Skip to main navigation Skip to search Skip to main content

Optimal scheduling of multi-tank multi-source system using genetic algorithm

  • Haien Fang*
  • , Jinliang Gao
  • , Yixing Yuan
  • *Corresponding author for this work
  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

For optimal operation of multi-storage tank multi-source system, a two-stage method is developed in this paper. In the first stage, the optimal storage policy of each tank is determined according to the electricity tariff. In the second stage, Genetic algorithm is applied to solve pump scheduling problem. The objective of the pump scheduling problem is to ensure that the required volume is adequately provided by the pumps while minimizing the operation cost. Decision variables are the settings of the pumps and speed ratio of variable-speed pumps at time steps of the total operational time horizon. A mixed coding methodology is developed according to the characteristics of decision variables. Daily operation cost savings of approximately 11% is obtained by application of the proposed method to a pressure zone of S.Y. water distribution system.

Original languageEnglish
Title of host publicationProceedings - 2010 2nd International Workshop on Intelligent Systems and Applications, ISA 2010
DOIs
StatePublished - 2010
Event2nd International Workshop on Intelligent Systems and Applications, ISA2010 - Wuhan, China
Duration: 22 May 201023 May 2010

Publication series

NameProceedings - 2010 2nd International Workshop on Intelligent Systems and Applications, ISA 2010

Conference

Conference2nd International Workshop on Intelligent Systems and Applications, ISA2010
Country/TerritoryChina
CityWuhan
Period22/05/1023/05/10

Keywords

  • Genetic algorithm
  • Multi-storage tank system
  • Pump scheduling
  • Storage policy
  • Water supply network

Fingerprint

Dive into the research topics of 'Optimal scheduling of multi-tank multi-source system using genetic algorithm'. Together they form a unique fingerprint.

Cite this