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Autore: | González de la Rosa Juan-José |
Titolo: | Analysis for Power Quality Monitoring |
Pubblicazione: | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
Descrizione fisica: | 1 electronic resource (210 p.) |
Soggetto non controllato: | modulation |
FPGA | |
flicker | |
DC power quality indices | |
limited resources hardware | |
low cost monitor | |
dynamic phasor estimation | |
harmonics | |
RMS voltage estimation | |
islanding operation | |
embedded system | |
signal waveform compression | |
big data | |
digital signal processing | |
data scalability | |
data compression | |
wind-grid distribution | |
voltage fluctuations | |
smart grid (SG) applications | |
power event detection | |
modelling | |
voltage ripple | |
power quality monitoring | |
higher-order statistics (HOS) | |
power distribution systems | |
power quality disturbances | |
reconfigurable computing | |
operation analysis | |
sensor node | |
power quality (PQ) | |
distribution networks | |
wireless sensor network | |
reliability | |
power system measurements | |
embedded microcontroller | |
phasor measurement units | |
IoT | |
soft computing | |
smart grids | |
power quality monitor | |
induction machines | |
sensors and instruments for PQ | |
Kalman filters | |
low-voltage DC networks | |
convolution neural network | |
spectral kurtosis | |
municipal distribution network | |
statistical signal processing | |
detection | |
power quality disturbance | |
smart grid | |
energizing warning | |
dense-mesh topology | |
low computational cost | |
fourth-order statistics | |
PQ indices and thresholds | |
machine learning | |
voltage sags | |
power quality | |
computational solutions for advanced metering infrastructure (AMI) | |
constant amplitude trend | |
phasor measurement | |
improved principal component analysis | |
long-term | |
Persona (resp. second.): | DonsiónManuel Pérez |
Sommario/riassunto: | We are immersed in the so-called digital energy network, continuously introducing new technological advances for a better way of life. Numerous emerging words are in the spotlight, namely: Internet of Things (IoT), Big Data, Smart Cities, Smart Grid, Industry 4.0, etc. To achieve this formidable goal, systems should work more efficiently, and this fact inevitably leads to power quality (PQ) assurance. Apart from its economic losses, a bad PQ implies serious risks for machines, and consequently for people. Many researchers are endeavoring to develop new analysis techniques, instruments, measurement methods, and new indices and norms that match and fulfil the requirements regarding the current operation of the electrical network. This book offers a compilation of the some recent advances in this field. The chapters range from computing issues to technological implementations, going through event detection strategies and new indices and measurement methods that contribute significantly to the advancement of PQ analysis. Experiments have been developed within the frames of research units and projects, and deal with real data from industry and public buildings. Human beings have an unavoidable commitment with sustainability, which implies adapting PQ monitoring techniques to our dynamic world, defining a digital and smart concept of quality for electricity. |
Titolo autorizzato: | Analysis for Power Quality Monitoring |
ISBN: | 3-03928-111-9 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910404080603321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |