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Analysis of Hedging Strategies for Hydro Power on the Nordic Power Market
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2015 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Hydro power is the largest source for generation of electricity in the Nordic region today.

This production is heavily dependent on the weather since it dictates the terms for the availability and the amount of power to be produced. Vattenfall as a company has an incentive to avoid volatile revenue streams as it facilitates economic planning and induces a positive effect on its credit rating, thus also on its bottom line. Vattenfall is a large producer of hydro power with a possibility to move the power market which adds further complexity to the problem. In this thesis the authors develop new hedging strategies which will hedge more efficiently. With efficiency is meant the same risk, or standard deviation, at a lower cost or alternatively formulated lower risk for the same cost. In order to enable comparison and make claims about efficiency, a reference solution is developed that should reflect their current hedging strategy. To achieve higher efficiency we focus on finding dynamic hedging strategies. First a prototype model is suggested to facilitate the construction of the solution methods and if it is worthwhile to pursue a further investigation. As this initial prototype model results showed that there were substantial room for efficiency improvement, a larger main model with parameters estimated from data is constructed which encapsulate the real world scenario much better. Four different solutions methods are developed and applied to this main model setup. The results are then compared to reference strategy. We find that even though the efficiency was less then first expected from the prototype model results, using these new hedging strategies could reduce costs by 1.5 % - 5%. Although the final choice of the hedging strategy might be down to the end user we suggest the strategy called BW to reduce costs and improve efficiency. The paper also discusses among other things; the solution methods and hedging strategies, the term optimality and the impact of parameters in the model.

Place, publisher, year, edition, pages
TRITA-MAT-E, 2015:12
National Category
Probability Theory and Statistics
URN: urn:nbn:se:kth:diva-164519OAI: diva2:810154
Subject / course
Mathematical Statistics
Educational program
Master of Science - Mathematics
Available from: 2015-05-06 Created: 2015-04-17 Last updated: 2015-05-06Bibliographically approved

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