• KIEE International Transactions on Power Engineering
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• 제5A권2호
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• pp.177-185
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• 2005

This paper proposes an expert system that can enhance the accuracy of real-time bus reconfiguration strategy by adopting the local minimum tree search method and that can minimize the spreading effect of the fault by considering the operating condition when a main transformer fault occurs in an automated substation. The local minimum tree search method is used to expand the best-first search method. This method has the advantage that it can improve the solution performance within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. The second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules from the obtained switching candidate set. Also, this paper proposes generalized distribution substation modeling using graph theory, and a substation database based on the study results is designed.

• 대한전기학회논문지:전력기술부문A
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• 제53권10호
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• pp.565-572
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• 2004

This paper proposes an expert system which can enhance the accuracy of real-time bus reconfiguration strategy by adopting local minimum tree search method and minimize the spreading effect of the fault by considering totally the operating condition when a main transformer fault occurs in the automated substation. The local minimum tree search method to expand the best-first search method. This method has an advantage which can improve the performance of solution within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. And, second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules for the obtained switching candidate set. Also, this paper studies the generalized distribution substation modelling using graph theory and a substation database is designed based on the study result. The inference engine of the expert system and the substation database is implemented in MFC function of Visual C++. Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and local minimum tree search solution based on diversity event simulations for typical distribution substation.

• 대한전기학회논문지:전력기술부문A
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• 제53권11호
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• pp.596-603
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• 2004

This paper proposes an expert system based on the pattern recognition method which can enhance the accuracy and effectiveness of real-time bus reconfiguration strategy for the transfer of faulted load when a main transformer fault occurs in the automated substation. The minimum distance classification method is adopted as the pattern recognition method of expert system. The training pattern set is designed MTr by MTr to minimize the searching time for target load pattern which is similar to the real-time load pattern. But the control pattern set, which is required to determine the corresponding bus reconfiguration strategy to these trained load pattern set is designed as one table by considering the efficiency of knowledge base design because its size is small. The training load pattern generator based on load level and the training load pattern generator based on load profile are designed, which are can reduce the size of each training pattern set from max L/sup (m+f)/ to the size of effective level. Here, L is the number of load level, m and f are the number of main transformers and the number of feeders. The one reduces the number of trained load pattern by setting the sawmiller patterns to a same pattern, the other reduces by considering only load pattern while the given period. And control pattern generator based on exhaustive search method with breadth-limit is designed, which generates the corresponding bus reconfiguration strategy to these trained load pattern set. The inference engine of the expert system and the substation database and knowledge base is implemented in MFC function of Visual C++ Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and pattern recognition solution based on diversity event simulations for typical distribution substation.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.540-549
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• 2018

This paper proposes the method of active distribution network expansion planning considering distributed generation integration and distribution network reconfiguration. The distribution network reconfiguration is taken as the expansion planning alternative with zero investment cost of the branches. During the process of the reconfiguration in expansion planning, all the branches are taken as the alternative branches. The objective is to minimize the total costs of the distribution network in the planning period. The expansion alternatives such as active management, new lines, new substations, substation expansion and Distributed Generation (DG) installation are considered. Distribution network reconfiguration is a complex mixed-integer nonlinear programming problem, with integration of DGs and active managements, the active distribution network expansion planning considering distribution network reconfiguration becomes much more complex. This paper converts the dual-level expansion model to Second-Order Cone Programming (SOCP) model, which can be solved with commercial solver GUROBI. The proposed model and method are tested on the modified IEEE 33-bus system and Portugal 54-bus system.

• Transactions on Electrical and Electronic Materials
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• 제18권6호
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• pp.345-349
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• 2017

Reconfiguration is an important method to minimize power loss and load interruption by creating an optimal configuration of a system. Furthermore, by increasing demand and value of consumption, construction of new power plants can be postponed in networks by reconfiguration and proper arrangement of linkage switches. This method is feasible for radial networks, which create meshes of linkage switches. One convenient way to achieve a system with minimal power loss and interruption is to utilize capacitors. Optimal placement and sizing of capacitors in such applications is an important issue in the literature. In this paper, cat swarm optimization is introduced as a new metaheuristic algorithm to achieve this purpose. Simulation has been carried out in two feasible networks, 69-bus and 33-bus systems.

• Journal of Electrical Engineering and Technology
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• 제8권2호
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• pp.215-222
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• 2013

Electrical power distribution systems are critical links between the utility and customer. In general, power distribution systems have unbalanced feeders due to the unbalanced loading. The devices that dependent on balanced three phase supply are affected by the unbalanced feeders. This necessitates the balancing of feeders. The main objective of reconfiguration is to balance the loads among the phases subject to constraints such as load flow equations, capacity and voltage constraints and to reduce the real power loss, while subject to a radial network structure in which all loads must be energized. Therefore, the distribution system reconfiguration problem has been viewed as multi-objective problem. In this paper, the hybrid heuristic algorithm has been used for reconfiguration, which is the combination of fuzzy and greedy algorithms. The purpose of the introduction of greedy is to refrain the searching for the period of phase balancing. The incorporation of fuzzy helps to take up more objectives amid phase balancing in the searching. The effectiveness of the proposed method is demonstrated through modified IEEE 33 bus and modified IEEE 125 bus radial distribution system.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제14권8호
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• pp.813-817
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• 2008

지능로봇(Intelligent Robot)은 주변환경을 감지하는 센서로부터 실시간 정보를 수집하고 지능적인 기능을 수행한다. 지능로봇의 자가 재구성(Self-Reconfiguration) 능력은 외부 환경의 변화에 대응하기 위해 기능을 재구성하고, 오류가 발생하였을 때 중지 없이 스스로 회복할 수 있는 중요한 요소이다. 본 논문에서는 ESB(Enterprise Service Bus)를 사용한 지능로봇의 에이전트 기반 자가 재구성 프레임워크를 제안한다. 본 논문의 프궤임워크는 멀티에이전트 시스템을 이용한 서비스 지향 애플리케이션의 동적인 발견과 자가 재구성에 초점을 맞춘다. 지능로봇이 예외적인 상황을 만났을 때, 지능로봇은 외부의 서비스 저장소로부터 새로운 서비스를 다운로드 후 실행시켜 상황을 해결한다. 에이전트 기술은 로봇들이 상호작용하기 위한 지능적인 접근법을 제공하고, ESB는 분산된 서비스 또는 지식을 활용하고 조직하기 위한 방법을 제공한다. 또한 본 연구의 유효성을 보여주기 위해 프로토타입을 구현하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권8호
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• pp.1368-1387
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• 2011

In recent years, ubiquitous and pervasive scenarios have emerged as a complex ecosystem where differentiated software/hardware components interoperate wirelessly and seamlessly. The goal is to enable users to continuously access services and contents, and to always get the best out of their current environment and available resources. In such dynamic and flexible scenarios, the need emerges for flexible and general solutions for continuous runtime self-reconfiguration and self-optimization of ubiquitous support software systems. This paper proposes a fully reconfigurable middleware approach that aims at reconfiguring complex software systems made up of heterogeneous off-the-shelf components from both functional and non-functional perspectives. Our middleware can also extend already existing and non-reconfigurable middleware/applications in an easy and flexible way, with no need to re-design them. The proposed design principles have been practically applied to the implementation of a runtime self-reconfigurable middleware called Off-The-Shelf Ready To Go (OTS-RTG), implemented on top of iPOJO. The reported experimental results both exhibit a limited overhead and show the wide applicability of the proposed solution to many application scenarios, including complex, industrial, Enterprise Service Bus-based ones.

• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1229-1239
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• 2014

Optimal Distributed Generation (DG) output and reconfiguration are among the well accepted approach to reduce power loss in a distribution network. In the past, most of the researchers employed optimal DG output and reconfiguration separately. In this work, a simultaneous DG output and reconfiguration analysis is proposed to maximize power loss reduction. The impact of the separated analysis and simultaneous analysis are investigated. The test result on the 33 bus distribution network with 3 units of DG operated in PV mode showed the simultaneous analysis gave the lowest power loss (global optimal) and faster results compared to other combined methods. All the analyses for optimizing the DG as well as reconfiguration are used the Artificial Bee Colony Optimization technique.

• 대한전기학회논문지:전력기술부문A
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• 제50권2호
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• pp.76-82
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• 2001

This paper presents a approach for a service restoration and optimal reconfiguration of distribution network using Genetic algorithm(GA) and Tabu search(TS) method. Restoration and reconfiguration problems in distribution network are difficult to solve in short times, because distribution network supplies power for customers combined with many tie-line switches and sectionalizing switches. Furthermore, the solutions of these problems have to satisfy radial operation conditions and reliability indices. To overcome these time consuming and sub-optimal problem characteristics, this paper applied Genetic-Tabu algorithm. The Genetic-Tabu algorithm is a Tabu search combined with Genetic algorithm to complement the weak points of each algorithm. The case studies with 7 bus distribution network showed that not the loss reduction but also the reliability cost should be considered to achieve the economic service restoration and reconfiguration in the distribution network. The results of suggested Genetic-Tabu algorithm and simple Genetic algorithm are compared in the case study also.