Frequency control is a vital component of a secure and robust power grid and it ought to be closely monitored. Frequency control consists of two main components; primary and secondary control and their contributions are usually aggregated in the active power generation data of a plant, which is acquired via Supervisory Control And Data Acquisition. In many cases, such as in Turkey, they are demanded to be evaluated separately due to different impacts on power system or different financial policies. However, this is not usually a straightforward process since primary and secondary response cannot be obtained distinctly. In this work, Extraction of Primary and Secondary Control (EPSCon) algorithm is introduced to extract primary and secondary response over active power generation data. Based on time and frequency domain characteristics of primary and secondary response, EPSCon is developed on a Expectation-Maximization type recursive scheme employing Generalized Cross Correlation and ℓ1 Trend Filtering techniques. Favorably, EPSCon uses a simple plant model built upon basic governor and plant load controller technical characteristics as an initial estimate of primary and secondary response. © 2015 Elsevier Ltd. All rights reserved

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In this work we consider the problem of measurement matrix design for compressed 3-D Direction of Arrival (DoA) estimation using a sensor array with analog combiner. Since generic measurement matrix designs often do not yield optimal estimation performance, we propose a novel design technique based on the minimization of the Crameŕ-Rao Lower Bound (CRLB). We develop specific approaches for adaptive measurement design for two applications: detection of the newly appearing targets and tracking of the previously detected targets. Numerical results suggest that the developed designs allow to provide the near optimal performance in terms of the CRLB.

Cavitation phenomenon has attracted much attention in engineering applications so the industry has provided considerable funding during recent years. Despite the simplicity and rather low price of small devices generating cavitation bubbles, the physics behind the creation and collapse of these bubble is still not well understood particularly in micro/nano scale. The assessment of size effects is vital for the design and development of new generation microfluidic devices involving phase change. Additionally, as the length scale decreases, surface nuclei dominate and dictate cavitation events. The modifications in the microchip geometry and enhancement in the micro device performance in applications involving cavitation will lead to increased cavitation bubbles number, reduced noise, improved bubbles collapse and increased energy sustainability. This study aims to investigate the creation of cavitation bubbles and classify the cavitating flow patterns in a novel roughened microchannel configuration. Cavitating flows are characterized in a transparent microchannel configuration in order to achieve a comprehensive understanding of cavitation inception and collapse in micro scale, which are crucial in the development of new-generation energy harvesting systems. In this device, a restrictive element and a big channel downstream of the restrictive element are mainly considered. The microchip consists of two main wafers, namely silicon and glass, which are anodically bonded together to withstand high pressures. The flow rate and discharge are evaluated at the outlet of the channels to characterize the chocking flow conditions in micro scale. The flow characteristics are determined to recognize differences in flow physics between smooth and roughened micro channels. Moreover, cavitation number, which is a major parameter for flow patterns, is considered in order to have valuable insights to the inception, development and collapse of the cavitation phenomenon in micro scale. Furthermore, the surface characteristics are also considered in detail in the microchip, and the effect of surface roughness on cavitating flows is investigated.