Modelling and optimization of energy consumption in the activated sludge biological aeration unit
The biological aeration unit consumes the highest energy (67.3%) in wastewater treatment compared with physical (18.8%) and chemical (13.9%) treatment processes. The high energy consumption is caused by the supply of oxygen using air pumps/blowers and temperature that controls microorganisms' g...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IWA Publishing
2023-01-01
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| Series: | Water Practice and Technology |
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| Online Access: | http://wpt.iwaponline.com/content/18/1/140 |
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| author | Mpho Muloiwa M. O. Dinka Stephen Nyende-Byakika |
| author_facet | Mpho Muloiwa M. O. Dinka Stephen Nyende-Byakika |
| author_sort | Mpho Muloiwa |
| collection | DOAJ |
| description | The biological aeration unit consumes the highest energy (67.3%) in wastewater treatment compared with physical (18.8%) and chemical (13.9%) treatment processes. The high energy consumption is caused by the supply of oxygen using air pumps/blowers and temperature that controls microorganisms' growth. The purpose of this study was to model and optimize energy consumption in the biological aeration unit. The multilayer perceptron (MLP) artificial neural network (ANN) algorithm was used to model energy consumption. The particle swarm optimization (PSO) algorithm was used to optimize the energy consumption model. Sensitivity analysis was performed to determine the percentage contribution of input variables towards energy consumption. The MLP ANN algorithm modelled energy consumption successfully and produced R², RMSE, and MSE of 0.89, 0.0265, and 0.00070, respectively, during the testing phase. The PSO algorithm optimized energy consumption successfully and produced a global solution of 0.993 kWh/m³. The percentage reduction between the lowest measured and optimized energy consumption was 38.4%. Aeration period (81%) and temperature (10.7%) contributed the highest towards energy consumption. In conclusion, temperature played a significant role in energy consumption compared with airflow rate (4.2%). When the temperature is conducive to allowing the growth of microorganisms, the removal of COD and ammonia will be rapid resulting in low energy consumption.
HIGHLIGHTS
Temperature is the driver of energy consumption compared with airflow rate in the biological aeration unit.;
Temperature contributes 6.5% more than airflow rate towards energy consumption in the biological aeration unit.;
Biological aeration unit should be operated at high temperatures (35 °C) in order to achieve low energy consumption.;
A total of 38.4% reduction in energy consumption was achieved using the PSO algorithm.; |
| first_indexed | 2024-04-10T09:35:49Z |
| format | Article |
| id | doaj.art-d2ef5bc8d0cc4140890408528bfa6ca4 |
| institution | Directory Open Access Journal |
| issn | 1751-231X |
| language | English |
| last_indexed | 2024-04-10T09:35:49Z |
| publishDate | 2023-01-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Water Practice and Technology |
| spelling | doaj.art-d2ef5bc8d0cc4140890408528bfa6ca42023-02-17T17:33:22ZengIWA PublishingWater Practice and Technology1751-231X2023-01-0118114015810.2166/wpt.2022.154154Modelling and optimization of energy consumption in the activated sludge biological aeration unitMpho Muloiwa0M. O. Dinka1Stephen Nyende-Byakika2 Department of Civil Engineering, Tshwane University of Technology, Private Bag X680 Pretoria 0001, Staatsartillerie Road, Pretoria West, South Africa Department of Civil Engineering Science, University of Johannesburg, Auckland Park Campus 2006, Box 524, Johannesburg, South Africa Department of Civil Engineering, Tshwane University of Technology, Private Bag X680 Pretoria 0001, Staatsartillerie Road, Pretoria West, South Africa The biological aeration unit consumes the highest energy (67.3%) in wastewater treatment compared with physical (18.8%) and chemical (13.9%) treatment processes. The high energy consumption is caused by the supply of oxygen using air pumps/blowers and temperature that controls microorganisms' growth. The purpose of this study was to model and optimize energy consumption in the biological aeration unit. The multilayer perceptron (MLP) artificial neural network (ANN) algorithm was used to model energy consumption. The particle swarm optimization (PSO) algorithm was used to optimize the energy consumption model. Sensitivity analysis was performed to determine the percentage contribution of input variables towards energy consumption. The MLP ANN algorithm modelled energy consumption successfully and produced R², RMSE, and MSE of 0.89, 0.0265, and 0.00070, respectively, during the testing phase. The PSO algorithm optimized energy consumption successfully and produced a global solution of 0.993 kWh/m³. The percentage reduction between the lowest measured and optimized energy consumption was 38.4%. Aeration period (81%) and temperature (10.7%) contributed the highest towards energy consumption. In conclusion, temperature played a significant role in energy consumption compared with airflow rate (4.2%). When the temperature is conducive to allowing the growth of microorganisms, the removal of COD and ammonia will be rapid resulting in low energy consumption. HIGHLIGHTS Temperature is the driver of energy consumption compared with airflow rate in the biological aeration unit.; Temperature contributes 6.5% more than airflow rate towards energy consumption in the biological aeration unit.; Biological aeration unit should be operated at high temperatures (35 °C) in order to achieve low energy consumption.; A total of 38.4% reduction in energy consumption was achieved using the PSO algorithm.;http://wpt.iwaponline.com/content/18/1/140artificial neural networkbiological aeration unitenergy consumptionmodellingparticle swarm optimizationwastewater treatment plant |
| spellingShingle | Mpho Muloiwa M. O. Dinka Stephen Nyende-Byakika Modelling and optimization of energy consumption in the activated sludge biological aeration unit Water Practice and Technology artificial neural network biological aeration unit energy consumption modelling particle swarm optimization wastewater treatment plant |
| title | Modelling and optimization of energy consumption in the activated sludge biological aeration unit |
| title_full | Modelling and optimization of energy consumption in the activated sludge biological aeration unit |
| title_fullStr | Modelling and optimization of energy consumption in the activated sludge biological aeration unit |
| title_full_unstemmed | Modelling and optimization of energy consumption in the activated sludge biological aeration unit |
| title_short | Modelling and optimization of energy consumption in the activated sludge biological aeration unit |
| title_sort | modelling and optimization of energy consumption in the activated sludge biological aeration unit |
| topic | artificial neural network biological aeration unit energy consumption modelling particle swarm optimization wastewater treatment plant |
| url | http://wpt.iwaponline.com/content/18/1/140 |
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