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.

Systematically examines the uncertainties power companies are facing in competitive markets Develops and applies mathematical, operations research methods to describe and manage these uncertainties Some of the application fields include: market and price modeling with combined fundamental and finance models, optimization of generation and trading portfolios including CHP in the short and medium term, risk management using an integral earnings at risk measure adapted to market structure and market liquidity, technology assessment for fuel cells, long-term optimal generation portfolios under fuel price uncertainty

Autorentext

Christoph Weber is a Full Professor of Management Sciences and Energy Economics at the University of Duisburg-Essen, Germany. With a background in Mechanical Engineering and a Ph.D. in Economics, his main research interests are in electricity markets, risk and sustainable energy systems, and the use of operations research methods in connection with energy. Dominik Möst is a Full Professor of Energy Economics at the Faculty of Business and Economics, Technische Universität Dresden, Germany. He studied Industrial Engineering and Management at the Universität Karlsruhe (TH) and at the ENSGI-INPG Grenoble (Ecole nationale supérieure de Genie Industriel, France), holds a Ph.D. in Economics from the Universität Karlsruhe (TH) and habilitated at the Karlsruhe Institute of Technology (KIT). His research interests are European electricity and gas markets, the integration of renewable energy sources, and energy system modeling, as well as energy and resource efficiency. Wolf Fichtner is a Full Professor of Energy Economics at the Karlsruhe Institute of Technology (KIT), Germany. He studied Industrial Engineering and Management at the Universität Karlsruhe (TH), holds a doctoral degree in Economics and habilitated at the Universität Karlsruhe (TH). His main research interests are electricity markets, sustainable energy systems, and operations research in energy systems.

Inhalt
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.