Control reconfiguration

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

Adapted ant colony optimization for efficient reconfiguration of balanced and unbalanced distribution systems for loss minimization

Abstract: This paper presents an efficient method for the reconfiguration of radial distribution systems for minimization of real power loss using adapted ant colony optimization. The conventional ant colony optimization is adapted by the graph theory to always create feasible radial topologies during the whole evolutionary process. This avoids tedious mesh check and hence reduces the computational burden. The initial population is created randomly and a heuristic spark is introduced to enhance the pace of the search process. The effectiveness of the proposed method is demonstrated on balanced and unbalanced test distribution systems. The simulation results show that the proposed method is efficient and promising for reconfiguration problem of radial distribution systems.

Real-Time Implementation of Intelligent Reconfiguration Algorithm for Microgrid

Abstract: Microgrids with renewable distributed generation and energy storage offer sustainable energy solutions. To maintain the availability of energy to the connected loads, considering priority and to interrupt the smallest portion of the microgrid under any abnormal conditions, reconfiguration is critical to restore service to a section or to meet some operational requirements of dropping minimum loads. Reconfiguration is the process of modifying the microgrid's topological structure by changing the status (open/close) of the circuit breakers or switches. In this work, constraints are the power balance equation and power generation limits, and we assumed that the system is designed with the entire planning and operational control criterion to meet the voltage violation and line overloading constraints. This paper offers novel real-time implementation of intelligent algorithm for microgrid reconfiguration. Intelligent algorithm is based on the genetic algorithms and has been tested on two test systems including shipboard power system and modified Consortium for Electric Reliability Technology Solutions (CERTS) microgrid. Real-time test bed utilizes real-time digital simulator and commercial real-time controllers from Schweitzer Engineering Lab. Reconfiguration algorithm has been implemented in the real time using real-time test bed, e.g., microgrid system, and satisfactory results were obtained.

Sequencing Run-Time Reconfigured Hardware with Software

Abstract: Run-Time Reconfigured systems offer additional hardware resources to systems based on reconfigurable FPGAs. These systems, however, are often difficult to build and must tolerate substantial reconfiguration times. A processor based architecture has been built to simplify the development of these systems by providing programmable control of hardware sequencing while retaining the performance of hardware. Configuration overhead of this system is reduced by "caching" hardware on the reconfigurable resource. An image processing application was developed on this system to demonstrate both the performance improvements of custom hardware and the ease of software development.

MiNT-m: an autonomous mobile wireless experimentation platform

Abstract: Limited fidelity of software-based wireless network simulations has prompted many researchers to build testbeds for developing and evaluating their wireless protocols and mobile applications. Since most testbeds are tailored to the needs of specific research projects, they cannot be easily reused for other research projects that may have different requirements on physical topology, radio channel characteristics or mobility pattern. In this paper, we describe the design, implementation and evaluation of MiNT-m, an experimentation platform devised specifically to support arbitrary experiments for mobile multi-hop wireless network protocols. In addition to inheriting the miniaturization feature from its predecessor MiNT [9], MiNT-m enables flexible testbed reconfiguration on an experiment-by-experiment basis by putting each testbed node on a centrally controlled untethered mobile robot. To support mobility and reconfiguration of testbed nodes, MiNT-m includes a scalable mobile robot navigation control subsystem, which in turn consists of a vision-based robot positioning module and a collision avoidance-based trajectory planning module. Further, MiNT-m provides a comprehensive network/experiment management subsystem that affords a user full interactive control over the testbed as well as real-time visualization of the testbed activities. Finally, because MiNT-m is designed to be a shared research infrastructure that supports 24x7 operation, it incorporates a novel automatic battery recharging capability that enables testbed robots to operate without human intervention for weeks.

Improving functional density through run-time constant propagation

Abstract: Circuit specialization techniques such as constant propagation are commonly used to reduce both the hardware resources and cycle time of digital circuits. When reconfigurable FPGAs are used, these advantages can be extended by dynamically specializing circuits using run-time reconfiguration (RTR). For systems exploiting constant propagation, hardware resources can be reduced by folding constants within the circuit and dynamically changing the constants using circuit reconfiguration. To measure the benefits of circuit specialization, a functional density metric is presented. This metric allows the analysis of both static and run-time reconfigured circuits by including the cost of circuit reconfiguration. This metric will be used to justify runtime constant propagation as well as analyze the effects of reconfiguration time on run-time reconfigured systems.