Reprint

Power Electronics and Energy Management for Battery Storage Systems

Edited by
September 2022
174 pages
  • ISBN978-3-0365-5277-4 (Hardback)
  • ISBN978-3-0365-5278-1 (PDF)

This is a Reprint of the Special Issue Power Electronics and Energy Management for Battery Storage Systems that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary

The deployment of distributed renewable generation and e-mobility systems is creating a demand for improved dynamic performance, flexibility, and resilience in electrical grids. Various energy storages, such as stationary and electric vehicle batteries, together with power electronic interfaces, will play a key role in addressing these requests thanks to their enhanced functionality, fast response times, and configuration flexibility. For the large-scale implementation of this technology, the associated enabling developments are becoming of paramount importance. These include energy management algorithms; optimal sizing and coordinated control strategies of different storage technologies, including e-mobility storage; power electronic converters for interfacing renewables and battery systems, which allow for advanced interactions with the grid; and increase in round-trip efficiencies by means of advanced materials, components, and algorithms.

This Special Issue contains the developments that have been published b researchers in the areas of power electronics, energy management and battery storage. A range of potential solutions to the existing barriers is presented, aiming to make the most out of these emerging technologies.

Format
  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
Keywords
load shifting; energy storage; wind energy; green energy; self-consumption; cover factor; microgrids; buffer battery; distributed generation; simulation; Artificial neural network; battery management system; Kalman filter; lithium-ion battery; state of charge estimation; residential energy storage; battery energy storage systems; standards; grid interface converters; intellectual property; bidirectional converters; AC-DC power converters; DC-DC power converters; multilevel converters; partial power converters; ANPC converter; EV charging; multilevel converter; PWM methods; SiC MOSFETs; electric vehicles; machine learning; Kalman filter; thermal modelling; online prediction; electromagnetic impedance spectroscopy; computational cost; impedance network; Z-source; quasi-Z-source; voltage source inverter; voltage distortions; electric vehicles; stationary battery energy storage system; battery automated system; online state estimation; thermal modeling; first-order model; second-order model; Kalman filtering; high-gain non-inverting buck-boost converter; continuous conduction mode (CCM); discontinuous conduction mode (DCM)