基于流量数据的城市污水协调调度排放控制系统  

Predictable Scheduling Optimization Control of City Sewage Discharge System Based on Data

作　　者：夏莹莹[1] 汪雄海[1] 

机构地区：[1]浙江大学电气工程学院杭州310027

出　　处：《电工技术学报》2011年第12期73-78,共6页Transactions of China Electrotechnical Society

基　　金：国家973重点基础研究发展规划(2009CB320602);浙江省重大专项(2006C11227)资助项目

摘　　要：针对当前城市污水排放系统缺乏全局调度功能,易引起泵站高能耗运行或污水外溢的问题,提出了一种基于历史流量数据的分时段分析,运用最小二乘支持向量机(Least Square-Support Vector Machine,LS-SVM)方法预测实时径流大小实现安全排放的新方法。通过建立分布式排水系统模型,采用基于流量数据的预测协调控制算法以实时跟踪流入量,并协调调度控制相应排出量,依据流量变化适时调整控制目标,从而使排水系统既能避免污水溢出又能达到高效节能。利用实际污水泵站采集的数据进行仿真实验及现场实时控制模拟实验,结果表明,该控制策略与系统有很好的流量变化判断、快速跟踪和执行流量调度的功能,可较好应对流量突变,达到保持扬程稳定、避免污水溢出的效果。The lack of global scheduling function in the current city sewage system easily causes high energy cost and sewage overflow problems. A new method is introduced based on the previous sub-time flow data analysis. The least square-support vector machine（LS-SVM） method is used to predict the size of real-time runoff in order to achieve safe discharge. By establishing global scheduling model, the flow predictable scheduling optimization control algorithm is adopted to track real-time inflows and control the emission. The control objectives are timely adjusted according to inflow changes so as to prevent sewage overflow and achieve energy efficiency. Actual collected data is used to do the simulation and field test is carried on. The results show that the control strategy and the system have good behaviors of determining and fast-tracking flow changes, implementing the flow scheduling function and dealing with flow mutation. The system is able to maintain a stable water level and the overflow is prevented effectively.

关 键 词：污水泵站 最小二乘支持向量机 历史数据 协调调度 流量预测 

分 类 号：TP273.1[自动化与计算机技术—检测技术与自动化装置]