A Genco self-scheduling problem with correlated prices using a new robust optimization approach

Amir Jalilvand-Nejad, Rasoul Shafaei and Hamid Shahriari

International Journal of Production Research, 2017, vol. 55, issue 11, 3249-3265

Abstract: In this research, a self-scheduling problem for a power generation company (Genco), participating in a day-ahead power market is studied. A robust optimisation approach is followed to tackle uncertainty on the market prices. Due to the existing correlations among hourly market prices and in order to enhance the value of the objective function in an uncertain environment, a new robust optimisation approach is developed and presented to prevent over-conservative solutions. A couple of polyhedral uncertainty sets are applied to protect the optimal solution solely against any correlated perturbation. In addition two robust self-scheduling models are formulated under these uncertainty sets. The results of this study justify the performance of the proposed models compared to those of the existing robust self-scheduling model applied for conventional polyhedral uncertainty set.

Date: 2017
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DOI: 10.1080/00207543.2017.1288944

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