چکیده مقاله
The high energy demand of wastewater treatment plants WWTPs , particularly for aeration, poses significant operational and economic challenges This study presents a comprehensive machine learning approach for predicting energy consumption in aeration basins of extended aeration wastewater treatment plants Using 10 years of daily operational data, we developed Random Forest and XGBoost models to identify key parameters influencing energy usage The analysis revealed that MLSS Mixed Liquor Suspended Solids is the most significant predictor, accounting for 39 2% of energy consumption variation, followed by COD 27 7% and inflow rate 13 7% The models achieved impressive prediction accuracy with R² scores of 0 65 Random Forest and 0 68 XGBoost , demonstrating the potential for substantial energy optimization through data driven operational adjustments This study concludes that data driven models coupled with feature importance analysis provide a powerful framework for plant operators to identify key leverage points for targeted energy optimization, leading to more cost effective and sustainable wastewater treatment operations at the Eyvan plant and similar facilities
کلیدواژهها
نویسندگان
Fastemeh Houshmand
Department of Engineering Sciences, Technical and vocational University TVU ,Tehran, Iran
Zahra Moafi
Department of Engineering Sciences, Technical and vocational University TVU ,Tehran, Iran
Sara Houshmand
Department of Mechanical Engineering, University of Alberta, Edmonton, AB T۶G ۱H۹, Canada
شیوه ارجاع
Houshmand, Fastemeh and Moafi, Zahra and Houshmand, Sara,1404,Predictive Modeling and Feature Importance Analysis for Aeration Energy Optimization in Extended Aeration Wastewater Treatment Plants: Case Study Eyvan Wastewater Treatment Plant,The Third National Conference on Water Quality Management and the Fifth National Conference on Water Consumption Management with a Waste Reduction and Recycling Approach,Tehran
ارائهشده در
مجموعه مقالات سومین همایش ملی مدیریت کیفیت آب و پنجمین همایش ملی مدیریت مصرف آب با رویکرد کاهش هدررفت و بازیافت11 آذر 1404 · تهران