Advance-commitment Books

This is an excellent book that I received as a gift. I purchased a copy for my brother to motivate and inspire him.

This book really inspired me. I couldn't put it down and dog-eared almost every page.

I really enjoyed this book. If you like to use motivational statements, this book is packed full of them. The contents are useful for managers to use with staff, teachers with students and in your own personal life.

useness,new,needed by dev-ing country! If Free,Best

The unit commitment problem is stated using math formulas which contain 28 symbols. To understand the formulas, it is necessary to memorize the definition of each symbol. If you have the patience, you can translate the formulas into something coherent in about 3 hours. The result is rather straight forward and forms a basis for understanding which, theoretically, is the purpose for which the book was written.

For those who are already familiar with the symbols, see the review by the reader from Yonkers.

Excellent book. Definite keeper for anyone working in the market. Appreciate the source code and data which backs up the paper. For those who believe in cost based world, get this book and compare your results

This text appears to have been a technical report or a PhD thesis that was modified to become a book. The authors did their best to stretch the page count by providing basic information that is generally known by most senior-level students in electrical engineering or operations research. Even after this exercise, the "real" page count is 108. The remainder of the book was made possible by copying several standard formulas from a statistics book, by downloading and plotting some of PJM's data (isn't the Internet great?), and by providing an amateurish source code for some of the material suggested in the book for the single-unit case.

The book begins by describing the unit commitment problem, referencing a total of 9 journal articles (Page 9), but skipping most of the important references in this area. It is strange to discuss unit commitment (in a book) without mentioning the original work of Muckstadt and Koenig (1977), Merlin and Sandrin (1983), or that of Zhuang and Galiana (1988), to name a few. The authors quickly discount all previous work as being inadequate as it does not handle many of the important elements of a system (leading you to believe that they are going to discuss these issues), such as network constraints or losses. I suggest that they refer to "The Generalized Unit Commitment Problem" by Baldick, IEEE Transactions on Power Systems, 1995, for a discussion on this subject. I also strongly recommend that Mr. Allen and Ms. Ilic obtain a copy of (the outdated) "Unit Commitment Literature Synopsis" by Sheble and Fahd, IEEE Transactions on Power Systems, 1994. It may serve as a starter on this subject. The most impressive aspect of this book is its depth, or lack there of. The authors manage to provide their deep knowledge of the unit commitment problem and its solution techniques in less than 5 pages.

Chapter 3 describes the unit commitment in a deregulated environment in the most simplistic fashion possible (indicating the authors' lack of any true experience in this business) resulting in six pages of basic material. In chapter 4, the reader is presented with a pathetic review of dynamic programming. Chapter 5 is even more interesting. The authors assume a known price process in the market and optimize each individual generating unit based on these prices. They discuss (in less than 7 pages) the use of dynamic programming to solve the unit commitment (in reality a single generator) with and without generation limits using normal and lognormal price distributions. For those of us teaching dynamic programming to senior or master level students, the three models could serve as a homework assignment. If you are a "quant" on the trading floor, you may want to derive these formulas during your lunch hour.

Chapter 6 is entitled "Price Process of Electricity". Thanks to the statisticians of this world, the reader is bombarded with endless tests and distributions describing electricity prices. The authors skillfully demonstrate their ability to use Matlab to draw a large number of graphs.

I must admit that I stopped reading when I reached Chapter 7 "Computational Complexity of the Unit Commitment". The authors say that the dynamic programming is widely used for solving stochastic optimization problems "however, it also has the disadvantage of non-polynomial (NP) growth of operation count with respect to problem size." They refer the reader to the book by Bertsekas on Dynamic Programming and Optimal Control. The authors abruptly shy away from discussing this subject. Given the depth of the book, I would have expected a proof showing that the problem being discussed (the unit commitment) is NP. It is not sufficient to say that their formulation suffers from exponential growth. If the matter is so simple, I have several problems that I modeled as dynamic programs and would like to claim that they are NP (including a couple of linear programs that I solved using dynamic programming as I was lazy to call the LP solver).

In summary, the book is a waste of time and money. It is a sad demonstration of how tenure and graduation pressure can lead people to publish garbage. If you need to learn about this subject, I suggest searching the web for articles related to deregulation. Then, you can buy Bertsekas's book (or refer to your notes from college), use your good old Schaum's Series on statistics, and derive the results that truly fit your problem.