000 02885nam a22002657a 4500
001 sulbI000242
003 BD-SySUS
005 20160522122614.0
008 160522s2012 flua b 001 0 eng d
020 _a9781439893944 (hardback)
040 _aDLC
_cDLC
_dDLC
_dBD-SySUS
082 0 0 _a333.79320685
_223
_bELE
245 0 0 _aElectric power systems :
_badvanced forecasting techniques and optimal generation scheduling /
_c[edited by] Joao P.S. Catalao.
260 _aBoca Raton :
_bCRC Press,
_c2012.
300 _a(various pagings ) :
_bill. ;
_c24 cm.
504 _aIncludes bibliographical references and index.
520 _a"Preface A wide-ranging impression about the subjects discussed in this book is that the topics are pivotal for understanding and solving some of the problems flourishing in the second decade of the twenty-first century in the field of management of electric power generation systems. Noticeably, the chapters start with some of the last-decade knowledge to uncover lines of research on some of the present knowledge and, in due course, anticipate some of the admissible lines for future research in management of electric power generation systems. The scope of the book is well defined and of significant interest. Indeed, the development of new methodologies carrying away an improved forecasting and scheduling of electric power generation systems is crucial under the new competitive and environmentally constrained energy policy. The capability to cope with uncertainty and risk will benefit significantly generating companies. It is a fact that to avoid losing advantages of participating in the electricity market or negotiating bilateral contracts, a power producer should self-schedule its power system in anticipation. In recognition of this fact, hydro and thermal scheduling are relevant topics today. Already, wind power generation is playing an important role in some countries and will be even more important in the nearby future of energy supply in many countries. Thus, optimal coordination between hydro, thermal, and wind power is of utmost importance. Deterministic and stochastic modeling frameworks are allowing the development of the next generation of computational tools to help successful management of electric power generation systems. Research is underway to conquer the capability to cope with the present and the future of electric power generation systems as shown"--
650 0 _aElectric power production
_xForecasting.
_924311
650 0 _aElectric power systems
_xManagement.
_924312
650 7 _aTECHNOLOGY & ENGINEERING / Electronics / General.
_2bisacsh
_924196
650 7 _aTECHNOLOGY & ENGINEERING / Power Resources / Alternative & Renewable.
_2bisacsh
_924197
650 7 _aTECHNOLOGY & ENGINEERING / Power Resources / Electrical.
_2bisacsh
_924198
700 1 _aCatalao, Joao P. S.
_924313
942 _2ddc
_cBK
999 _c60541
_d60541