Hydro-Québec

About: Hydro-Québec is a government organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Electric power system & Dielectric. The organization has 2596 authors who have published 4433 publications receiving 100878 citations.

Predicting river water temperatures using stochastic models : case study of the Moisie River (Québec, Canada)

Abstract: Successful applications of stochastic models for simulating and predicting daily stream temperature have been reported in the literature. These stochastic models have been generally tested on small rivers and have used only air temperature as an exogenous variable. This study investigates the stochastic modelling of daily mean stream water temperatures on the Moisie River, a relatively large unregulated river located in Quebec, Canada. The objective of the study is to compare different stochastic approaches previously used on small streams to relate mean daily water temperatures to air temperatures and streamflow indices. Various stochastic approaches are used to model the water temperature residuals, representing short-term variations, which were obtained by subtracting the seasonal components from water temperature time-series. The first three models, a multiple regression, a second-order autoregressive model, and a Box and Jenkins model, used only lagged air temperature residuals as exogenous variables. The root-mean-square error (RMSE) for these models varied between 0·53 and 1·70 °C and the second-order autoregressive model provided the best results. A statistical methodology using best subsets regression is proposed to model the combined effect of discharge and air temperature on stream temperatures. Various streamflow indices were considered as additional independent variables, and models with different number of variables were tested. The results indicated that the best model included relative change in flow as the most important streamflow index. The RMSE for this model was of the order of 0·51 °C, which shows a small improvement over the first three models that did not include streamflow indices. The ridge regression was applied to this model to alleviate the potential statistical inadequacies associated with multicollinearity. The amplitude and sign of the ridge regression coefficients seem to be more in agreement with prior expectations (e.g. positive correlation between water temperature residuals of different lags) and make more physical sense. Copyright © 2006 John Wiley & Sons, Ltd.

Power quality enhancement utilising single-phase unified power quality conditioner : digital signal processor-based experimental validation

Abstract: This study is based on a single-phase unified power quality conditioner (UPQC) to enhance power quality problem in single-phase systems. A simple control approach is implemented and validated through simulation as well as experimental studies. A laboratory prototype of UPQC is designed and developed using a digital signal processor. The performance of UPQC is validated experimentally under several operating conditions. It is found that the UPQC in single-phase system effectively compensates the important power quality issues, such as the load reactive power, load current harmonics, voltage harmonics, voltage sag, voltage swell and voltage flicker. Under distorted source voltage having total harmonics distortion (THD) of 14.1% with a non-linear load producing a distorted current (THD of 30.98%), the UPQC simultaneously compensates these harmonics resulting sinusoidal source current (THD of 3.77%) and load voltage (THD of 2.54%).

Investigation of the reaction mechanism of lithium sulfur batteries in different electrolyte systems by in situ Raman spectroscopy and in situ X-ray diffraction

Abstract: Lithium–sulfur batteries are of great interest owing to their high theoretical capacity of 1675 mA h g−1 and low cost. Their discharge mechanism is complicated and it is still a controversial issue. In the present work, in situ Raman spectroscopy is employed to investigate the poly-sulfide species in the sulfur cathode and in the electrolyte during the cycling of Li–S batteries. The aim is to understand the discharge mechanism and the influence of the electrolyte on the dissolution of sulfur and poly-sulfides. S8n− is identified as the main species in the high voltage plateau of discharge together with cycloocta S8, in the cell using 0.5 mol L−1 LiTFSI–PY13–FSI as the electrolyte. S42−, S22− and S2− are detected soon after the low voltage plateau is reached. A discharge mechanism in the PY13–FSI is proposed based on the identified species which provides important information for improving and designing cathodes. Electrolytes of 0.5 mol L−1 LiTFSI–PY13–FSI and 1 mol L−1 LiTFSI–DOL–DME are used in studying the dissolution of sulfur and poly-sulfides. The results demonstrate that the same poly-sulfide species are present in the two electrolytes. However, the rates of poly-sulfide formation and diffusion to the anode are slow in the ionic liquid compared to those in the ether-based electrolyte due to different ionic mobilities of various species in the two electrolytes. These differences are evidenced by the observation of poly-sulfide species in the DOL–DME from the very beginning of cell assembly even before starting the discharge whereas their appearances, in the ionic liquid, are delayed and only found at the end of the high voltage plateau. Notably, the soluble elemental sulfur is clearly observed in the ionic liquid electrolyte during the first discharge in the high voltage region, which is very different from the DOL–DME system where the elemental sulfur is quickly reduced to poly-sulfides due to self-discharge reactions. In addition, the elemental sulfur is also detected near the lithium anode in DOL–DME at the end of charge, for the first time to our knowledge, which suggests that the degradation of lithium metal is caused by the multiple reactions of the lithium metal surface with soluble poly-sulfides and/or elemental sulfur.

PD pattern recognition with neural networks using the multilayer perceptron technique

Abstract: The partial discharge (PD) pattern recognition capability of a neural network, employing the multilayer perceptron technique with data input based on five discharge pulse form parameters, is examined. Simple discharge sources, consisting of artificially created cylindrical cavities with metallic and dielectric electrodes, are employed. The PD pattern discrimination capability is tested using cavities of equal depth but with different electrodes, and cavities of varying depths but with similar electrodes. Preliminary test results are positive. >