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Coordination of Directional Overcurrent Relays Using the backtracking search algorithm

JOURNAL OF ELECTRICAL SYSTEMS 2016年第2期12卷 387-405页

作者： Bouchekara, Houssem Rafik El-Hana Zellagui, Mohamed Abido, Mohammad Ali Univ Freres Mentouri Constantine Dept Elect Engn LEC Lab Constantine Algeria Univ Batna 2 Dept Elect Engn LSP IE Lab Batna Algeria King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran Saudi Arabia

The Directional Overcurrent Relays (DOCRs) coordination problem is of paramount importance for power system protection. This paper uses a new metaheuristic method called the backtracking search algorithm (BSA) to solve the DOCRs coordination problem. The coordination problem has been formulated as an optimization problem to minimize the operating time of all the primary relays. The proposed algorithm has been implemented and applied to three test systems including the 6-bus, the 8-bus and the 15-bus test systems. Furthermore, a reliable approach has been developed to compare the results obtained using the proposed BSA with those obtained using other well-known metaheuristics. The results show the superiority of BSA over other methods in solving DOCRs coordination problems.

关键词： Power system protection overcurrent relay coordination optimization backtracking search algorithm

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Wind Integrated Multi Area Economic Dispatch using backtracking search algorithm 6

Wind Integrated Multi Area Economic Dispatch using Backtrack...

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6th IEEE International Conference on Power Systems (ICPS)

作者： Dubey, Hari Mohan Pandit, Manjaree Tyagi, Nitin Panigrahi, B. K. MITS Dept Elect Engn Gwalior India IIT Dept Elect Engn Delhi India

ISBN: (纸本)9781509001286

This paper presents a solution of multi area economic dispatch (MAED) problem with wind integration using backtracking search algorithm (BSA), a novel optimization technique. BSA is a stochastic search algorithm with only one control parameter and mutation and crossover operators for exploration and exploitation of the search space for problem under consideration. It can easily take care of various complex operating constraints, which is difficult to solve using any mathematical approaches. To show its efficiency, BSA algorithm is applied to two different categories of MAED problems. Category I has a two area network having 40 and 140 power generating units with valve point loading effects (VPL), ramp rate limits (RRL) and prohibited operating zones (POZ) and category II presents simulation study of MAED problem with wind integration. The outcome of simulation results in terms of operating cost are compared with other recently published relevant approaches and are found to be better.

关键词： backtracking search algorithm Multi area Economic dispatch wind over estimation and wind under estimation prohibited operating zones

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Best Guided backtracking search algorithm for Numerical Optimization Problems 9th

Best Guided Backtracking Search Algorithm for Numerical Opti...

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9th International Conference on Knowledge Science, Engineering, and Management (KSEM)

作者： Zhao, Wenting Wang, Lijin Wang, Bingqing Yin, Yilong Shandong Univ Sch Comp Sci & Technol Jinan 250101 Peoples R China Fujian Agr & Forestry Univ Coll Comp & Informat Sci Fuzhou 350002 Peoples R China Shandong Univ Finance & Econ Sch Comp Sci & Technol Jinan 250014 Peoples R China

ISBN: (纸本)9783319476506;9783319476490

backtracking search algorithm is a promising stochastic search technique by using its historical information to guide the population evolution. Using historical population information improves the exploration capability, but slows the convergence, especially on the later stage of iteration. In this paper, a best guided backtracking search algorithm, termed as BGBSA, is proposed to enhance the convergence performance. BGBSA employs the historical information on the beginning stage of iteration, while using the best individual obtained so far on the later stage of iteration. Experiments are carried on the 28 benchmark functions to test BGBSA, and the results show the improvement in efficiency and effectiveness of BGBSA.

关键词： backtracking search algorithm Best guided Historical information Numerical optimization problems

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A backtracking search algorithm for Distribution Network Reconfiguration Problem

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AETA International Conference

作者： Thuan Thanh Nguyen Hiep Ngoc Pham Anh Viet Truong Tuan Anh Phung Thang Trung Nguyen HCMC Univ Technol & Educ Fac Elect & Elect Engn 1 Vo Van Ngan St Ho Chi Minh City Vietnam Dong An Polytech 30-4 St Di An Dist Binh Duong Prov Vietnam Ha Noi Univ Technol 1 Dai Co Viet St Hanoi Vietnam Ton Duc Thang Univ Fac Elect & Elect Engn 19 Nguyen Huu Tho StDist 7 Ho Chi Minh City Vietnam

ISBN: (纸本)9783319272474;9783319272450

This paper proposes a distribution network reconfiguration (DNR) methodology based on a backtracking search algorithm (BSA) for minimizing active power loss and minimizing voltage deviation. The BSA is a new evolutionary algorithm for solving of numerical optimization problems. It uses a single control parameter and two crossovers and mutation strategies for powerful exploration of the problem's search space. The effectiveness of the proposed BSA has been tested on 69-node distribution network system and the obtained test results have been compared to those from other methods in the literature. In addition to BSA, two other algorithms-particle swarm optimization (PSO) and cuckoo search algorithm (CSA)-are implemented for comparisons. The simulation results show that the proposed BSA can be an efficient and promising method for distribution network reconfiguration problems.

关键词： Distribution network reconfiguration Cuckoo search algorithm Particle swarm optimization backtracking search algorithm Power loss reduction

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backtracking search algorithm with three constraint handling methods for constrained optimization problems

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EXPERT SYSTEMS WITH APPLICATIONS 2015年第21期42卷 7831-7845页

作者： Zhang, Chunjiang Lin, Qun Gao, Liang Li, Xinyu Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Hubei Peoples R China

A new evolutionary algorithm, backtracking search algorithm (BSA), is applied to solve constrained optimization problems. Three constraint handling methods are combined with BSA for constrained optimization problems;namely feasibility and dominance (FAD) rules, epsilon-constrained method with fixed control way of epsilon value and a proposed epsilon-constrained method with self-adaptive control way of epsilon value. The proposed method controls epsilon value according to the properties of current population. This kind of epsilon value enables algorithm to sufficiently search boundaries between infeasible regions and feasible regions. It can avoid low search efficiency and premature convergence which happens in fixed control method and FAD rules. The comparison of the above three algorithms demonstrates BSA combined epsilon-constrained method with self-adaptive control way of epsilon value (BSA-SA epsilon) is the best one. The proposed BSA-SA epsilon also outperforms other five classic and the latest constrained optimization algorithms. Then, BSA-SA epsilon has been applied to four engineering optimization instances, and the comparison with other algorithms has proven its advantages. Finally, BSA-SA epsilon is used to solve the car side impact design optimization problem, which illustrates the wide application prospects of the proposed BSA-SA epsilon. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： backtracking search algorithm Constrained optimization problem Feasibility and dominance rules epsilon-constrained method Engineering optimization

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backtracking search algorithm for effective and efficient surface wave analysis

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JOURNAL OF APPLIED GEOPHYSICS 2015年 114卷 19-31页

作者： Song, Xianhai Zhang, Xueqiang Zhao, Sutao Li, Lei China Univ Geosci Inst Geophys & Geomat Wuhan 430074 Hubei Peoples R China

Surface wave dispersion analysis is widely used in geophysics to infer near-surface shear (S)-wave velocity profiles for a wide variety of applications. However, inversion of surface wave data is challenging for most local-search methods due to its high nonlinearity and to its multimodality. In this work, we proposed and implemented a new Rayleigh wave dispersion curve inversion scheme based on backtracking search algorithm (BSA), a novel and powerful evolutionary algorithm (EA). Development of BSA is motivated by studies that attempt to develop an algorithm that possesses desirable features for different optimization problems which include the ability to reach a problem's global minimum more quickly and successfully with a small number of control parameters and low computational cost, as well as robustness and ease of application to different problem models. The proposed inverse procedure is applied to nonlinear inversion of fundamental-mode Rayleigh wave dispersion curves for near-surface S-wave velocity profiles. To evaluate calculation efficiency and effectiveness of BSA, four noise-free and four noisy synthetic data sets are firstly inverted. Then, the performance of BSA is compared with that of genetic algorithms (GA) by two noise-free synthetic data sets. Finally, a real-world example from a waste disposal site in NE Italy is inverted to examine the applicability and robustness of the proposed approach on real surface wave data. Furthermore, the performance of BSA is compared against that of GA by real data to further evaluate scores of BSA. Results from both synthetic and actual data demonstrate that BSA applied to nonlinear inversion of surface wave data should be considered good not only in terms of the accuracy but also in terms of the convergence speed. The great advantages of BSA are that the algorithm is simple, robust and easy to implement. Also there are fewer control parameters to tune. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Swarm intelligence Evolutionary algorithms backtracking search algorithm Surface waves Dispersion curves

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backtracking search algorithm-based optimal power flow with valve point effect and prohibited zones

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ELECTRICAL ENGINEERING 2015年第2期97卷 101-110页

作者： Kilic, Ulas Celal Bayar Univ Fac Hasan Ferdi Turgutlu Technol Dept Mechatron Engn Turgutlu Manisa Turkey

This paper presents a solution technique for optimal power flow (OPF) with valve-point effect and prohibited operating zones of power systems using backtracking search algorithm (BSA). BSA is a new population-based evolutionary algorithm. The most important property of the algorithm is not over precision to initial of value, unlike many other heuristic algorithms. The proposed algorithm having four different cases is tested on IEEE-30 bus test system. The results of BSA are compared to those reported in literature. Thus, its validity for so applications in this area is proved. In this paper, OPF problem of power systems is solved by BSA for the first time.

关键词： backtracking search algorithm Optimal power flow Valve point effect Prohibited zones

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Study impact of various load models on DG placement and sizing using backtracking search algorithm

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APPLIED SOFT COMPUTING 2015年 30卷 803-811页

作者： El-Fergany, Attia Zagazig Univ Fac Engn Dept Elect Power & Machines POB 44519 Zagazig Egypt

In this article, a meta-heuristic technique based on a backtracking search algorithm (BSA) is employed to produce solutions to ascertain distributed generators (DGs). The objective is established to reduce power loss and improve network voltage profile in radial distribution networks by determining optimal locations and sizes of the DGs. Power loss indices and bus voltages are engaged to explore the initial placement of DG installations. The study cares with the DG type injects active and reactive power. The proposed methodology takes into consideration four load models, and their impacts are addressed. The proposed BSA-based methodology is verified on two different test networks with different load models and the simulation results are compared to those reported in the recent literature. The study finds that the constant power load model among various load models is sufficed and viable to allocate DGs for network loss and voltage studies. The simulation results reveal the efficacy and robustness of the BSA in finding the optimal solution of DGs allocation. (C) 2015 Elsevier By. All rights reserved.

关键词： Distributed generation Network losses Load models backtracking search algorithm

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Design of Multi-objective UPFC Employing backtracking search algorithm for Enhancement of Power System Stability 18

Design of Multi-objective UPFC Employing Backtracking Search...

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18th International Conference on Computer and Information Technology (ICCIT)

作者： Shahriar, Mohammad Shoaib Shafiullah, Md Asif, Mohammed Afzal Hasan, Md Mahmudul Rafiuzzaman, Md King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran Saudi Arabia Independent Univ Dept Elect & Elect Engn Dhaka Bangladesh

ISBN: (纸本)9781467399302

In the arena of power system, small signal stability is one of the most important issue to be settled down. In relatively weak tie line interconnections, these low frequency oscillations are observed. Use of Flexible AC Transmission System (FACTS) devices is playing most important roles in damping out of those oscillations. Unified Power Flow Controller (UPFC), one of the key members of FACTS family is being used in long and high voltage transmission networks of modern power system. Tuning of the UPFC parameters in real time power system application is a multi-objective optimization problem. In this paper the parameters of UPFC has been optimized employing a novel optimization approach, backtracking search algorithm (BSA). The efficacy of the proposed BSA tuned UPFC has been investigated by comparing the time domain simulation results with fixed gain conventional UPFC. Additionally, the Eigenvalues of optimized and conventional UPFC of the power system has also been compared.

关键词： backtracking search algorithm Eigenvalue FACTS Multi-objective Optimization Power System Stability UPFC

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Opposition-Based backtracking search algorithm for Numerical Optimization Problems 5th

Opposition-Based Backtracking Search Algorithm for Numerical...

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5th International Conference on Intelligence Science and Big Data Engineering (IScIDE)

作者： Xu, Qingzheng Guo, Lemeng Wang, Na Xu, Li Xian Commun Inst Xian 710106 Peoples R China Unit 73689 PLA Nanjing 210042 Jiangsu Peoples R China

ISBN: (纸本)9783319238623;9783319238616

backtracking search algorithm (BSA) is a novel global optimization algorithm for solving real-valued numerical optimization problems. In this paper, several opposition-based BSAs are proposed and compared comprehensively. Its key character is that a candidate solution and its corresponding opposite solution are considered simultaneously to achieve an optimal approximation. The simulation results on 58 widely used benchmark problems demonstrate that, the opposition-based learning method can significantly improve the performance of original BSA. In addition, the proposed algorithm performance has evident positive correlation with the utilization rate of opposite points.

关键词： backtracking search algorithm Opposition-Based Learning Number of function calls Utilization rate of opposite points

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