000			03152cam a22003374a 4500
001			17126960
003			Nust- CAS-E
005			20180118181355.0
008			120119s2012 flua b 001 0 eng
010			_a 2011050407
020			_a9781439893944
040			_aDLC _cDLC _dDLC
042			_apcc
050	0	0	_aTK1001 _b.E424 2012
082	0	0	_a333.79320685 _223 _bELE 2012
084			_aTEC008000 _aTEC031010 _aTEC031020 _2bisacsh
245	0	0	_aElectric power systems : _badvanced forecasting techniques and optimal generation scheduling / _c[edited by] Jo�ao P.S. Catal�ao.
260			_aBoca Raton : _bCRC Press, _c2012.
300			_a1 v. (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.
650		0	_aElectric power systems _xManagement.
650		7	_aTECHNOLOGY & ENGINEERING / Electronics / General. _2bisacsh
650		7	_aTECHNOLOGY & ENGINEERING / Power Resources / Alternative & Renewable. _2bisacsh
650		7	_aTECHNOLOGY & ENGINEERING / Power Resources / Electrical. _2bisacsh
700	1		_aCatal�ao, Jo�ao P. S.
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c355261 _d355261