In this paper, we propose a model-based approach to the computation of line outage angle factors (LOAFs), which relies on the use of angle factors (AFs) and power transfer distribution factors (PTDFs). A LOAF provides the sensitivity of the voltage angle difference between the terminal buses of a transmission line in the event the line is outaged to the pre-outage active power flow on the line. Large angle differences between the terminal buses of an outaged line can prevent the successful reclosure of the line-such an event was a significant contributing factor to the 2011 San Diego blackout. The proposed model-based LOAFs, along with the AFs and injection shift factors (ISFs), enable the fast computation of the impact on the angle across lines of line outages and active power injections, and provide system operators a systematic mean by which to assess line outage angles and undertake the appropriate dispatch actions necessary to alleviate large phase angle differences. We demonstrate the effectiveness of the proposed LOAFs with a case study carried out on the IEEE 14-bus test system.

%B 2015 North American Power Symposium (NAPS) %I IEEE %C Charlotte, NC, USA %P 1 - 5 %8 10/2015 %R 10.1109/NAPS.2015.7335130 %0 Journal Article %J IEEE Transactions on Power Systems %D 2014 %T A Sparse Representation Approach to Online Estimation of Power System Distribution Factors %A Chen, Yu Christine %A Alejandro D. Dominguez-Garcia %A Peter W. Sauer %K AARD %X In this paper, we propose a method to compute linear sensitivity distribution factors (DFs) in near real time without relying on a power flow model of the system. Specifically, we compute the injection shift factors (ISFs) of a particular line of interest with respect to active power injections at all buses (all other DFs can be determined from ISFs). The proposed ISF estimation method relies on the solution of an underdetermined system of linear equations that arise from high-frequency synchronized measurements obtained from phasor measurement units. We exploit a sparse representation (i.e., one in which many elements are zero) of the vector of desired ISFs via rearrangement by electrical distance and an appropriately chosen linear transformation, and cast the estimation problem into a sparse vector recovery problem. As we illustrate through case studies, the proposed approach provides accurate DF estimates with fewer sets of synchronized measurements than earlier approaches that rely on the solution of an overdetermined system of equations via the least-squares errors estimation method. %B IEEE Transactions on Power Systems %P 1 - 12 %8 10/2014 %! IEEE Trans. Power Syst. %R 10.1109/TPWRS.2014.2356399