Analysis of Load Impact on Small-signal Stability based on Load Active Power Sensitivity

While load flow conditions vary with different loads, the small-signal stability of the entire system is closely related with to the locations, capacities and models of loads. In this paper, load impacts with different capacities and models on the small-signal stability are analysed. In the real large-scale power system case, the load sensitivity which denotes the sensitivity of the eigenvalue with respect to the load active power is introduced and applied to rank the loads. The loads with high sensitivity are also considered.

Sensitivity characteristics of inverse Class-E power amplifier

In this paper, an analysis is performed in order to determine the effects that variations in circuit component values, frequency, and duty cycle have on the performance of the newly introduced inverse Class-E amplifier. Analysis of the inverse Class-E amplifier under the generalized condition of arbitrary duty cycle is performed and it is shown that the inverse Class-E amplifier is reasonably tolerant to circuit parameter variations. When compared to the conventional Class-E amplifier the inverse Class-E amplifier offers the potential for high efficiency at increased output power as well as higher peak output power levels than are available with a conventional Class-E amplifier. Further the inverse Class-E amplifier provides more flexibility for deployment with a pulsewidth modulator as the means of producing full-carrier amplitude modulation (AM) due to its ability to operate to high AM modulation indices.

Assessment Method for a Power Analysis to Identify Differentially Expressed Pathways

Gene expression data can provide a very rich source of information for elucidating the biological function on the pathway level if the experimental design considers the needs of the statistical analysis methods. The purpose of this paper is to provide a comparative analysis of statistical methods for detecting the differentially expression of pathways (DEP). In contrast to many other studies conducted so far, we use three novel simulation types, producing a more realistic correlation structure than previous simulation methods. This includes also the generation of surrogate data from two large-scale microarray experiments from prostate cancer and ALL. As a result from our comprehensive analysis of 41,004 parameter configurations, we find that each method should only be applied if certain conditions of the data from a pathway are met. Further, we provide method-specific estimates for the optimal sample size for microarray experiments aiming to identify DEP in order to avoid an underpowered design. Our study highlights the sensitivity of the studied methods on the parameters of the system. © 2012 Tripahti and Emmert-Streib.

Distribution Network Voltage Support Using Sensitivity-based Dispatch of Distributed Generation

This paper is concerned with the voltage and reactive power issues surrounding the connection of Distributed Generation (DG) on the low-voltage (LV) distribution network. The presented system-wide voltage control algorithm consists of three stages. Firstly available reactive power reserves are utilized. Then, if required, DG active power output is curtailed. Finally, curtailment of non-critical site demand is considered. The control methodology is tested on a variant of the 13-bus IEEE Node Radial Distribution Test Feeder. The presented control algorithm demonstrated that the distribution system operator (DSO) can maintain voltage levels within a desired statutory range by dispatching reactive power from DG or network devices. The practical application of the control strategy is discussed.