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Estimation of pump-curves using genetic algorithms

Published: 12 July 2008 Publication History

Abstract

This paper presents a variety of different ways of estimating the general parameters for pump-curves. First a formulation is made that converts the problem into estimating four parameters in this general formulation. Then three different methods that utilize the general formulation are presented. The estimated parameters for each method are used in generating the desired pump-curves, and the quality of the estimates are determined. The paper finishes with a recommendation that, for estimation of the generalized parameters, the method utilizing speed differences is preferable over the other methods discussed in the paper.

References

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Y.-H. Dai. New properties of a nonlinear conjugate gradient method. Numerische Mathematik, 89:83--98, 2001.
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Y.-H. Dai and L.-Z. Liao. New conjugacy conditions and related nonlinear conjugate gradient methods. Applied Mathematics and Optimization, 43:87--101, 2001.
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K. Deb. Multi-Objective Optimization using Evolutionary Algorithms. John Wiley & Sons, Ltd., West Sussex, England, 1st edition, 2001.
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D. E. Goldberg. The Design of Innovation: Lessons from and for Competent Genetic Algorithms. Genetic Algorithms and Evolutionary Computation. Kluwer Academic Publishers, Norwell, MA, 2002.
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Grundfos A/S. Pump handbook. Website, 2007. http://net.grundfos.com/doc/webnet/professional profile/int/documentation.html.
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C. Kanzow, N. Yamashita, and M. Fukushima. Levenberg-marquardt methods for constrained nonlinear equations with strong local convergence properties. Journal of Computational and Applied Mathematics, 172:375--397, 2004.
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G. K. M. Pedersen and Z. Yang. Efficiency optimization of a multi-pump booster system. In Genetic and Evolutionary Computation -- GECCO-2008, Atlanta, GA, 2008. ACM Press.
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K. Sastry. Single and multiobjective genetic algorithm toolbox for matlab in c++. IlliGAL Report No. 2007017, University of Illinois at Urbana-Champaign, Illinois Genetic Algorithms Laboratory, Urbana, IL, 2007.
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T.-L. Yu, K. Sastry, D. E. Goldberg, and M. Pelikan. Population sizing for entropy-based model building in genetic algorithms. IlliGAL Report No. 2006020, University of Illinois at Urbana-Champaign, Illinois Genetic Algorithms Laboratory, Urbana, IL, 2006.

Cited By

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  • (2022)Energy Performance Curves Prediction of Centrifugal Pumps Based on Constrained PSO-SVR ModelEnergies10.3390/en1509330915:9(3309)Online publication date: 1-May-2022
  • (2010)Optimal scheduling and control of a multi-pump boosting system2010 IEEE International Conference on Control Applications10.1109/CCA.2010.5611177(2071-2076)Online publication date: Sep-2010
  • (2008)Efficiency optimization of a multi-pump booster systemProceedings of the 10th annual conference on Genetic and evolutionary computation10.1145/1389095.1389400(1611-1618)Online publication date: 13-Jul-2008

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cover image ACM Conferences
GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation
July 2008
1814 pages
ISBN:9781605581309
DOI:10.1145/1389095
  • Conference Chair:
  • Conor Ryan,
  • Editor:
  • Maarten Keijzer
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2008

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Author Tags

  1. curve fitting
  2. parameter estimation
  3. pump curves
  4. simple genetic algorithm

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GECCO08
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Cited By

View all
  • (2022)Energy Performance Curves Prediction of Centrifugal Pumps Based on Constrained PSO-SVR ModelEnergies10.3390/en1509330915:9(3309)Online publication date: 1-May-2022
  • (2010)Optimal scheduling and control of a multi-pump boosting system2010 IEEE International Conference on Control Applications10.1109/CCA.2010.5611177(2071-2076)Online publication date: Sep-2010
  • (2008)Efficiency optimization of a multi-pump booster systemProceedings of the 10th annual conference on Genetic and evolutionary computation10.1145/1389095.1389400(1611-1618)Online publication date: 13-Jul-2008

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