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Optimal water allocation method based on the genetic algorithm for a system of a reservoir and two pumping stations
Author(s) -
Ling Zhuo,
Jilin Cheng,
Zhihao Gong
Publication year - 2021
Publication title -
water science and technology water supply
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 39
eISSN - 1607-0798
pISSN - 1606-9749
DOI - 10.2166/ws.2021.236
Subject(s) - genetic algorithm , adaptability , economic shortage , mathematical optimization , water resources , computer science , water supply , algorithm , environmental science , environmental engineering , ecology , mathematics , linguistics , philosophy , government (linguistics) , biology
The subtropical monsoon climate zone features abundant water resources but with uneven temporal and spatial distribution, so seasonal water shortages are frequent. In order to reduce the water shortage and water spill in this region, a nonlinear optimization model for the joint operation of a system of a reservoir and two pumping stations is developed in this paper. In this model, the water supply of the reservoir and pumping volume of the pumping stations in each period are two types of decision variables, which are subjected to the annual available water in the reservoir, water rights of the two pumping stations and the operation rule of the reservoir. However, modern intelligent algorithms may fail in dealing with constraints of if-statements like the operation rule of the reservoir in this model. In light of the shortcoming of the classical genetic algorithm, a modified genetic algorithm is proposed by comparing the different methods for dealing with constraints. The modified algorithm shows a better adaptability to the operation rule. The modified genetic algorithm may provide a reference for similar modern intelligent algorithms to solve optimal water resources allocation for systems of multiple reservoirs and multiple pumping stations.

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