Comparison of two large scale NLP strategies for determining optimal pump station controls

Qinghui Zhong, Kevin E Lansey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To solve the general nonlinear problem which is not simplified using the uniform spatial demand patterns, a two-level hierarchial scheme has been identified. The purpose of this decomposition is to reduce space of possible pump combinations at each time period. Thus, a DP technique may be then easily applied to find out an optimal combinations. The first stage of the algorithm is to solve a nonlinear programming problem (NLP) for the optimal tank trajectories. The decision variables in this problem are each pump station's discharge and pumped head for each period. The second level, a DP method is applied to find the best combination for each operation time period based on the optimal tank trajectories. Within the scope of this paper, the authors only focus on the first level, e.g., the NLP module. The real-time pump station operation problem has been posed as a large scale NLP which can be efficiently considered using a problem reduction technique. This formulation is discussed in detail. A discussion of two methods to solve the resulting NLP is presented and conclusions regarding their advantages are discussed.

Original languageEnglish (US)
Title of host publicationWater Resources Planning and Management and Urban Water Resources
EditorsJerry L. Anderson
PublisherPubl by ASCE
Pages954-958
Number of pages5
ISBN (Print)0872628051
StatePublished - 1991
EventProceedings of the 18th Annual Conference and Symposium - New Orleans, LA, USA
Duration: May 20 1991May 22 1991

Other

OtherProceedings of the 18th Annual Conference and Symposium
CityNew Orleans, LA, USA
Period5/20/915/22/91

Fingerprint

Nonlinear programming
Pumps
Trajectories
Decomposition

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Zhong, Q., & Lansey, K. E. (1991). Comparison of two large scale NLP strategies for determining optimal pump station controls. In J. L. Anderson (Ed.), Water Resources Planning and Management and Urban Water Resources (pp. 954-958). Publ by ASCE.

Comparison of two large scale NLP strategies for determining optimal pump station controls. / Zhong, Qinghui; Lansey, Kevin E.

Water Resources Planning and Management and Urban Water Resources. ed. / Jerry L. Anderson. Publ by ASCE, 1991. p. 954-958.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhong, Q & Lansey, KE 1991, Comparison of two large scale NLP strategies for determining optimal pump station controls. in JL Anderson (ed.), Water Resources Planning and Management and Urban Water Resources. Publ by ASCE, pp. 954-958, Proceedings of the 18th Annual Conference and Symposium, New Orleans, LA, USA, 5/20/91.
Zhong Q, Lansey KE. Comparison of two large scale NLP strategies for determining optimal pump station controls. In Anderson JL, editor, Water Resources Planning and Management and Urban Water Resources. Publ by ASCE. 1991. p. 954-958
Zhong, Qinghui ; Lansey, Kevin E. / Comparison of two large scale NLP strategies for determining optimal pump station controls. Water Resources Planning and Management and Urban Water Resources. editor / Jerry L. Anderson. Publ by ASCE, 1991. pp. 954-958
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