A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

Loss-of-Main Monitoring and Detection for Distributed Generations Using Dynamic Principal Component Analysis

In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events; however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearly
auto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.

Electron-impact excitation of Li to high principal quantum numbers

The time-dependent close-coupling method is used to calculate electron-impact excitation cross sections for the Li(2s)--{\textgreater}Li(nl) and Li(2p)--{\textgreater}Li(nl) transitions at incident energies just above the ionization threshold. The implementation of the time-dependent close-coupling method on a nonuniform lattice allows the study of continuum-coupling effects in excitations to high principal quantum number, i.e., n{\textless}=10. Good agreement is found with R-matrix with pseudostates calculations, which also include continuum-coupling effects, for excitations to low principal quantum number, i.e., n{\textless}=4. Poor agreement is found with standard distorted-wave calculations for excitations to all principal quantum numbers, with differences still at the 50% level for n=10. We are able to give guidance as to the accuracy expected in the n3 extrapolation of nonperturbative close-coupling calculations of low n cross sections and rate coefficients.

Forest soil short term response to prescribed fire: an approach by Principal Components Analysis

In the current context of serious climate changes, where the increase of the frequency of some extreme events occurrence can enhance the rate of periods prone to high intensity forest fires, the National Forest Authority often implements, in several Portuguese forest areas, a regular set of measures in order to control the amount of fuel mass availability (PNDFCI, 2008). In the present work we’ll present a preliminary analysis concerning the assessment of the consequences given by the implementation of prescribed fire measures to control the amount of fuel mass in soil recovery, in particular in terms of its water retention capacity, its organic matter content, pH and content of iron. This work is included in a larger study (Meira-Castro, 2009(a); Meira-Castro, 2009(b)). According to the established praxis on the data collection, embodied in multidimensional matrices of n columns (variables in analysis) by p lines (sampled areas at different depths), and also considering the quantitative data nature present in this study, we’ve chosen a methodological approach that considers the multivariate statistical analysis, in particular, the Principal Component Analysis (PCA ) (Góis, 2004). The experiments were carried out in a soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, NW Portugal, who was able to maintain itself intact from prescribed burnings from four years and was submit to prescribed fire in March 2008. The soils samples were collected from five different plots at six different time periods. The methodological option that was adopted have allowed us to identify the most relevant relational structures inside the n variables, the p samples and in two sets at the same time (Garcia-Pereira, 1990). Consequently, and in addition to the traditional outputs produced from the PCA, we have analyzed the influence of both sampling depths and geomorphological environments in the behavior of all variables involved.

Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response.With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leça river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leça River.

Optimização da estrutura principal de um armazém metálico

Esta Tese consiste no cálculo estrutural de um pórtico pertencente a um suposto pavilhão instalado na zona Industrial de Matosinhos. Trata-se de um estudo comparativo entre dois tipos de pórticos metálicos que incluem o estudo das várias vertentes de permeabilidade. O objectivo é a optimização da quantidade de aço e betão que satisfaçam os requisitos segundo o REAP e Eurocódigo para a concepção deste pórtico. Posteriormente é feito uma análise crítica aos resultados obtidos.

Principal component analysis of the yield curve

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Pair trading: Clustering based on principal component analysis

This study focuses on the implementation of several pair trading strategies across three emerging markets, with the objective of comparing the results obtained from the different strategies and assessing if pair trading benefits from a more volatile environment. The results show that, indeed, there are higher potential profits arising from emerging markets. However, the higher excess return will be partially offset by higher transaction costs, which will be a determinant factor to the profitability of pair trading strategies. Also, a new clustering approach based on the Principal Component Analysis was tested as an alternative to the more standard clustering by Industry Groups. The new clustering approach delivers promising results, consistently reducing volatility to a greater extent than the Industry Group approach, with no significant harm to the excess returns.

Journal de botanique, appliquée à l'agriculture, à la pharmacie, à la médecine et aux arts / [rédacteur principal : N. A. Desvaux]

1814 (T4).

Journal de botanique, appliquée à l'agriculture, à la pharmacie, à la médecine et aux arts / [rédacteur principal : N. A. Desvaux]

1814 (T3).

Journal de botanique, appliquée à l'agriculture, à la pharmacie, à la médecine et aux arts / [rédacteur principal : N. A. Desvaux]

1813 (T1).

Journal de botanique, appliquée à l'agriculture, à la pharmacie, à la médecine et aux arts / [rédacteur principal : N. A. Desvaux]

1813 (T2).

Journal de botanique, appliquée à l'agriculture, à la pharmacie, à la médecine et aux arts / [rédacteur principal : N. A. Desvaux]

Variante(s) de titre : Journal de botanique

Arrêt du conseil d'Etat qui proge le délai fixé par arrêt du 29 septembre 1711, pour dix mois, pour le paiement tant du principal et intérêts des billets faits par les cautions d'Et. Rey, pour raison ou traité des trésoriers-payeurs des chancelleries, que pour le principal de ceux faits pour les autres traités

[Acte. 1712-03-22. Versailles]