Kusiak Co-edits Textbook on Wind Power Systems
Andrew Kusiak, professor of mechanical and industrial engineering, is co-editor of a new textbook, titled "Green Energy and Technology: Wind Power Systems-Applications of Computational Intelligence."
The book, published by Springer-Verlag, includes state-of-the-art studies on applications of computational intelligence, including evolutionary computation, neural networks, fuzzy logic, hybrid algorithms, multi-agent reinforcement learning, and several other approaches, to wind power systems. Various research areas focus on wind turbine control, wind turbine diagnosis, wind farm design, economic dispatch, conductor sizing, realiabilith analysis, power loss minimization, and frequency regulation.
Kusiak co-edited the textbook with Dr. Lingfeng Wang, Department of Electrical Engineering and Computer Science, University of Toledo, and Dr. Chanan Singh, Electrical and Computer Engineering Department, Texas A&M University.
Kusiak's research interests are in data mining, evolutionary computation, optimization of energy systems, mass customization, healthcare systems, medical technology, reengineering, engineering design, manufacturing, process modeling. He oversees the Intelligent Systems Laboratory, which provides facilities for research in computational intelligence leading to applications in electric energy utilities, manufacturing industry, service organizations, and healthcare.