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.
The Role of Affine Arithmetic in Robust Optimal Power Flow Analysis
Vaccaro A.
2020-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
