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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
N. A. Wahab
Universiti Teknologi Malaysia
Electrical & Electronics Engineering

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Decentralized proportional-integral control with carbon addition for wastewater treatment plant M. H. Husin; M. F. Rahmat; N. A. Wahab
Bulletin of Electrical Engineering and Informatics Vol 9, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i6.2170

Abstract

Two main challenges in activated sludge wastewater treatment plant (WWTP) are cost and effluent quality, which has forced the wastewater treatment operator to find an alternative to improve the existing control strategy. The Benchmark Simulation Model No. 1 (BSM1) is applied as operational settings for this study. In BSM1, the standard control variables are the internal recirculation flow rate and the oxygen transfer rate. To improve the existing control strategy of BSM1, three alternative control handles are proposed, which are the individual aeration intensity control, carbon source addition and combination of both. The effect of each control handles in terms of the effluent violation, effluent quality, aeration cost, and total operational cost index are examined. The simulation result has shown that the individual control of aeration intensity improved the effluent quality index, and reduced the aeration, pumping, and total operational cost index when compared to the standard BSM1 control handle. Nonetheless, the addition of a fixed external carbon source has shown a significantly improved effluent quality with a lower number of total nitrogen violations as compared to the standard BSM1 control handles. Thus, the proposed control handles may be beneficial if applied in a real WWTP.
Estimation of Turbidity in Water Treatment Plant using Hammerstein-Wiener and Neural Network Technique M. S Gaya; L. A. Yusuf; Mamunu Mustapha; Bashir Muhammad; Ashiru Sani; Aminu Tijjani Aminu Tijjani; N. A. Wahab; M. T.M. Khairi
Indonesian Journal of Electrical Engineering and Computer Science Vol 5, No 3: March 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v5.i3.pp666-672

Abstract

Turbidity is a measure of water quality. Excessive turbidity poses a threat to health and causes pollution. Most of the available mathematical models of water treatment plants do not capture turbidity. A reliable model is essential for effective removal of turbidity in the water treatment plant. This paper presents a comparison of Hammerstein Wiener and neural network technique for estimating of turbidity in water treatment plant. The models were validated using an experimental data from Tamburawa water treatment plant in Kano, Nigeria. Simulation results demonstrated that the neural network model outperformed the Hammerstein-Wiener model in estimating the turbidity. The neural network model may serve as a valuable tool for predicting the turbidity in the plant.
Co-Authors Aminu Tijjani Aminu Tijjani Ashiru Sani Bashir Muhammad L. A. Yusuf M. F. Rahmat M. H. Husin M. S Gaya M. T.M. Khairi Mamunu Mustapha