Electric Power Unit Commitment Scheduling Using Dynamically Evolving Mixed Integer Program
Author: Massachusetts Institute of Technology. Energy Laboratory
Publisher:
Published: 1973
Total Pages: 148
ISBN-13:
DOWNLOAD EBOOKRead and Download eBook Full
Author: Massachusetts Institute of Technology. Energy Laboratory
Publisher:
Published: 1973
Total Pages: 148
ISBN-13:
DOWNLOAD EBOOKAuthor: Benjamin F. Hobbs
Publisher: Springer Science & Business Media
Published: 2006-04-11
Total Pages: 323
ISBN-13: 0306476630
DOWNLOAD EBOOKOver 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.
Author: Yuping Huang
Publisher: Springer
Published: 2017-01-13
Total Pages: 98
ISBN-13: 1493967681
DOWNLOAD EBOOKThis volume in the SpringerBriefs in Energy series offers a systematic review of unit commitment (UC) problems in electrical power generation. It updates texts written in the late 1990s and early 2000s by including the fundamentals of both UC and state-of-the-art modeling as well as solution algorithms and highlighting stochastic models and mixed-integer programming techniques. The UC problems are mostly formulated as mixed-integer linear programs, although there are many variants. A number of algorithms have been developed for, or applied to, UC problems, including dynamic programming, Lagrangian relaxation, general mixed-integer programming algorithms, and Benders decomposition. In addition the book discusses the recent trends in solving UC problems, especially stochastic programming models, and advanced techniques to handle large numbers of integer- decision variables due to scenario propagation
Author:
Publisher:
Published: 1974
Total Pages: 1138
ISBN-13:
DOWNLOAD EBOOKAuthor:
Publisher:
Published: 1974
Total Pages: 518
ISBN-13:
DOWNLOAD EBOOKAuthor:
Publisher:
Published: 1979
Total Pages: 376
ISBN-13:
DOWNLOAD EBOOKAuthor: United States. Division of Electric Energy Systems. Systems Management & Structuring
Publisher:
Published: 1980
Total Pages: 204
ISBN-13:
DOWNLOAD EBOOKAuthor: Holifield National Laboratory. Energy Information Center
Publisher:
Published: 1975
Total Pages: 344
ISBN-13:
DOWNLOAD EBOOKAuthor: RANN Document Center
Publisher:
Published: 1974
Total Pages: 84
ISBN-13:
DOWNLOAD EBOOK