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Control reconfiguration

About: Control reconfiguration is a research topic. Over the lifetime, 22423 publications have been published within this topic receiving 334217 citations.


Papers
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Journal ArticleDOI
TL;DR: A novel hybrid method of metaheuristic and heuristic algorithms is presented in order to boost robustness and shorten the computational runtime to achieve network minimum loss configuration in the presence of DGs.
Abstract: Different types of distributed generation (DG) are broadly used and optimally placed in a distribution system to improve its performance. Since the network configuration affects the system operational conditions, the network reconfiguration and DG placement should be manipulated simultaneously. Nevertheless, the complexity of the problem may prevent from achieving the optimal solution. This paper presents a novel hybrid method of metaheuristic and heuristic algorithms, in order to boost robustness and shorten the computational runtime to achieve network minimum loss configuration in the presence of DGs. The developed backward/forward power flow is adopted to consider the PV(Q) model of DG. Moreover, different patterns of load types are taken into consideration to perform a practical study. To assess the capabilities of the proposed method, simulations are carried out on IEEE 33-bus and 83-bus practical distribution network of Taiwan Power Company. Furthermore, the proposed method is applied to a 33-bus unbalanced distribution network to verify its applicability in unbalanced distribution systems. The obtained results demonstrate the effectiveness of the proposed method to find optimal status of switches, as well as locations and sizes of DG units, in a rather shorter time than other approaches in the literature.

114 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a long-term planning method to maximize the benefits of network reconfiguration and distributed generation (DG) allocation in distribution networks, taking into account the uncertainty related to renewable DG output power and the load variability.

114 citations

Proceedings ArticleDOI
22 Jun 2009
TL;DR: A reinforcement learning approach for autonomic configuration and reconfiguration of multi-tier web systems is proposed and can drive the system into a near-optimal configuration setting in less than 25 trial-and-error iterations.
Abstract: In a web system, configuration is crucial to the performance and service availability. It is a challenge, not only because of the dynamics of Internet traffic, but also the dynamic virtual machine environment the system tends to be run on. In this paper, we propose a reinforcement learning approach for autonomic configuration and reconfiguration of multi-tier web systems. It is able to adapt performance parameter settings not only to the change of workload, but also to the change of virtual machine configurations. The RL approach is enhanced with an efficient initialization policy to reduce the learning time for online decision. The approach is evaluated using TPC-W benchmark on a three-tier website hosted on a Xen-based virtual machine environment. Experiment results demonstrate that the approach can autoconfigure the web system dynamically in response to the change in both workload and VM resource. It can drive the system into a near-optimal configuration setting in less than 25 trial-and-error iterations.

114 citations

Book ChapterDOI
08 Apr 2002
TL;DR: This paper describes an approach in which dynamic adaptation is supported by the use of software architectural models to monitor an application and guide dynamic changes to it, and illustrates the application of this idea to pervasive computing systems.
Abstract: An important requirement for pervasive computing systems is the ability to adapt at runtime to handle varying resources, user mobility, changing user needs, and system faults. In this paper we describe an approach in which dynamic adaptation is supported by the use of software architectural models to monitor an application and guide dynamic changes to it. The use of externalized models permits one to make reconfiguration decisions based on a global perspective of the running system, apply analytic models to determine correct repair strategies, and gauge the effectiveness of repair through continuous system monitoring. We illustrate the application of this idea to pervasive computing systems, focusing on the need to adapt based on performance-related criteria and models.

113 citations

Proceedings ArticleDOI
17 Sep 2001
TL;DR: This work proposes a Dynamic Reconfiguration Service for CORBA that allows the reconfiguration of a running system with maximum transparency for both client and server side developers.
Abstract: Distributed systems with high availability requirements have to support some form of dynamic reconfiguration. This means that they must provide the ability to be maintained or upgraded without being taken off-line. Building a distributed system that allows dynamic reconfiguration is very intrusive to the overall design of the system, and generally requires special skills from both the client and server side application developers. There is an opportunity to provide support for dynamic reconfiguration at the object middleware level of distributed systems, and create a dynamic reconfiguration transparency to application developers. We propose a Dynamic Reconfiguration Service for CORBA that allows the reconfiguration of a running system with maximum transparency for both client and server side developers. We describe the architecture, a prototype implementation, and some preliminary test results.

113 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023784
20221,765
2021778
2020958
2019976
20181,060