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Multistage Stochastic Portfolio Optimisation in Deregulated Electricity Markets Using Linear Decision Rules

Paula Rocha (paula.martins-da-silva-rocha08***at***imperial.ac.uk)
Daniel Kuhn (d.kuhn***at***imperial.ac.uk)

Abstract: The deregulation of electricity markets increases the financial risk faced by retailers who procure electric energy on the spot market to meet their customers' electricity demand. To hedge against this exposure, retailers often hold a portfolio of electricity derivative contracts. In this paper, we propose a multistage stochastic mean-variance optimisation model for the management of such a portfolio. To reduce computational complexity, we apply two approximations: we aggregate the decision stages and solve the resulting problem in linear decision rules (LDR). The LDR approach consists of restricting the set of recourse decisions to those affine in the history of the random parameters. When applied to mean-variance optimisation models, it leads to convex quadratic programs. Since their size grows typically only polynomially with the number of periods, they can be efficiently solved. Our numerical experiments illustrate the value of adaptivity inherent in the LDR method and its potential for enabling scalability to problems with many periods.

Keywords: OR in energy, electricity portfolio management, stochastic programming, risk management, linear decision rules

Category 1: Applications -- OR and Management Sciences

Category 2: Stochastic Programming

Citation: Working paper, Department of Computing, Imperial College London, June 2010

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Entry Submitted: 06/04/2010
Entry Accepted: 06/04/2010
Entry Last Modified: 11/20/2012

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