Recent updates

Testing Operation and Coordination of DC Solid State Circuit Breakers

Authors:  James Langston; Andrew Rockhill; Karl Schoder; Michael Sloderbeck; Michael Steurer Extended Abstract: An approach for testing the operation and coordination of medium-voltage dc solid state circuit breakers (SSCB) for shipboard power systems is described. For the considered application, the rate of rise of current during a short-circuit is limited primarily by a small cable inductance.  This high rate of rise, coupled with the need to interrupt the current prior to exceeding the limits of the power electronic switches in the SSCBs, necessitates a coordinated protection scheme which can isolate the fault within a matter of microseconds. Challenges in such tests include the high-voltage, high current, high rates of change of current, and the interconnection of devices within a system. Testing of the SSCBs in a system context presents a challenge, as the MVDC system to which these are to be applied has been realized neither in an actual shipboard implementation, nor in a land-based test site. In order to cope with these challenges and verify the operation of the SSCBs within a system context, a combination of tests and analyses are employed, including off-line simulation, controller hardware-in-the-loop simulation, hardware testing of a single SSCB, and coordination testing with multiple ...
Read More

Distributed k-means algorithm for sensor networks based on multi-agent consensus theory

Authors: Qiuhong Liu ; Weiming Fu ; Jiahu Qin ; Wei Xing Zheng ; Huijun Gao Abstract: This paper is concerned with developing a distributed k-means algorithm for the wireless sensor networks (WSN) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multi-agent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is firstly proposed to find the initial centroids before executing the distributed k-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that achieved by the centralized clustering algorithms. 2017 Best conference paper award for IEEE ICIT 2016 This paper is presented at the 2016 IEEE International Conference on Industrial Technology (ICIT), check full paper at: ...
Read More