LEADER 04674nam 2201069z- 450 001 9910404080603321 005 20231214132853.0 010 $a3-03928-111-9 035 $a(CKB)4100000011302332 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/40816 035 $a(EXLCZ)994100000011302332 100 $a20202102d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAnalysis for Power Quality Monitoring 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 electronic resource (210 p.) 311 $a3-03928-110-0 330 $aWe 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. 610 $amodulation 610 $aFPGA 610 $aflicker 610 $aDC power quality indices 610 $alimited resources hardware 610 $alow cost monitor 610 $adynamic phasor estimation 610 $aharmonics 610 $aRMS voltage estimation 610 $aislanding operation 610 $aembedded system 610 $asignal waveform compression 610 $abig data 610 $adigital signal processing 610 $adata scalability 610 $adata compression 610 $awind-grid distribution 610 $avoltage fluctuations 610 $asmart grid (SG) applications 610 $apower event detection 610 $amodelling 610 $avoltage ripple 610 $apower quality monitoring 610 $ahigher-order statistics (HOS) 610 $apower distribution systems 610 $apower quality disturbances 610 $areconfigurable computing 610 $aoperation analysis 610 $asensor node 610 $apower quality (PQ) 610 $adistribution networks 610 $awireless sensor network 610 $areliability 610 $apower system measurements 610 $aembedded microcontroller 610 $aphasor measurement units 610 $aIoT 610 $asoft computing 610 $asmart grids 610 $apower quality monitor 610 $ainduction machines 610 $asensors and instruments for PQ 610 $aKalman filters 610 $alow-voltage DC networks 610 $aconvolution neural network 610 $aspectral kurtosis 610 $amunicipal distribution network 610 $astatistical signal processing 610 $adetection 610 $apower quality disturbance 610 $asmart grid 610 $aenergizing warning 610 $adense-mesh topology 610 $alow computational cost 610 $afourth-order statistics 610 $aPQ indices and thresholds 610 $amachine learning 610 $avoltage sags 610 $apower quality 610 $acomputational solutions for advanced metering infrastructure (AMI) 610 $aconstant amplitude trend 610 $aphasor measurement 610 $aimproved principal component analysis 610 $along-term 700 $aGonzález de la Rosa$b Juan-José$4auth$01267785 702 $aDonsión$b Manuel Pérez$4auth 906 $aBOOK 912 $a9910404080603321 996 $aAnalysis for Power Quality Monitoring$93035779 997 $aUNINA