Ruibal, Claudio
(2007)
On the Variance of Electricity Prices in Deregulated Markets.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Since 1990 many countries have started a deregulation process in the electricity wholesale market with a view to gaining in efficiency, lowering prices and encouraging investments. In most of the markets these objectives have been accomplished, but at the same time, prices have shown high volatility. This is mainly due to certain unique characteristics of electricity as a commodity: it cannot be easily stored; and the flow across lines is dependent on the laws of physics. Electricity must be delivered on the spot to the load.Electricity price variance has been studied very little. Variance is important for constructing prediction intervals for the price. And it is a key factor in pricing derivatives, which are used for energy risk management purposes.A fundamental bid-based stochastic model is presented to predict electricity hourly prices and average price in a given period. The model captures both the economic and physical aspects of the pricing process, considering two sources of uncertainty: availability of theunits and demand. This work is based on three oligopoly models -Bertrand, Cournot and Supply Function Equilibrium (SFE) - and obtains closed form expressions for expected value and variance of electricity hourly prices and average price.Sensitivity analysis is performed on the number of firms, anticipated peak demand and price elasticity of demand. It turns out that as the number of firms in the market decreases, the expected values increase by a significant amount, especially for the Cournot model. Variances for Cournot model also increase. But the variances for SFE model decrease, taking even smaller values than Bertrand's.Price elasticity of demand severely affects expected values and variances in the Cournot model. So does the firms' anticipated peak demand with respect to full installed capacity in the SFE model. Market design and market rules should take these two parameters into account.Finally, a refinement of the models is used to investigate to what extent prices can be more accurately predicted when temperature forecast is at hand. It has been demonstrated that an accurate temperature forecast can reduce significantly the prediction error of the electricity prices.
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Details
Item Type: |
University of Pittsburgh ETD
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Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
Title | Member | Email Address | Pitt Username | ORCID |
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Committee Chair | Mazumdar, Mainak | | | | Committee Member | Rajgopal, Jayant | | | | Committee Member | Needy, Kim LaScola | | | | Committee Member | Rajan, Uday | | | |
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Date: |
31 January 2007 |
Date Type: |
Completion |
Defense Date: |
30 August 2006 |
Approval Date: |
31 January 2007 |
Submission Date: |
23 August 2006 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Swanson School of Engineering > Industrial Engineering |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
Average Prices; Bertrand Model; Conditional Value-at-Risk; Cournot Model; Deregulated Electricity Markets; Edgeworth Expansion; Electricity Derivatives Prices; Electricity Price Variance; Electricity Prices; Energy Risk Management; Hourly Prices; Method of Cumulants; Rudkevich and Duckworth and Rosen's Formula; Stochastic Load; Supply Function Equilibrium; Value-at-Risk; Volatility |
Other ID: |
http://etd.library.pitt.edu/ETD/available/etd-08232006-111342/, etd-08232006-111342 |
Date Deposited: |
10 Nov 2011 20:00 |
Last Modified: |
15 Nov 2016 13:49 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/9243 |
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