Abstract
In this paper, a problem of great practical interest, related to the production, transmission and distribution of electric energy, is taken into consideration and the optimal management policy for the system is formulated as a nonlinear mathematical programming. The optimization model has been solved by implementing an Augmented Lagrangian algorithm on shared memory vector-parallel computing environments. The computational experiments have been carried out on the ALLIANT FX/80 and CONVEX C-240. The numerical results show the efficiency of the proposed algorithm and the suitability of the parallel computing systems in solving large scale nonlinear optimization problems.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Conforti, D., Grandinetti, L.: An Experience of Advanced Computation Techniques in the solution of Nonlinearly Constrained Optimization Problems. Lecture Notes in Economics and Mathematical Systems 304 (1988) 69–85
Grandinetti, L., Conforti, D.: Numerical Comparisons of Nonlinear Programming Algorithms on Serial and Vector Processors using Automatic Differentiation. Mathematical Programming 42 (1988) 375–389
Conforti, D., Grandinetti, L.: Nonlinear Optimization Codes for Real Time Solution of Large Scale Problems: a case study on the Parallel Vector Supercomputers CRAY X-MP and IBM 3090/VF. Parallel Computing, D.J. Evans, C. Sutti (eds.), Adam Hilger, Bristol, (1989) 201–211
Murtagh, B. A., Saunders, M. A.: A projected Lagrangian algorithm and its implementation for sparse nonlinear constraints. Mathematical Programming Study 16 (1982) 84–117
Fletcher, R.: Practical Methods of Optimization. John Wiley and Sons, Chichester, 1987
Luenberger, D. G.: Linear and Nonlinear Programming. Addison-Wesley, Reading, 1984
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1995 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Conforti, D., De Luca, L. (1995). Optimal management of electric power systems via high performance computing. In: Hertzberger, B., Serazzi, G. (eds) High-Performance Computing and Networking. HPCN-Europe 1995. Lecture Notes in Computer Science, vol 919. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0046654
Download citation
DOI: https://doi.org/10.1007/BFb0046654
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-59393-5
Online ISBN: 978-3-540-49242-9
eBook Packages: Springer Book Archive