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Modeling swedish real-time balancing power prices using nonlinear time series models
KTH, School of Electrical Engineering (EES), Electric Power Systems.
KTH, School of Electrical Engineering (EES), Electric Power Systems.ORCID iD: 0000-0002-8189-2420
2010 (English)In: 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2010, 2010, 358-363 p.Conference paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
2010. 358-363 p.
Keyword [en]
Real-time balancing market, Stochastic process, Time series, Decision problems, Decision support tools, Electricity market, Exogenous variables, Marginal pricing, Market place, Monte Carlo Simulation, Nonlinear time series, Nonlinear time series model, Power sources, Power systems, Probabilistic models, Production mix, Real-time market, Scenario tree, Spot price, Stochastic optimizations, Time balancing, Uncertain parameters, Commerce, Computer simulation, Costs, Decision support systems, Decision trees, Monte Carlo methods, Random processes, Real variables, Stochastic systems, Uncertainty analysis, Stochastic models
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-36370DOI: 10.1109/PMAPS.2010.5526246ScopusID: 2-s2.0-77956442838ISBN: 978-1-4244-5720-5OAI: diva2:430718
QC 20110712Available from: 2011-07-12 Created: 2011-07-12 Last updated: 2011-07-12Bibliographically approved

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Olsson, MagnusSöder, Lennart
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