Uncertainty in the Electric Power Industry Methods and Models for Decision Support - Weber, Christoph; SpringerLink (Online service) (New York, NY : Springer New York : Imprint: Springer, 2005)
Around 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.
Deregulation 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.
Keywords: Energy policy; Energy and state; Engineering economics; Engineering economy; Applied mathematics; Engineering mathematics; Probabilities; Operations research; Decision making; Energy Policy, Economics and Management; Engineering Economics, Organization, Logistics, Marketing; Mathematical and Computational Engineering; Probability Theory and Stochastic Processes; Operations Research/Decision Theory; Energy Policy, Economics and Management