Power System Restoration With Transient Stability

Authors: Hassan Hijazi, Terrence W.K. Mak, Pascal Van Hentenryck

AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Experimental results on existing benchmarks confirm the feasibility of the new approach.
Researcher Affiliation Collaboration Hassan Hijazi and Terrence W.K. Mak and Pascal Van Hentenryck NICTA and Australian National University 7 London Circuit, Canberra, ACT 2601, Australia {Hassan.Hijazi,Terrence.Mak,Pascal.Vanhentenryck}@nicta.com.au
Pseudocode No The paper includes mathematical models and a flow chart, but not structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide an explicit statement or link for open-source code for the methodology described.
Open Datasets Yes We have tested our model on 5 MATPOWER benchmarks (Zimmerman, Murillo-S andnchez, and Thomas 2011).
Dataset Splits No The paper uses standard MATPOWER benchmarks but does not specify any training/validation/test dataset splits, as it applies an optimization model rather than a machine learning training process requiring such splits.
Hardware Specification No The paper does not provide specific hardware details (e.g., CPU, GPU models, memory) used for running its experiments.
Software Dependencies Yes Our model is implemented in AMPL (Fourer, Gay, and Kernighan 2002; AMPL 2014), and uses Ipopt 3.11 (W achter and Biegler 2006) as a nonlinear solver.
Experiment Setup Yes Table 1 presents experimental results for various generator reactances and maximum rotor swing limits δ. The table presents aggregate results obtained by summing up all the objective values after solving Model 2 for all of the restoration steps (after filtering and simplification). Note that, in general, a rotor angle limit of 90 degrees is considered acceptable, the goal of the current experiment is to push the limits on this bound as far as possible. (T = 400, = 0.005)