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This paper describes our experience with developing a parallel weighted- least-square (WLS) state estimation (SE) program for shared-memory parallel computers. Since the key computational kernel of the WLS algorithm based on the Newton-Raphson approach is a solver of sparse linear equations, a significant part of our effort was focused on selecting, implementing and evaluating this algorithm. An optimized...
We are investigating the effectiveness of parallel weighted- least-square (WLS) state estimation solvers on shared-memory parallel computers. Shared-memory parallel architectures are rapidly becoming ubiquitous due to the advent of multi-core processors. In the current evaluation, we are using an LU-based solver as well as a conjugate gradient (CG)-based solver for a 1177-bus system. In lieu of a...
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