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.