By Topic

Modeling Swedish real-time balancing power prices using nonlinear time series models

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Brolin, M.O. ; Sch. of Electr. Eng., R. Inst. of Technol. (KTH), Stockholm, Sweden ; Söder, L.

The liberalization of electricity markets and the rapid establishment of renewable power sources in the power system increases the need for decision support tools for planning, trading and operation. A suitable approach to model such decision problems is the use of stochastic optimization, where uncertain parameters, e.g. prices, are represented by a scenario tree. A scenario tree consists of possible outcomes of the stochastic prices. This paper describes a probabilistic model of real-time balancing prices. Real-time here refers to market places where balance power is traded with the TSO close to real-time. The proposed model reflects real-time markets applying hourly marginal pricing with different prices for upward and downward balancing. Further, the model is aimed for Monte Carlo simulation and generation of scenario trees. The model is based on nonlinear time series processes and use hourly day-ahead spot prices and real-time balancing demands as exogenous variables. By adjusting these prices and demands, future production mixes can be considered.

Published in:

Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on

Date of Conference:

14-17 June 2010