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Optimal placement of switches in a radial distribution network for reliability improvement

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2016年 76卷 53-68页

作者： Ray, Saheli Bhattacharya, Aniruddha Bhattacharjee, Subhadeep Natl Inst Technol Agartala Agartala 799046 India

This paper proposes differential search (DS) algorithm to solve distribution system reliability optimization problem. Optimum number and location of remote control switch (RCS) have been found, in order to enhance reliability of a radial distribution system. A multi-objective formulation has been considered with a view to enhance reliability at a compromised cost. DS algorithm utilizes the Brownian-like random-walk movement used by an organism to migrate. Simulation results obtained by DS algorithm have been compared with that of particle swarm optimization (PSO), differential evolutionary algorithm (DE), genetic algorithm (GA), ant colony optimization (ACO) and gravitational search algorithm (GSA). Results show that DS algorithm provides considerably superior performance, in terms of quality of solution obtained and computational efficiency. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： differential search algorithm Multi-objective function Radial distribution system Remote control switches Repair time Restoration time

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Multi-objective sidetracking horizontal well trajectory optimization in cluster wells based on DS algorithm

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2016年 147卷 771-778页

作者： Wang, Zhiyue Gao, Deli Liu, Jianjun China Univ Petr MOE Key Lab Petr Engn Beijing 102249 Peoples R China China Univ Petr Coll Sci Beijing 102249 Peoples R China

To optimize sidetracking horizontal well trajectory in cluster wells, a new multi-objective optimization model has been established. The new model synthetically considers the total trajectory length, the well profile energy and the accuracy of target hitting as the objective functions and takes the anti-collision with adjacent well as constraint. A novel heuristic algorithm based on DS is presented to solve the established optimization model, and the constraint is handled by a penalty method using an S-type penalty function. The comparisons between multi-objective optimization and single-objective optimization indicate that multi-objective optimization is more superior in sidetracking well trajectory optimization which can obtain a relatively short total trajectory length, a low well profile energy and an extremely high accuracy of target hitting. Furthermore, the optimization model considering anti-collision can ensure the minimum distance with adjacent well no less than the safety distance which can avoid collision in cluster wells. At last, the convergence and stability of the proposed algorithm have been discussed, and the results indicate that d-DS has good convergence and numerical stability, thus the d-DS algorithm is excellent for solving trajectory optimization problem.

关键词： Multi-objective optimization Sidetracking horizontal well Collision avoidance differential search algorithm Dynamic penalty function method

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Sympathetic Trippings Blocking in Over Current Relay Coordination algorithm during Steady State & Transient Network Topologies

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INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS 2016年第3期17卷 311-326页

作者： Singh, Manohar Panigrahi, B. K. Vishnuvardhan, T. Cent Power Res Inst Power Syst Div Bangalore Karnataka India Indian Inst Technol Dept Elect Engn Delhi India

In this paper an improved over current relay coordination protection technique is proposed. The proposed technique eliminates the sympathetic/nuisance tripping in an interconnected distribution system. Nuisance trippings are eliminated by incorporating the additional selectivity constraints in conventional over current relay coordination problem. Whenever the fault is cleared only from one end of the line in bidirectional fault feed lines, transient network configuration comes into existence. Transient network configuration causes the redistribution of fault in the distribution system and leads to further nuisance tripping of relays. This problem in this paper is solved by minimising the operating time gap between primary relays located at near end and far end of a faulty line to the best minimum possible value. The differential search algorithm is applied for optimization of highly non-linear over current relay coordination problem in this paper. The result presented in this paper shows that the proposed over current relay coordination technique is immune against the sympathetic/nuisance tripping and operating time difference between primary relays at near end and far end is also minimised within acceptable time margin successfully.

关键词： relay coordination sympathetic trippings distribution system differential search algorithm transient network configuration

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A new segmentation method for non-ideal iris images using morphological reconstruction FCM based on improved DSA

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SN APPLIED SCIENCES 2021年第1期3卷 53页

作者： Rapaka, Satish Rajesh Kumar, P. Katta, Miranji Lakshminarayana, K. Bhupesh Kumar, N. Sir CR Reddy Coll Engn Dept Elect & Commun Engn Eluru 534007 Andhra Pradesh India Andhra Univ Dept Elect & Commun Engn Coll Engn Visakhapatnam 530003 Andhra Pradesh India Sir CR Reddy Coll Engn Dept Elect & Elect Engn Eluru 534007 Andhra Pradesh India

In any accurate iris recognition system segmentation of iris plays a vital role. The noise, specular reflections, eyelid/eyelash obstruction, and intensity inhomogeneities in an image make the segmentation more difficult. In this paper, a novel technique is proposed to segment the iris from images that are taken under uncooperative image conditions. The proposed method segments the image in two stages. Firstly, Morphological reconstruction fuzzy c-means clustering (MRFCM) based on an improved differential search algorithm is implemented before the segmentation step. The MRFCM can preserve image contours even in the presence of noise. Secondly, the iris is isolated from the undesired regions of an eye image by implementing geodesic active contours driven by a modified stopping criterion on the resultant images of the pre-segmentation step. The accuracy of the method presented has been tested on the databases such as CASIAv3-Interval, UBIRISv1, MMU1, IITDv1, and MICHE-I. The segmentation accuracy has been demonstrated and compared with other existing methods present in the literature. The obtained results are promising and the proposed model is outperformed the existing methods.

关键词： Iris segmentation FCM clustering Morphological reconstruction differential search algorithm Geodesic active contours

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Memetic algorithm with Adaptive Local search Depth for Large Scale Global Optimization

Memetic Algorithm with Adaptive Local Search Depth for Large...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Liu, Can Li, Bin Univ Sci & Technol China Nat Inspired Computat & Applicat Lab Hefei 230026 Peoples R China Univ Sci & Technol China CAS Key Lab Hefei 230026 Peoples R China

ISBN: (纸本)9781479914883

Memetic algorithms (MAs) have been recognized as an effective algorithm framework for solving optimization problems. However, the exiting work mainly focused on the improvement for search operators. Local search Depth (LSD) is a crucial parameter in MAs, which controls the computing resources assigned for local search. In this paper, an Adaptive Local search Depth (ALSD) strategy is proposed to arrange the computing resources for local search according to its performance dynamically. A Memetic algorithm with ALSD (MA-ALSD) is presented, its performance and the effectiveness of ALSD are testified via experiments on the LSGO test suite issued in CEC'2012.

关键词： Memetic algorithms Local search Depth differential search algorithm Solis and Wets' algorithm

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Minimization of Operating Time Gap Between Primary Relays at Near and Far Ends in Overcurrent Relay Coordination

Minimization of Operating Time Gap Between Primary Relays at...

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North American Power Symposium (NAPS)

作者： Singh, Manohar Panigrahi, B. K. Cent Power Res Inst Bangalore 560080 Karnataka India Indian Inst Technol Elect Engn Dept Delhi 110016 India

ISBN: (纸本)9781479959044

In bidirectional fault feed distribution lines, the fault should be cleared from both the fault feeding sources ends simultaneously, so that impact of faults currents on the exiting over current relay coordination will be minimum. In existing over current relay coordination algorithms, it is observed that operating time gaps between primaries over current relays at near end and far end of faulted line are quite enough. This time gaps may redistribute the fault currents in the power networks which leads to cascading type of over current relay miscoordination in a properly coordinated power network. In this paper, the over current relay coordination problem formulation is modified in such a way to minimize the operating time gap between the primary over current relays at near and far ends with in a desired time margin such that the chance of redistribution of fault currents in the distribution network is eliminated. The proposed modified over current relay coordination algorithm is implemented in 8 bus test distribution system.

关键词： coordination time margin differential search algorithm graph theory over current relays primary relays

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DSA/WDO Based PI Controller tuning for D-STATCOM for Reactive power Compensation

DSA/WDO Based PI Controller tuning for D-STATCOM for Reactiv...

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IEEE Uttar Pradesh Section Conference on Electrical Computer and Electronics (UPCON)

作者： Patel, Pritam Rout, Srikant Swain, Milan Patel, Punyaban Natl Inst Technol Dept Elect Engn Agartala India Chhatrapati Shivaji Inst Technol Dept Comp Scince & Engn Durg Chhattisgarh India

ISBN: (纸本)9781467385077

Distribution static synchronous compensator (DSTACOM) has a greater importance in modern distribution level for reactive power compensation dynamically and power quality improvement. In this paper an effort has been given to design a D-STATCOM, an essential shunt Flexible AC Transmission Systems (FACTS) device using decoupled current control method for three phase three wire system to compensate the reactive power. It is difficult as well as time consuming process to get the proper tuning parameters of PI controller for D-STATCOM using conventional methods. An attempt has been made by implementing two recently developed global optimization techniques named differential search algorithm (DSA) and Wind Driven optimization (WDO) for proper tuning of parameters by minimizing the integral square error (ISE) for both outer voltage controller and inner current controller simultaneously. The PI gain calculated by DSA and WDO shows in terms of reduction of error, improvement of overshoot in capacitor voltage waveform, convergence speed and some other parameters of the circuit. Comparative study of both the methods with trial and error method reveals that DSA algorithm based PI controller tuning method gives more optimized results.

关键词： D-STATCOM Decoupled current control Reactive power compensation differential search algorithm Wind driven optimization

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Relaxation of non-convex problem as an initial solution of Meta-heuristics for Energy Resource Management

Relaxation of non-convex problem as an initial solution of M...

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General Meeting of the IEEE-Power-and-Energy-Society

作者： Soares, Joao Lobo, Cristina Silva, Marco Morais, Hugo Vale, Zita Polytech Porto ISEP IPP GECAD Knowledge Engn & Decis Support Res Ctr Rua Dr Antonio Almeida 431 P-4200072 Oporto Portugal

ISBN: (纸本)9781467380409

Energy resources management is an important topic in the context of Smart Grids (SG) and MicroGrids (MG). Virtual Power Players (VPP) emerge as aggregator entities responsible for managing energy resources in SG and MG. In this paper modern meta-heuristics are compared with their hybrid version that uses a deterministic method as initial solution. The meta-heuristics implemented are differential search algorithm (DSA) and Quantum Particle Swarm Optimization (QPSO) to solve the hard combinatorial scheduling problem. The deterministic method employs a relaxation of the non-convex Mixed Integer Non-Linear Programming (MINLP) formulation in order to reduce the computational burden and the number of iterations in meta-heuristics. The implemented methods are tested with a 33-bus distribution network, 1800 Electric Vehicles (EV), 15 fixed storage, 66 Distributed Generation (DG), 10 energy suppliers and 1 utility-scale wind generation facility. The results show the excellent performance of the DSA, QPSO and hybrid approaches.

关键词： Day-Ahead Scheduling differential search algorithm Energy Resources Management PSO

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NONDESTRUCTIVE DETECTION OF ANCHORAGE QUALITY OF ROCK BOLT BASED ON DS-DBN-SVM 17

NONDESTRUCTIVE DETECTION OF ANCHORAGE QUALITY OF ROCK BOLT B...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Zheng, Hai-Qing Yang, Ya-Ru Sun, Xiao-Yun Wen, Cheng Shijiazhuang Tiedao Univ Sch Elect & Elect Engn Shijiazhuang 050043 Hebei Peoples R China

ISBN: (纸本)9781538652145

Deep learning is a hot topic in the field of machine learning, which provides a new method for the nondestructive testing of bolt anchorage. Aiming at the importance of identifying the type of bolt defects, this paper proposes a DS-DBN-SVM(differential search-Deep belief network-Support vector machine) model for identifying the type of bolt anchorage defects. The DS algorithm is used to optimize the weights and thresholds of the DBN network. The original acceleration signal of the anchor is used as the input of the DS-DBN model to extract the high-level features of the signal. Finally, the SVM classifier is used for defect identification. To assess the effectiveness of the method, and compare it with the traditional classification methods. The results show that the defect recognition effect of this method is better than the traditional defect recognition method, and the recognition rate reaches 95.45%.

关键词： Rock bolt Defect identification Deep belief network differential search algorithm

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A Review on Optimization algorithm for Deep Learning Method in Bioinformatics Field

A Review on Optimization Algorithm for Deep Learning Method ...

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IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES)

作者： Yousoff, Siti Noorain Mohmad Baharin, Amirah Abdullah, Afnizanfaizal Univ Teknol Malaysia Fac Comp Synthet Biol Res Grp Utm 81310 Johor Malaysia

ISBN: (纸本)9781467377911

In the past few years, deep learning has been used widely in bioinformatics area to solve common problems such as protein sequence prediction, phylogenic inferences, multiple sequence alignment and many more. It has been in the spotlight as a powerful approach which makes significant advances in taking care of the issues that haunt artificial intelligence community for many years. However, several weaknesses such as trap at local minima, lower performance and high computational time still occur in deep learning. Therefore, global optimization technique such as differential search algorithm can be used to assist deep learning method in order to get best finding result and data. This review will cover fundamental of deep learning and their involvement in bioinformatics field as well as implementation of differential search algorithm and their involvement in bioinformatics field.

关键词： bioinformatics deep learning neural network backpropagation optimization algorithm differential search algorithm

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