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Decision Making under Constraints pp 189–196Cite as

The Role of Affine Arithmetic in Robust Optimal Power Flow Analysis

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Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 276))

Abstract

Optimal Power Flow (OPF) analysis represents the mathematical foundation of many power engineering applications. For the most common formalization of the OPF problem, all input data are specified using deterministic variables, and the corresponding solutions are deemed representative of the limited set of system conditions. Hence, reliable algorithms aimed at representing the effect of data uncertainties in OPF analyses are required in order to allow analysts to estimate both the data and solution tolerance, providing, therefore, insight into the level of confidence of OPF solutions. To address this issue, this Chapter outline the role of novel solution methodologies based on the use of Affine Arithmetic.

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Authors and Affiliations

  1. Department of Engineering, University of Sannio, Piazza Roma 21, 82100, Benevento, Italy

    Alfredo Vaccaro

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  1. Alfredo Vaccaro
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Correspondence to Alfredo Vaccaro .

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Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Martine Ceberio

  2. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

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Vaccaro, A. (2020). The Role of Affine Arithmetic in Robust Optimal Power Flow Analysis. In: Ceberio, M., Kreinovich, V. (eds) Decision Making under Constraints. Studies in Systems, Decision and Control, vol 276. Springer, Cham. https://doi.org/10.1007/978-3-030-40814-5_24

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