Transversality enforced Newton–Raphson algorithm for fast calculation of maximum loadability
Name
IET Generation Trans Dist - 2018 - Ali - Transversality enforced Newton Raphson algorithm for fast calculation of maximum.pdf
Description
Published version
Size
1.36 MB
Format
Adobe PDF
Checksum (MD5)
0ccb79d7eea9b0d42264dd1d50d231fa
Author(s)
Ali, Mazhar
Dymarsky, Anatoly
Turitsyn, Konstantin
Date Issued
February 7, 2018
Journal
IET Generation, Transmission & Distribution
Publisher
Wiley
Citation
Ali, M., Dymarsky, A. and Turitsyn, K. (2018), Transversality enforced Newton–Raphson algorithm for fast calculation of maximum loadability. IET Gener. Transm. Distrib., 12: 1729-1737.
Version
Final published version
Abstract
The authors propose a novel modification of the conventional Newton-Raphson load flow solver for characterisation of the maximal system loadability. Within the proposed approach, the standard power flow equations are extended with (i) an algebraic representation of maximal and minimal voltage level conditions and (ii) with the so-called transversality condition restricting the set of solutions to the boundary of the solvability region. Solutions to this extended system of equation characterise the maximal load levels for which the solution of power flow equations exists and satisfies the standard feasibility constraints on voltage levels. The resulting system of equations is non-singular and can be solved with just a few standard Newton-Raphson type iterations. Different possible choices of transversality conditions are discussed together with fast algorithms for evaluating the transversality conditions and their gradients. Implementation of the algorithm is described in detail, and its performance is validated on several IEEE cases.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1049/iet-gtd.2017.1273
