High Performance Computing and Parallel Processing for Power Utility Applications

Monochrome pictures of the Art Deco colored glass murals in the lobby of the
Niagara Mohawk building in Syracuse, NY.

SUMMARY

We are pursuing a project on the use of high performance computing, especially parallel computing, in power utility applications, in collaboration with Niagara Mohawk Power Corporation, a central New York utility headquartered in Syracuse.

PARTICIPATING INSTITUTIONS

NPAC, Syracuse University
School of Information Studies, Syracuse University
Niagara Mohawk Power Corporation

KEY CONTACTS

Paul Coddington | paulc@npac.syr.edu | 315-443-4883

IMPACT

Faster and more accurate modeling of power network stability, and power generation and distribution, should lead to more efficient operation of electrical power networks, reducing cost, fuel use, and environmental impact.

PROJECT DESCRIPTION

An important aspect of the operation of an electrical power network is the security model, that simulates the response of the network to disturbances such as component failure. These simulations allow power utilities to identify possible sources of cascading failures that could cause a disruption of power supply, and to take measures to prevent their occurrence. In order to maintain the fault tolerance of the network, extra generation and transmission capacity must be available. There is a certain margin of error factored into this extra capacity due to the limited accuracy of the simulations. Better simulations would allow improved system security and reduced operating margins, saving energy and reducing environmental impact.

Current security model simulations are based on component stability limits that are determined very infrequently, using worst-case models. Improved stability limits based on the actual state of the network would greatly improve the accuracy of these simulations. Stability limits are based on transient stability analysis, which examines the dynamic behavior of the network following a power flow disturbance. This involves the solution of a set of coupled differential-algebraic equations, which is a highly compute intensive problem. We are developing parallel algorithms to solve these equations, and the associated sparse matrix equations that are required for power systems problems.

Analysis of the output of the transient stability program is a technical art, requiring trained, experienced engineers. In order for the results to be available on-line in near real-time, we are planning to use an expert system to identify results as being transient stable or unstable. We are currently developing a knowledge base to be used for the expert system.

Another compute-intensive application being studied is the problem of unit commitment. This is a large-scale optimization problem, concerned with efficiently matching the available generation capacity to the expected load. We are also investigating other possible applications of HPC, from databases and billing to the simulation of nuclear power stations.

An ordering of a sparse matrix, representing the connectivity of an electrical power grid, into a block-diagonal-bordered form that is more suitable for parallelization. Blue denotes non-zeros, and red is fillin (elements that were originally zero but become non-zero during factorization).

REFERENCES

1. A.J. Wood and B.F. Wollenberg, Power Generation, Operation and Control, (Wiley, New York, 1984).
2. IEEE Committee Report, Parallel Processing in Power Systems Computations, IEEE Transactions on Power Systems, 7(2), 629, (1992).
3. NPAC technical report SCCS-549
   David Koester, Sanjay Ranka, and Geoffrey Fox, Power Systems Transient Stability - A Grand Computing Challenge.
4. NPAC technical report SCCS-550
   David Koester, Sanjay Ranka, and Geoffrey Fox, Parallel LU Factorization of Block-Diagonal-Bordered Sparse Matrices.
5. NPAC technical report
   David Koester, Sanjay Ranka, and Geoffrey Fox, Parallel Choleksi Factorization of Block-Diagonal-Bordered Sparse Matrices.
6. NPAC technical report SCCS-552
   David Koester, Sanjay Ranka, and Geoffrey Fox, Parallel Block-Diagonal-Bordered Sparse Linear Solvers for Electrical Power System Applications, Proceedings of the Scalable Parallel Libraries Conference, Mississippi State University, October 1993.
7. NPAC technical report SCCS-562
   Alvin Leung, Anthony Skjellum, and Geoffrey Fox, Concurrent DASSL: A Second-Generation, DAE Solver Library, Proceedings of the Scalable Parallel Libraries Conference, Mississippi State University, October 1993.
8. NPAC technical report SCCS-563
   Kamala Anupindi, Anthony Skjellum, Paul Coddington, and Geoffrey Fox, Parallel Differential-Algebraic Equations (DAE) Solvers for Power System Transient Stability Analysis, Proceedings of the Scalable Parallel Libraries Conference, Mississippi State University, October 1993.