Modeling and Forecasting Electricity Demand - A Risk Management Perspective

The master thesis of Kevin Berk develops a stochastic model for the electricity demand of small and medium-sized companies that is flexible enough so that it can be used for various business sectors. The model incorporates the grid load as an exogenous factor and seasonalities on a daily, weekly and yearly basis. It is demonstrated how the model can be used e.g. for estimating the risk of retail contracts. The uncertainty of electricity demand is an important risk factor for customers as well as for utilities and retailers. As a consequence, forecasting electricity load and its risk is now an integral component of the risk management for all market participants.

List of contents

Electricity Market.- Energy Economy in Enterprises.- Time Series Analysis.- A one Factor Model for medium-term Load Forecasting.- Retail Contract Evaluation and Pricing.- MATLAB Implementation.

About the author

Kevin Berk is a Ph.D. student at the Mathematics Department of the University Siegen, Germany. His major research focus is risk management and time series models with applications in energy markets.

Summary

The master thesis of Kevin Berk develops a stochastic model for the electricity demand of small and medium-sized companies that is flexible enough so that it can be used for various business sectors.
The model incorporates the grid load as an exogeneous factor and seasonalities on a daily, weekly and yearly basis. It is demonstrated how the model can be used e.g. for estimating the risk of retail contracts. The uncertainty of electricity demand is an important risk factor for customers as well as for utilities and retailers. As a consequence, forecasting electricity load and its risk is now an integral component of the risk management for all market participants.

Product details

• Authors: Kevin Berk
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2015
• EAN: 9783658086688
• ISBN: 978-3-658-08668-8
• No. of pages: 115
• Dimensions: 156 mm x 6 mm x 211 mm
• Weight: 182 g
• Illustrations: XVI, 115 p. 39 illus.
• Series: Springer Spektrum; BestMasters; BestMasters
• Subjects: Natural sciences, medicine, IT, technology > Technology > Heat, energy and power station engineering; B, Energy Policy, Economics and Management, Behavioral Science and Psychology, Energy technology & engineering, Probability Theory and Stochastic Processes, Energy Policy, Energy industries & utilities, Probability & statistics, Probabilities, Stochastics, Probability Theory, Energy Efficiency, Energy and state