首页|Cloud-Model-Based Feature Engineering to Analyze the Energy-Water Nexus of a Full-Scale Wastewater Treatment Plant

Cloud-Model-Based Feature Engineering to Analyze the Energy-Water Nexus of a Full-Scale Wastewater Treatment Plant

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Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the per-spective of carbon neutrality.However,water-energy nexus analysis and models for WWTPs have rarely been reported to date.In this study,a cloud-model-based energy consumption analysis(CMECA)of a WWTP was conducted to explore the relationship between influent and energy consumption by cluster-ing its influent's parameters.The principal component analysis(PCA)and K-means clustering were applied to classify the influent condition using water quality and volume data.The energy consumption of the WWTP is divided into five standard evaluation levels,and its cloud digital characteristics(CDCs)were extracted according to bilateral constraints and golden ratio methods.Our results showed that the energy consumption distribution gradually dispersed and deviated from the Gaussian distribution with decreased water concentration and quantity.The days with high energy efficiency were extracted via the clustering method from the influent category of excessive energy consumption,represented by a compact-type energy consumption distribution curve to identify the influent conditions that affect the steady distribution of energy consumption.The local WWTP has high energy consumption with 0.3613 kWh·m-3 despite low influent concentration and volumes,across four consumption levels from low(Ⅰ)to relatively high(Ⅳ),showing an unsatisfactory operation and management level.The average oxygenation capacity,internal reflux ratio,and external reflux ratio during high energy efficiency days recognized by further clustering were obtained(0.2924-0.3703 kg O2·m-3,1.9576-2.4787,and 0.6603-0.8361,respectively),which could be used as a guide for the days with low energy efficiency.Consequently,this study offers a water-energy nexus analysis method to identify influent conditions with operational management anomalies and can be used as an empirical reference for the optimized operation of WWTPs.

Wastewater treatment plantsCloud-model theoryData miningPrincipal component analysisK-means clusteringCloud-model-based energy consumption analysis

Shan-Shan Yang、Xin-Lei Yu、Chen-Hao Cui、Jie Ding、Lei He、Wei Dai、Han-Jun Sun、Shun-Wen Bai、Yu Tao、Ji-Wei Pang、Nan-Qi Ren

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State Key Laboratory of Urban Water Resource and Environment,Harbin Institute of Technology,Harbin 150000,China

Key Laboratory of Environmental Biotechnology,Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences,Beijing 100085,China

School of Civil and Environmental Engineering,Harbin Institute of Technology(Shenzhen),Shenzhen 518055,China

China Energy Conservation and Environmental Protection Group,Beijing 100089,China

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National Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaState Key Laboratory of Urban Water Resource and Environment,Harbin Institute of TechnologyImportant Projects in the Scientific Innovation of CECEPOpen Project of Key Laboratory of Environmental Biotechnology,Chinese Academy of Sciences

2019YFD1100204520915452021TS03cecepzdkj-2020-009kf2018002

2024

10.1016/j.eng.2022.02.011

工程(英文)

工程(英文)

CSTPCDEI
ISSN：2095-8099
年,卷(期)：2024.36(5)
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