Solving the nonlinear power flow equations with an inexact Newtonmethod using GMRES

This paper presents a detailed investigation into the effectiveness of iterative methods in solving the linear system subproblem of a Newton power flow solution process. An exact Newton method employing an LU factorization has been one of the most widely used power flow solution algorithms, due to the efficient minimum degree ordering techniques that attempt to minimize fill-in. However, the LU factorization remains a computationally expensive task that can be avoided by the use of an iterative method in solving the linear subproblem. An inexact Newton method with a preconditioned Generalized Minimal Residual (GMRES) linear solver is presented as a promising alternative for solving the power flow equations. When combined with a good quality preconditioner, the Newton-GMRES method achieves a better than 50% reduction in computation, compared to Newton-LU, for two large-scale power systems: one with 3493 buses and 6689 branches, another with 8027 buses and 13765 branches     

Look-ahead voltage and load margin contingency selection functionsfor large-scale power systems

Given the current operating condition (obtained from the real-time data), the near-term load demand at each bus (obtained from short-term load forecast), and the generation dispatch (say, based on economic dispatch), we present in this paper a load margin measure (MW and/or MVAr) to assess the system's ability to withstand the forecasted load and generation variations. We also present a method to predict near-term system voltage profiles. The proposed look-ahead measure and the proposed voltage prediction are then applied to contingency selections for the near-term power system in terms of load margins to collapse and of the bus voltage magnitudes. We evaluate the proposed look-ahead measure and the voltage profile prediction on several power systems including a 1169-bus power system with 53 contingencies with promising results     

Destination: Perfection

The objectives of the perfect power project include: 1) the achievement of system-wide perfect power and demonstration of its technological viability; 2) 50% peak demand reduction capability via on-site generation when called upon by ComEd/PJM; 3) deferral of ComEd planned substation upgrades due to the demand reduction achieved; 4) demonstration of the economic value of perfect power, specifically the avoidance of outage costs and the introduction of significant savings and revenue from providing ancillary services; and 5) a design that can be replicated to any municipality-sized system where customers can participate in electric power market opportunities. In addition, the IIT team seeks to fulfill the mission of the university as set forth by President John L. Anderson, "IIT will be internationally recognized in distinctive areas of education and research, using as its platform the global city of Chicago, driven by a focus on professional and technology oriented education, and based on a culture of innovation that embraces bold and transformational ideas." Transforming the IIT power delivery infrastructure to achieve perfect power is a bold idea that will require a never-ending series of innovations. We have embraced the vision of the GEI and we look forward to sharing our progress with the power and energy community in the years to come.     

Status und Strategien zum Schutz des bedrohten Süd-Andenhirsches (Hippocamelus bisulcus): Bericht über das erste argentinisch-chilenische Treffen

Ohne Zusammenfassung     

A new power sensitivity method of ranking branch outagecontingencies for voltage collapse

The objective of this paper is to present a powerful procedure for identifying severe single branch outage contingencies with respect to saddle-mode bifurcation induced voltage collapse, given a power system operating point, a load demand forecast, and a generation dispatch. The new power sensitivity ranking algorithm for voltage collapse, called λ/MVA sensitivity, provides more accurate "distance to collapse" estimates than linear admittance sensitivity, yet requires only slightly more computation time. The distinguishing features are the ability (1) to rank all branches in a large-scale power system quickly, and (2) to estimate the outage contingency bifurcation values accurately. As an illustration, the new λ/MVA sensitivity ranking algorithm can estimate all 6689 single branch outage contingency bifurcation points (λ*_ctgc) of a 3493 bus power system within 3% relative error, except for two branches within 7%, in less than 4 min on a 180 MHz PentiumPro PC     

Some Mathematical and Numerical Aspects in Aluminum Production

In this paper, we present a mathematical modeling of some magnetohydrodynamic effects arising in an aluminum production cell as well as its numerical approximation by a finite element method. We put the emphasis on the magnetic effects which live in the whole three dimensional space and which are solved numerically with a domain decomposition method.