In order to optimize the type and number of pumps, operation parameters of pumping stations in multisource water injection systems simultaneously, a mathematical model was established, in which the input power of pumps is objective function, the water balance in system, flow rate and operating pressure as well as type of pumps are served as constraint conditions. Taking the features of this optimization problem in account, a dual coding was proposed to improve the existing genetic algorithm, and then was appied to solve the mathematical model. In that dual coding, a real number was adopted in the row in the coding to indicate the flow rate of a pump, an integer was put into the second row to present the number of a water injection station where the pump was installed; thus, an exact discribtion of the optimization variables was realized; obviously, the coding of solution was in variable length. An approach was porposed, where the type of pump was determined initially according to a flow rate, then the rest operating parameters of the pump were decided based on the known type. In applications of the improved genetic algorithm, the method for generating of initial solutions was given; meanwhile, a variety of crossover and mutation methods, which were adaptable to the optimization problem, were cast. As a result of this, a part of the constraint conditions were satisfied, and the number of infeasible solutions was reduced. The water injection system in an oil field with deep oil wells was optimized by using the algorithm proposed, the total input power was reduced by 2.42%, showing simultaneously optimizating pump seclection and pump operating parameters has a remarkable energy saving effect in the multisource water injection system.
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