 

The great share of interruptions in distribution networks motivates distribution decision makers to establish various reliability enhancement strategies. Amongst, deploying remote controlled switch (RCS) can make a crucial contribution to the reduction of interruption costs. Nevertheless, the stochastic nature of contingencies affects the RCS worth and imposes substantial financial risk to RCS deployment projects. This paper proposes a mathematical model to consider the risk in the optimal RCS deployment problem. The model determines the number and location of RCSs such that the expected profit is maximized while financial risk is minimized. The risk is modeled through conditional... 

Remote controlled switch deployment in distribution networks is usually justified via comparing the required investment with the expected decrease in interruption costs. Although the investment is known prior to the implementation, the stochastic nature of contingencies imposes significant uncertainty on interruption costs. The uncertainty may impose substantial financial risks on the distribution company. This paper aims at evaluating the financial risk and key affecting parameters. For doing so, a step-by-step method is presented to evaluate the risk. The method captures the stochastic nature of contingencies through a sequential Monte Carlo simulation approach. A mathematical formulation... 

The great share of interruptions in distribution networks motivates distribution decision makers to establish various reliability enhancement strategies. Amongst these strategies, deploying remote controlled switch (RCS) can make a crucial contribution to the reduction of interruption costs. Nevertheless, the stochastic nature of contingencies affects RCS worth and imposes substantial financial risk to RCS deployment projects. This paper proposes a mathematical model to consider the risk in the optimal RCS deployment problem. The model determines the number and location of RCSs such that the expected profit is maximized while financial risk is minimized. The risk is modeled through... 

Remote controlled switch deployment in distribution networks is usually justified via comparing the required investment with the expected decrease in interruption costs. Although the investment is known prior to the implementation, the stochastic nature of contingencies imposes significant uncertainty on interruption costs. The uncertainty may impose substantial financial risks on the distribution company. This paper aims at evaluating the financial risk and key affecting parameters. For doing so, a step-by-step method is presented to evaluate the risk. The method captures the stochastic nature of contingencies through a sequential Monte Carlo simulation approach. A mathematical formulation... 

In the past decade, distribution network operators have been broadly engrossed toward automated distribution networks. The operators acknowledge network automation as an efficient investment toward a better service reliability. This paper aims to provide a new long-term cost/benefit analysis for an optimal level of distribution network automation. In the analysis, reduction in customer outage cost is considered as the benefit of implementing automation systems with capital investment, and annual operation and maintenance costs. In the Finnish regulation model, there is a special incentive based on customer outage cost reduction. As the main contribution of this paper, the impact of earth... 

We propose a cost estimation model based on a fuzzy rule backpropagation network, configuring the rules to estimate the cost under uncertainty. A multiple linear regression analysis is applied to analyze the rules and identify the effective rules for cost estimation. Then, using a dynamic programming approach, we determine the optimal path of the manufacturing network. Finally, an application of this model is illustrated through a numerical example showing the effectiveness of the proposed model for solving the cost estimation problem under uncertainty  

In the past decade, distribution network operators have been broadly engrossed toward automated distribution networks. The operators acknowledge network automation as an efficient investment toward a better service reliability. This paper aims to provide a new long-term cost/benefit analysis for an optimal level of distribution network automation. In the analysis, reduction in customer outage cost is considered as the benefit of implementing automation systems with capital investment, and annual operation and maintenance costs. In the Finnish regulation model, there is a special incentive based on customer outage cost reduction. As the main contribution of this paper, the impact of earth... 

Implementing automation system in distribution networks needs a huge investment that usually cannot be funded entirely in a short period of time. So distribution companies (DISCOs) should develop long-term plans to equip their network with automation technologies as far as economically justifiable. Aiming to provide a methodology for development such plans, this paper presents a novel multistage planning model for implementing distribution automation system considering all main hardware and software infrastructures. The proposed method optimally determines the type, location, and time in which an equipment or infrastructure must be added to network considering the network capacity expansion... 

In recent years, electromyogram signal (EMG) feature selection, based on wavelet transform, has received considerable attention. This study introduces a new multiwavelet function for surface EMG (sEMG) signal intended for tasks that involve hand movement recognition. To create the new wavelet function, several types of well known mother wavelet were exploited and through their integration the proposed mother wavelet was generated. The proposed wavelet function closely reproduced the characteristics of the EMG signal, while increasing the recognition accuracy of hand movements. We used eight unique classes of hand motions and considered the ability of various mother wavelets and the proposed... 

Background: Electromyography (EMG) is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG) can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling the prosthetic hands either have limited functions or can only be used to perform simple movements or use excessive amount of electrodes in order to achieve acceptable results. In an attempt to overcome these problems we have proposed an intelligent system to recognize hand movements and have provided... 

In this paper, the performance of five classifiers in P300 speller paradigm are compared. Theses classifiers are Linear Support Vector Machine (LSVM), Gaussian Support Vector Machine (RSVM), Neural Network (NN), Fisher Linear Discriminant (FLD), and Kernel Fisher Discriminant (KFD). In classification of P300 waves, there has been a trend to use SVM classifiers. Although they have shown a good performance, in this paper, it is shown that the FLD classifiers outperform the SVM classifiers. FLD classifier uses only ten channels of the recorded electroencephalogram (EEG) signals. This makes them a very good candidate for real-time applications. In addition, FLD approach does not need any...