Optimizing Electric Power Consumption in a Climate-changing Environment: A Study of the Conventional Activated Sludge Process

Municipalities’ most commonly applied wastewater treatment technology is the conventional activated sludge process (ASP). The challenge is that the ASP consumes high levels of electric power, which results in high electric energy consumption. The power consumption can be attributed to the air blowers/pumps that function non-stop to supply oxygen for the survival of microorganisms in the ASP. This study proposes optimizing electric pump power consumption in the ASP. Multilayer perceptron (MLP) Artificial Neural Network (ANN) algorithm was used to develop the pump power consumption optimization model. Particle Swarm Optimization (PSO) algorithm was applied to optimize the electric pump power consumption. The PSO algorithm output an optimal solution of 0.057396 kW after performing 1000 iterations. The percentage difference between the measured electric pump power consumption (0.087 kW) in the ASP and the optimized electric pump power consumption (0.057396 kW) was 34.03%. This significant difference implies that the PSO algorithm performance was satisfactory in optimizing the electric pump power consumption.

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Publication Details

Journal
E3S Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/e3sconf/202564703003
Primary Topic
Water-Energy-Food Nexus Studies
Type
article
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article

Optimizing Electric Power Consumption in a Climate-changing Environment: A Study of the Conventional Activated Sludge Process

Mpho Muloiwa, Dunisani Thomas Chabalala, Lusiwe Zamokuhle Maduna, Julius Musyoka Ndambuki
E3S Web of Conferences
Water-Energy-Food Nexus Studies
article

Optimizing Electric Power Consumption in a Climate-changing Environment: A Study of the Conventional Activated Sludge Process

Mpho Muloiwa, Dunisani Thomas Chabalala, Lusiwe Zamokuhle Maduna, Julius Musyoka Ndambuki
article en

Abstract

Municipalities’ most commonly applied wastewater treatment technology is the conventional activated sludge process (ASP). The challenge is that the ASP consumes high levels of electric power, which results in high electric energy consumption. The power consumption can be attributed to the air blowers/pumps that function non-stop to supply oxygen for the survival of microorganisms in the ASP. This study proposes optimizing electric pump power consumption in the ASP. Multilayer perceptron (MLP) Artificial Neural Network (ANN) algorithm was used to develop the pump power consumption optimization model. Particle Swarm Optimization (PSO) algorithm was applied to optimize the electric pump power consumption. The PSO algorithm output an optimal solution of 0.057396 kW after performing 1000 iterations. The percentage difference between the measured electric pump power consumption (0.087 kW) in the ASP and the optimized electric pump power consumption (0.057396 kW) was 34.03%. This significant difference implies that the PSO algorithm performance was satisfactory in optimizing the electric pump power consumption.

E3S Web of ConferencesVol. 647
Tshwane University of Technology (ZA)
Openalex Percentile: Top 79%
Water-Energy-Food Nexus Studies
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