基于遗传算法的水源热泵系统抽灌量优化配置

Optimal pumping and recharging rates allocation for a water-source heat-pump system based on a genetic algorithm

抽灌井设计是水源热泵系统设计中的关键环节之一,但目前对抽水量和回灌量的配置仍依据经验而行,导致运行成本较高。针对该问题,本文利用抽水和回灌现场试验资料,根据抽水井和回灌井的实际布局情况,建立了不同抽灌模式下水源热泵系统运行能耗最小的数学模型,利用遗传算法求解数学模型以实现抽灌量的优化配置。研究表明:水源热泵系统抽灌井施工完毕后,可根据水文地质条件及管道布局情况来优化配置其抽灌量,以实现低能耗运行;遗传算法具有适应性强、全局优化能力高和参数拾取方便的优点,可用于水源热泵系统抽灌量的合理调配;优化确定的以井5为抽水井、井1和井2及井4为日常回灌井、井3为备用回灌井,井5抽水量为90 m^3/h,井1、井2、井4回灌量分别为42.5 m^3/h、33.4 m^3/h、14.1 m^3/h,为生产中科学快速调度抽灌模式提供了依据。

The design of pumping and recharging wells is one of the key issues in designing a watersource heat-pump system. However,the current allocation of pumping and recharging rates is still based on experience,which leads to higher operating cost. In view of these problems,this study undertook to find a solution based on pumping and recharging test data, building an optimization model of minimum pump energy consumption under different pumping and irrigation modes of a water-source heat pump system,and obtaining an optimized configuration of the pumping-recharging rates using a genetic algorithm.The result shows that after the construction of pumping-recharging wells in water-source heat-pump system,the pumping-recharging quantity can be optimized according to the hydrogeological conditions and pipeline layout to achieve low energy consumption operation;the genetic algorithm has the advantages of strong adaptability,high global optimization ability and convenient parameter picking,which can be used for rational allocation of pumping-recharging rates in water-source heat-pump system. Then taking well 5 as pumping well,well 1,well 2 and well 4 as daily recharging well,and well 3 as standby recharge well. The pumping rates of well 5 is 90 m^3/h,and the recharging rates of well 1,well 2 and well 4 are 42.5 m^3/h,33.4 m^3/h and 14.1 m^3/h,which provides a basis for scientific and rapid dispatch of pumping-recharging mode in production.