Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis

• Other Authors: Bracale, Antonio (Editor), Sanjeevikumar, Padmanaban (Editor), Leonowicz, Zbigniew (Editor), Burgio, Alessandro (Editor), Sikorski, Tomasz (Editor), Janik, Przemyslaw (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
• Subjects: History of engineering & technology; Advanced Metering Infrastructure (AMI); Distributed Energy Resources (DER); Distribution Management System (DMS); Graph Reduction in Parallel (GRIP); Intelligent Electronic Device (IED); Intelligent Platform Management Interface (IPMI); Service Oriented Architecture (SOA); Ultra Large-Scale System (ULSS); photovoltaic systems; MPPT technique; partial shading; global MPP (GMPP); nature-inspired algorithms; congestion management; power flow; generator rescheduling; Flower Pollination Algorithm (FPA); Pumped Hydro Storage Unit (PHSU); ancillary services; grid; inverter; PV; reactive power; solar; Quasi-Z source inverter (QZSI); Y source inverter (YSI); energy storage system (ESS); hybrid renewable energy sources (HRES); demand; load; RBFNOEHO technique; common mode current; common mode voltage; modulation techniques; electromagnetic interference; mitigation; grid connected inverters; rotor angle; small signal stability; householder algorithm; power systems; electric vehicles; charging station; transformer; Energy PLAN; renewable energy; maximum demand (MD); solar PV; battery energy storage system (BESS); net energy metering (NEM); maximum demand reduction (MDRed) model; power quality; voltage variations; PV system; aggregation times; correlation analysis; harmonic analysis; wavelet transform; wavelet packet; measurement techniques; cloud services; trust management; secure computing; smart meter; LBSS; user-aware power regulatory model
• Online Access: DOAB: download the publication; DOAB: description of the publication

The work published in this book is related to the application of advanced signal processing in smart grids, including power quality, data management, stability and economic management in presence of renewable energy sources, energy storage systems, and electric vehicles. The distinct architecture of smart grids has prompted investigations into the use of advanced algorithms combined with signal processing methods to provide optimal results. The presented applications are focused on data management with cloud computing, power quality assessment, photovoltaic power plant control, and electrical vehicle charge stations, all supported by modern AI-based optimization methods.