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.

Detection and Classification of Power Quality Disturbances Using Sparse Signal Decomposition on Hybrid Dictionaries

Abstract: Several methods have been proposed for detection and classification of power quality (PQ) disturbances using wavelet, Hilbert transform, Gabor transform, Gabor-Wigner transform, S transform, and Hilbert-Haung transform. This paper presents a new method for detection and classification of single and combined PQ disturbances using a sparse signal decomposition (SSD) on overcomplete hybrid dictionary (OHD) matrix. The method first decomposes a PQ signal into detail and approximation signals using the proposed SSD technique with an OHD matrix containing impulse and sinusoidal elementary waveforms. The output detail signal adequately captures morphological features of transients (impulsive and oscillatory) and waveform distortions (harmonics and notching). Whereas the approximation signal contains PQ features of fundamental, flicker, dc-offset, and short- and long-duration variations (sags, swells, and interruptions). Thus, the required PQ features are extracted from the detail and approximation signals. Then, a hierarchical decision-tree algorithm is used for classification of single and combined PQ disturbances. The proposed method is tested using both synthetic and microgrid simulated PQ disturbances. Results demonstrate the accuracy and robustness of the method in detection and classification of single and combined PQ disturbances under noiseless and noisy conditions. The method can be easily expanded for compressed sensing based PQ monitoring networks.

A Fuzzy Rule-Based Approach for Islanding Detection in Distributed Generation

Abstract: The proposed method develops a fuzzy rule-based classifier that was tested using features for islanding detection in distributed generation. In the developed technique, the initial classification boundaries are found out by using the decision tree (DT). From the DT classification boundaries, the fuzzy membership functions (MFs) are developed and the corresponding rule base is formulated for islanding detection. But some of the fuzzy MFs are merged based upon similarity the measure for reducing the fuzzy MFs and simplifying the fuzzy rule base to make it more transparent. The developed fuzzy rule-based classifier is tested using features with noise up to a signal-to-noise ratio of 20 dB and provides classification results without misdetection, which shows the robustness of the proposed approach for islanding detection for distributed generations in the distribution network.

Mechanism of the Fe3+ Reduction at Low Temperature for LiFePO4 Synthesis from a Polymeric Additive

Abstract: Comparison is made between the use of either a carbon powder or a polymer additive to the precursors in the synthesis of LiFePO4 from the Fe(III) compound FePO4(H2O)2 and Li2CO3. The evolution of the structural properties and phase purity with temperature and time have been monitored at all length scales by X-ray diffraction, Fourier transformed infrared spectroscopy, and magnetic susceptibility. The reactor temperature was decreased to 300 °C to investigate the early stages of the reaction. Formation of crystalline LiFePO4 begins in the range 300−400 °C only if the polymer is used as the carbonaceous additive. This LiFePO4 formation is made possible by the reduction of Fe(III) species by gases such as H2 or gaseous hydrocarbons evolved during the calcination of the polymer. Moreover, decomposition of the polymer results in a carbonaceous deposit on the surface of the LiFePO4 particles. An Li3Fe2(PO4)3 impurity found after sintering at 400 °C for 4 h was greatly reduced after sintering at 400 °C for 24 h,...