The Office of Electricity Delivery and Energy Reliability of the U.S. Department of Energy (DOE), the Bonneville Power Administration (BPA), and industry and academic collaborators have leveraged resources to develop a new, cost-effective method for validating power plant models using synchrophasor data.

1 aOverholt, Philip, N.1 aKosterev, Dmitry1 aEto, Joseph, H.1 aYang, Steve1 aLesieutre, Bernard, C. uhttps://certs.lbl.gov/publications/improving-reliability-through-better01788nas a2200229 4500008003900000022001400039245009600053210006900149260001100218300001600229490000700245520106900252653001301321653000901334653002901343653001001372100002401382700002201406700002701428700002901455856007401484 2013 d a0885-895000aImplementation of a Large-Scale Optimal Power Flow Solver Based on Semidefinite Programming0 aImplementation of a LargeScale Optimal Power Flow Solver Based o c4/2013 a3987 - 39980 v283 aThe application of semidefinite programming to the optimal power flow (OPF) problem has recently attracted significant research interest. This paper provides advances in modeling and computation required for solving the OPF problem for large-scale, general power system models. Specifically, a semidefinite programming relaxation of the OPF problem is presented that incorporates multiple generators at the same bus and parallel lines. Recent research in matrix completion techniques that decompose a single large matrix constrained to be positive semidefinite into many smaller matrices has made solution of OPF problems using semidefinite programming computationally tractable for large system models. We provide three advances to existing decomposition techniques: a matrix combination algorithm that further decreases solver time, a modification to an existing decomposition technique that extends its applicability to general power system networks, and a method for obtaining the optimal voltage profile from the solution to a decomposed semidefinite program.10aAA13-00510aAARD10aoptimal power flow (OPF)10aRTGRM1 aMolzahn, Daniel, K.1 aHolzer, Jesse, T.1 aLesieutre, Bernard, C.1 aDeMarco, Christopher, L. uhttps://certs.lbl.gov/publications/implementation-large-scale-optimal01460nas a2200169 4500008003900000245006800039210006800107260002800175300000700203520085400210653006901064653001001133653001401143653003001157100002701187856007601214 2005 d00aImproving Dynamic Load and Generator Response Performance Tools0 aImproving Dynamic Load and Generator Response Performance Tools aBerkeleybLBNLc11/2005 a743 aThis report is a scoping study to examine research opportunities to improve the accuracy of the system dynamic load and generator models, data and performance assessment tools used by CAISO operations engineers and planning engineers, as well as those used by their counterparts at the California utilities, to establish safe operating margins. Model-based simulations are commonly used to assess the impact of credible contingencies in order to determine system operating limits (path ratings, etc.) to ensure compliance with NERC and WECC reliability requirements. Improved models and a better understanding of the impact of uncertainties in these models will increase the reliability of grid operations by allowing operators to more accurately study system voltage problems and the dynamic stability response of the system to disturbances.

10aconsortium for electric reliability technology solutions (certs)10aFIDVR10aFIDVR-00710aWECC Composite Load Model1 aLesieutre, Bernard, C. uhttps://certs.lbl.gov/publications/improving-dynamic-load-and-generator