000 03732nam a22004935i 4500
001 978-0-387-23048-1
003 DE-He213
005 20250710083927.0
007 cr nn 008mamaa
008 100301s2005 xxu| s |||| 0|eng d
020 _a9780387230481
_a99780387230481
024 7 _a10.1007/b100484
_2doi
082 0 4 _a333.79
_223
100 1 _aWeber, Christoph.
_eauthor.
245 1 0 _aUncertainty in the Electric Power Industry
_h[recurso electrónico] :
_bMethods and Models for Decision Support /
_cby Christoph Weber.
264 1 _aNew York, NY :
_bSpringer New York,
_c2005.
300 _aXXIII, 294 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v77
505 0 _aDeregulation and Markets in the Electricity Industry -- Decision Making and Uncertainties in the Electricity Industry -- Modelling Electricity Prices -- Modeling Competition in the Electricity Industry -- Optimizing Generation and Trading Portfolios -- Risk Management and Risk Controlling -- Technology Assessment -- Investment Decisions -- Final Remarks.
520 _aAround the world, liberalization and privatization in the electricity industry have lead to increased competition among utilities. At the same time, utilities are now exposed more than ever to risk and uncertainties, which they cannot pass on to their customers through price increases as in a regulated environment. Especially electricity-generating companies have to face volatile wholesale prices, fuel price uncertainty, limited long-term hedging possibilities and huge, to a large extent, sunk investments. In this context, Uncertainty in the Electric Power Industry: Methods and Models for Decision Support aims at an integrative view on the decision problems that power companies have to tackle. It systematically examines the uncertainties power companies are facing and develops models to describe them - including an innovative approach combining fundamental and finance models for price modeling. The optimization of generation and trading portfolios under uncertainty is discussed with particular focus on CHP and is linked to risk management. Here the concept of integral earnings at risk is developed to provide a theoretically sound combination of value at risk and profit at risk approaches, adapted to real market structures and market liquidity. Also methods for supporting long-term investment decisions are presented: technology assessment based on experience curves and operation simulation for fuel cells and a real options approach with endogenous electricity prices.
650 0 _aENGINEERING.
650 0 _aDISTRIBUTION (PROBABILITY THEORY).
650 0 _aENGINEERING MATHEMATICS.
650 0 _aENGINEERING ECONOMY.
650 1 4 _aENGINEERING.
650 2 4 _aENERGY ECONOMICS.
650 2 4 _aENGINEERING ECONOMICS, ORGANIZATION, LOGISTICS, MARKETING.
650 2 4 _aAPPL.MATHEMATICS/COMPUTATIONAL METHODS OF ENGINEERING.
650 2 4 _aPROBABILITY THEORY AND STOCHASTIC PROCESSES.
650 2 4 _aOPERATIONS RESEARCH/DECISION THEORY.
650 2 4 _aELECTRICAL POWER GENERATION AND TRANSMISSION.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387230474
830 0 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v77
856 4 0 _uhttp://dx.doi.org/10.1007/b100484
_zVer el texto completo en las instalaciones del CICY
912 _aZDB-2-ENG
942 _2ddc
_cER
999 _c56130
_d56130