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Inverse optimization approach to the identification of electricity consumer models

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  • András Kovács

    (Institute for Computer Science and Control (SZTAKI))

Abstract

Stackelberg game models for demand response management in smart electricity grids have been studied extensively in the scientific literature. Still, a barrier to their practical applicability is the assumption that the retailer (leader in the game) has perfect knowledge about the consumers’ (followers’) decision model. This paper investigates the possibilities of reconstructing the consumers’ decision model from historic tariff and consumption data. For this purpose, it introduces an inverse optimization approach to eliciting the parameters of electricity consumer models formulated as linear programs from the historic samples. The inverse problem is first transformed into a quadratically constrained quadratic program, and then solved using successive linear programming techniques. The approach is demonstrated on a common consumer model with multiple types of deferrable loads behind a single smart meter. Experimental results are presented, and directions for future research are proposed.

Suggested Citation

  • András Kovács, 2021. "Inverse optimization approach to the identification of electricity consumer models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 521-537, June.
    • Handle: RePEc:spr:cejnor:v:29:y:2021:i:2:d:10.1007_s10100-020-00699-1
    DOI: 10.1007/s10100-020-00699-1
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    References listed on IDEAS

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