Optimal planning issues of electric energy systems under uncertainty.- Optimal operation issues of electric energy systems under uncertainty.- Introduction to robust optimization (RO) method.- Introduction to information gap decision theory (IGDT) method.- Robust optimal planning and operation of electric energy systems.- Robs unit commitment.- Robust short-term scheduling.- Robust optimal power flow.- Robust transmission network expansion planning.- Robust strategic bidding of energy management systems.- Robust energy generation scheduling.- Robust economic dispatch problem in renewable-based hybrid energy systems.- Robust electricity market optimization.- Robust optimal design of hybrid energy systems.
Behnam Mohammadi-Ivatloo is an Associate Professor at the University of Tabriz, Tabriz, Iran. Before joining the University of Tabriz, he was a research associate at Institute for Sustainable Energy, Environment and Economy, University of Calgary, Calgary, Canada. He obtained M.Sc. and PhD degrees in electrical engineering from Sharif University of Technology, Tehran, Iran on 2008 and 2012, respectively. He is head of the Smart Energy Systems Lab. at University of Tabriz. The main areas of his interests are Renewable Energies, Micro Grid systems and smart grids.
Morteza Nazari-Heris is PhD candidate in Faculty of Electrical and Computer Engineering at the University of Tabriz, Tabriz, Iran. He obtained B.Sc. and M.Sc. degrees in electrical engineering from University of Tabriz, Tabriz, Iran on 2015 and 2017, respectively. He is a team member of the Smart Energy Systems Lab. at University of Tabriz. The main areas of his interests are micro grids, smart grids, integrated heat and power networks and energy storage technologies.
This book discusses the recent developments in robust optimization (RO) and information gap design theory (IGDT) methods and their application for the optimal planning and operation of electric energy systems. Chapters cover both theoretical background and applications to address common uncertainty factors such as load variation, power market price, and power generation of renewable energy sources. Case studies with real-world applications are included to help undergraduate and graduate students, researchers and engineers solve robust power and energy optimization problems and provide effective and promising solutions for the robust planning and operation of electric energy systems.