Short-term prediction of influent flow rate and ammonia concentration in municipal wastewater treatment plants

doi:10.1007/s11783-013-0598-9

Front Envir Sci Eng

2014, Vol. 8

Issue (1) : 128-136 https://doi.org/10.1007/s11783-013-0598-9

RESEARCH ARTICLE

Short-term prediction of influent flow rate and ammonia concentration in municipal wastewater treatment plants

Shuai MA¹, Siyu ZENG¹, Xin DONG¹, Jining CHEN¹(

), Gustaf OLSSON²

1. State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; 2. Department of Industrial Electrical Engineering and Automation, Lund University, Lund SE-22100, Sweden

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Abstract

The prediction of the influent load is of great importance for the improvement of the control system to a large wastewater treatment plant. A systematic data analysis method is presented in this paper in order to estimate and predict the periodicity of the influent flow rate and ammonia (NH₃) concentrations: 1) data filtering using wavelet decomposition and reconstruction; 2) typical cycle identification using power spectrum density analysis; 3) fitting and prediction model establishment based on an autoregressive model. To give meaningful information for feedforward control systems, predictions in different time scales are tested to compare the corresponding predicting accuracy. Considering the influence of the rainfalls, a linear fitting model is derived to estimate the relationship between flow rate trend and rain events. Measurements used to support coefficient fitting and model testing are acquired from two municipal wastewater treatment plants in China. The results show that 1) for both of the two plants, the periodicity affects the flow rate and NH₃ concentrations in different cycles (especially cycles longer than 1 day); 2) when the flow rate and NH₃ concentrations present an obvious periodicity, the decreasing of prediction accuracy is not distinct with increasing of the prediction time scales; 3) the periodicity influence is larger than rainfalls; 4) the rainfalls will make the periodicity of flow rate less obvious in intensive rainy periods.

Keywords influent load prediction wavelet de-noising power spectrum density autoregressive model time-frequency analysis wastewater treatment

Corresponding Author(s): CHEN Jining,Email:jchen1@tsinghua.edu.cn

Issue Date: 01 February 2014

Cite this article:

Shuai MA,Siyu ZENG,Xin DONG, et al. Short-term prediction of influent flow rate and ammonia concentration in municipal wastewater treatment plants[J]. Front Envir Sci Eng, 2014, 8(1): 128-136.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-013-0598-9
https://academic.hep.com.cn/fese/EN/Y2014/V8/I1/128

Fig.1 PSD curve (a) and contour map of spectrogram time-frequency distribution (b) of the flow rate of XHM. The peak of PSD at 0.041 corresponds to daily (24 h) cycles, while the peak at 0.082 corresponds to a 12 h cycle. The two cycles of 12 and 24 h are clearly indicated in the contour map, while the gaps in the two cycles of the contour maps are caused by the intensive rainfalls, which destroyed the periodicity, during days 40 to 61 (176th to 197th day of the entire year)

Tab.1 Coefficients for different prediction horizons for the influent flow rates and the ammonia concentrations in the XHM and KM plants

Fig.2 Relative error of influent flow rate prediction of XHM plant for different prediction horizons

Fig.3 PSD curve (a) and predicted data of the flow rate (b) of Kunming plant #5. The largest peak of PSD appears at the frequency of 0.03 d, corresponding to the cycle of 33 days. The second peak appears at 0.018 d (55 days). Smaller peaks appear at the frequencies of 0.044 d (23 days) and 0.094 d (11 days)

Fig.4 PSD-frequency curve of NH concentrations in the XHM plant. 455 day data (a) are based on daily measurement, while 2 week data (b) are sampled once every hour

Fig.5 Predicted results of NH concentration of XHM plant (a) and Kunming plant #5 (b)

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