Even order harmonic Series-L/Parallel-Tuned Class-E frequency multiplier

In this brief, we propose a new Class-E frequency multiplier based on the recently introduced Series-L/Parallel-Tuned Class-E amplifier. The proposed circuit produces even-order output harmonics. Unlike previously reported solutions the proposed circuit can operate under 50% duty ratio which minimizes the conduction losses. The circuit also offers the possibility for increased maximum operating frequency, reduced peak switch voltage, higher load resistance and inherent bond wire absorption; all potentially useful in monolithic microwave integrated circuit implementations. In addition, the circuit topology suggested large transistors with high output capacitances can be deployed. Theoretical design equations are given and the predictions made using these are shown to agree with harmonic balance circuit simulation results.

Open Source Telecommunications Framework for Time-Series Data from Smart Grid Sensors.

This paper presents a framework for a telecommunications interface which allows data from sensors embedded in Smart Grid applications to reliably archive data in an appropriate time-series database. The challenge in doing so is two-fold, firstly the various formats in which sensor data is represented, secondly the problems of telecoms reliability. A prototype of the authors' framework is detailed which showcases the main features of the framework in a case study featuring Phasor Measurement Units (PMU) as the application. Useful analysis of PMU data is achieved whenever data from multiple locations can be compared on a common time axis. The prototype developed highlights its reliability, extensibility and adoptability; features which are largely deferred from industry standards for data representation to proprietary database solutions. The open source framework presented provides link reliability for any type of Smart Grid sensor and is interoperable with existing proprietary database systems, and open database systems. The features of the authors' framework allow for researchers and developers to focus on the core of their real-time or historical analysis applications, rather than having to spend time interfacing with complex protocols.