多源环状注水系统泵站运行方案与管网同步优化

Simultaneous optimization of pump station operation scheme and pipe network in multi-source and looped water injection system

为了最大限度地提高注水系统运行效率,对泵站运行方案与管网同时进行优化.针对多源环状注水系统,以泵的开停状态、流量和管线的连接状态、管径为优化设计变量,以运行能耗和管网投资费用最小为优化目标,考虑流量、压力、环状管网等各类约束条件,建立了多源环状注水系统运行方案与管网同步优化数学模型.针对该同步优化问题的特点,设计了双重广义染色体编码遗传算法对模型求解.泵的编码中,第1行采用二进制编码表示泵的开停状态,第2行采用实数编码表示泵的流量;管线的编码中,第1行采用二进制编码表示管线的连接状态,第2行采用整数编码表示管线的管径.实现了对各优化变量的精确表达,设计了与问题相适应的初始解产生及编码交叉、变异方法,避免或减少了不可行解的产生.并对实例进行优化设计,同步优化与仅进行管网优化对比,运行能耗降低了4.66%,管网投资费用降低了1.73%,表明同步优化的节能效果明显.

The simultaneous optimization of pump station operation scheme and pipe network can improve the system operating efficiency furthest. Aiming at the multi-source and looped water injection system,a mathematical model for simultaneous optimization of operation scheme and pipe network is established. In which the start-up and stop status,displacement of pumps,and the connection status,diameter of pipelines were taken as design variables. The operating energy consumption and investment were served as objective function,and the constraint conditions of displacement,pressure,looped pipe network were considered. Taking the features of the simultaneous optimization problem,a dual generalized chromosome coding was proposed to improve the existing genetic algorithm,and then was appliedto solve the mathematical mode1. In the pump coding,the binary coding was adopted in the first row to indicate the start-up and stop status of pump,the real coding was adopted in the second row to present the displacement of pump. In the pipeline coding,the binary coding was adopted in the first row to indicate the connection status of pipeline,the integer coding was adopted in the second row to present the diameter of pipelines. Thus,an exact description of the optimization variables is realized. The method of initial solutions creating and many crossover and mutation methods that adapted to the optimize problem were designed,a part of constraint conditions were satisfied,so the number of infeasible solutions was reduced. An example was optimized by using the algorithm proposed,the results of simultaneous optimization compared with the results of pipe network optimization,the operating energy consumption was reduced by 4. 66%,the investment of pipe network is reduced by 1. 73%,showing simultaneous optimization has a remarkable energy saving effect.