Transmission Loss Allocation Through Complex Power Flow Tracing

This paper presents a new method for transmission loss allocation. The method is based on tracing the complex power flow through the network and determining the share of each load on the flow and losses through each line. Transmission losses are taken into consideration during power flow tracing. Unbundling line losses is carried out using an equation, which has a physical basis, and considers the coupling between active and reactive power flows as well as the cross effects of active and reactive power on active and reactive losses. A tracing algorithm which can be considered direct to a good extent, as there is no need for exhaustive search to determine the flow paths as these are determined in a systematic way during the course of tracing. Results of application of the proposed method are also presented.

Transmission loss allocation in a deregulated electrical energy market

This paper presents a new method for transmission loss allocation in a deregulated electrical power market. The proposed method is based on physical flow through transmission lines. The contributions of individual loads to the line flows are used as basis for allocating transmission losses to different loads. With minimum assumptions, that sound to be reasonable and cannot be rejected, a novel loss allocation formula is derived. The assumptions made are: a number of currents sharing a transmission line distribute themselves over the cross section in the same manner; that distribution causes the minimum possible power loss. Application of the proposed method is straightforward. It requires only a solved power flow and any simple algorithm for power flow tracing. Both active and reactive powers are considered in the loss allocation procedure. Results of application show the accuracy of the proposed method compared with the commonly used procedures.

The alternative sigma factor sigma B of Staphylococcus aureus modulates virulence in experimental central venous catheter-related infections.

The impact of the alternative sigma factor sigma B (SigB) on pathogenesis of Staphylococcus aureus is not conclusively clarified. In this study, a central venous catheter (CVC) related model of multiorgan infection was used to investigate the role of SigB for the pathogenesis of S. aureus infections and biofilm formation in vivo. Analysis of two SigB-positive wild-type strains and their isogenic mutants revealed uniformly that the wild-type was significantly more virulent than the SigB-deficient mutant. The observed difference in virulence was apparently not linked to the capability of the strains to form biofilms in vivo since wild-type and mutant strains were able to produce biofilm layers inside of the catheter. The data strongly indicate that the alternative sigma factor SigB plays a role in CVC-associated infections caused by S. aureus.

The structure of the Statistics Anxiety Rating Scale: A confirmatory factor analysis using UK psychology students

This study aimed to examine the structure of the statistics anxiety rating scale. Responses from 650 undergraduate psychology students throughout the UK were collected through an on-line study. Based on previous research three different models were specified and estimated using confirmatory factor analysis. Fit indices were used to determine if the model fitted the data and a likelihood ratio difference test was used to determine the best fitting model. The original six factor model was the best explanation of the data. All six subscales were intercorrelated and internally consistent. It was concluded that the statistics anxiety rating scale was found to measure the six subscales it was designed to assess in a UK population.