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Portfolio optimization using Mixture Design of Experiments: Scheduling trades within electricity markets

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  • de Oliveira, Francisco Alexandre
  • de Paiva, Anderson Paulo
  • Lima, José Wanderley Marangon
  • Balestrassi, Pedro Paulo
  • Mendes, Ronã Rinston Amaury

Abstract

Deregulation of the electricity sector has given rise to several approaches to defining optimal portfolios of energy contracts. Financial tools - requiring substantial adjustments - are usually used to determine risk and return. This article presents a novel approach to adjusting the conditional value at risk (CVaR) metric to the mix of contracts on the energy markets; the approach uses Mixture Design of Experiments (MDE). In this kind of experimental strategy, the design factors are treated as proportions in a mixture system considered quite adequate for treating portfolios in general. Instead of using traditional linear programming, the concept of desirability function is here used to combine the multi-response, nonlinear objective functions for mean with the variance of a specific portfolio obtained through MDE. The maximization of the desirability function is implied in the portfolio optimization, generating an efficient recruitment frontier. This approach offers three main contributions: it includes risk aversion in the optimization routine, it assesses interaction between contracts, and it lessens the computational effort required to solve the constrained nonlinear optimization problem. A case study based on the Brazilian energy market is used to illustrate the proposal. The numerical results verify the proposal's adequacy.

Suggested Citation

  • de Oliveira, Francisco Alexandre & de Paiva, Anderson Paulo & Lima, José Wanderley Marangon & Balestrassi, Pedro Paulo & Mendes, Ronã Rinston Amaury, 2011. "Portfolio optimization using Mixture Design of Experiments: Scheduling trades within electricity markets," Energy Economics, Elsevier, vol. 33(1), pages 24-32, January.
  • Handle: RePEc:eee:eneeco:v:33:y:2011:i:1:p:24-32
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    3. Losekann, Luciano & Marrero, Gustavo A. & Ramos-Real, Francisco J. & de Almeida, Edmar Luiz Fagundes, 2013. "Efficient power generating portfolio in Brazil: Conciliating cost, emissions and risk," Energy Policy, Elsevier, vol. 62(C), pages 301-314.
    4. George J Besseris, 2013. "A Distribution-Free Multi-Factorial Profiler for Harvesting Information from High-Density Screenings," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-13, August.
    5. Leme, Rafael C. & Paiva, Anderson P. & Steele Santos, Paulo E. & Balestrassi, Pedro P. & Galvão, Leandro de Lima, 2014. "Design of experiments applied to environmental variables analysis in electricity utilities efficiency: The Brazilian case," Energy Economics, Elsevier, vol. 45(C), pages 111-119.

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