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.
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