Advanced Modeling and Research in Hybrid Microgrid Control and Optimization

Edited by
November 2021
264 pages
  • ISBN978-3-0365-1886-2 (Hardback)
  • ISBN978-3-0365-1885-5 (PDF)

This book is a reprint of the Special Issue Advanced Modeling and Research in Hybrid Microgrid Control and Optimization that was published in

Computer Science & Mathematics
Physical Sciences
Public Health & Healthcare

This book presents the latest solutions in fuel cell (FC) and renewable energy implementation in mobile and stationary applications. The implementation of advanced energy management and optimization strategies are detailed for fuel cell and renewable microgrids, and for the multi-FC stack architecture of FC/electric vehicles to enhance the reliability of these systems and to reduce the costs related to energy production and maintenance. Cyber-security methods based on blockchain technology to increase the resilience of FC renewable hybrid microgrids are also presented. Therefore, this book is for all readers interested in these challenging directions of research.

  • Hardback
© 2022 by the authors; CC BY-NC-ND license
mobile charging station; electric vehicle; operational mode; location-allocation problem; battery; capacitor; differential flatness; double-layer capacitor; electric vehicle; energy management; interleaved converter; nonlinear control; second order equation; supercapacitor; multi-stack; Polymer Electrolyte Membrane Fuel Cell (PEMFC); energy management; power electronics; stability analysis; microgrid; LQR-PI control; grid-tied mode; current imbalance; power quality; genetic algorithms; renewable energy; consumer planning; real-time strategy; consumption monitoring; energy storage systems; renewable energy sources; genetic algorithms; dynamic programming; cascaded multilevel inverter; photovoltaic; leakage current; IoT security; Internet of Vehicles; IoV; connected car; Blockchain Governance Game; mixed game; stochastic model; fluctuation theory; 51 percent attack; double feed induction generator; grid frequency and amplitude support; smart grid; wind technology (WT); load frequency control; optimization issue; moth flame optimizer (MFO); Harris hawks optimizer (HHO); fuel economy; load-following; switching strategy; real-time optimization; fuel cell vehicle; fuel cell system; load frequency control; automatic generation control; controllers; optimization techniques; multisource power system; interconnected power system; hybrid gravitational with fire fly algorithm; gravitational search algorithm; firefly algorithm