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| Predictable Scheduling Optimization Control of City Sewage Discharge System Based on Data |
| Xia Yingying, Wang Xionghai |
| Zhejiang University Hangzhou 310027 China |
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Abstract 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.
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Received: 20 May 2010
Published: 10 March 2014
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2011, Vol. 26 
