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The Next Generation of Electric Power Unit Commitment Models (Hardcover, 2001 ed.)
Loot Price: R6,674
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The Next Generation of Electric Power Unit Commitment Models (Hardcover, 2001 ed.)
Series: International Series in Operations Research & Management Science, 36
Expected to ship within 10 - 15 working days
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Over the years, the electric power industry has been using
optimization methods to help them solve the unit commitment
problem. The result has been savings of tens and perhaps hundreds
of millions of dollars in fuel costs. Things are changing, however.
Optimization technology is improving, and the industry is
undergoing radical restructuring. Consequently, the role of
commitment models is changing, and the value of the improved
solutions that better algorithms might yield is increasing. The
dual purpose of this book is to explore the technology and needs of
the next generation of computer models for aiding unit commitment
decisions. Because of the unit commitment problem's size and
complexity and because of the large economic benefits that could
result from its improved solution, considerable attention has been
devoted to algorithm development in the book. More systematic
procedures based on a variety of widely researched algorithms have
been proposed and tested. These techniques have included dynamic
programming, branch-and-bound mixed integer programming (MIP),
linear and network programming approaches, and Benders
decomposition methods, among others. Recently, metaheuristic
methods have been tested, such as genetic programming and simulated
annealing, along with expert systems and neural networks. Because
electric markets are changing rapidly, how UC models are solved and
what purposes they serve need reconsideration. Hence, the book
brings together people who understand the problem and people who
know what improvements in algorithms are really possible. The
two-fold result in The Next Generation of Electric Power Unit
Commitment Models is an assessment of industry needs and new
formulations and computational approaches that promise to make unit
commitment models more responsive to those needs.
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