Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutr...Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective 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 clustering 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 kW·h·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 O_(2)·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.展开更多
为解决区域综合能源系统中多主体利益冲突、用户侧分布式储能投资成本高昂、容量利用不均以及碳排放量较高等问题,提出一种基于云储能服务商-综合能源系统运行商(integrated energy system operators,IESO)-负荷聚合商(load aggregators...为解决区域综合能源系统中多主体利益冲突、用户侧分布式储能投资成本高昂、容量利用不均以及碳排放量较高等问题,提出一种基于云储能服务商-综合能源系统运行商(integrated energy system operators,IESO)-负荷聚合商(load aggregators,LA)联盟三层博弈的区域综合能源系统低碳运行策略。首先,构建租赁云储能的IESO与LA的能源交易框架。其次,考虑到多个理性主体对盈利最大化的诉求,建立综合能源系统三层博弈模型。第一层为以IESO为主导者、LA联盟为伴随者的主从博弈;第二层为以云储能服务商为供给者、IESO为接收者的主从博弈;第三层是LA联盟成员之间的合作博弈,并采取非对称纳什议价法分配收益。最后,利用二分法、KKT条件结合交替方向乘子法(alternating direction multiplier method,ADMM)对该模型进行求解。仿真结果表明,该策略不仅能够促进系统低碳运行,而且能够满足各主体的经济性需求。展开更多
基金the financial support from the National Key Research and Development Program of China(2019YFD1100204)the National Natural Science Foundation of China(52091545)+2 种基金the State Key Laboratory of Urban Water Resource and Environment,Harbin Institute of Technology(2021TS03)The Important Projects in the Scientific Innovation of CECEP(cecep-zdkj-2020-009)the Open Project of Key Laboratory of Environmental Biotechnology,Chinese Academy of Sciences(kf2018002).
文摘Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective 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 clustering 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 kW·h·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 O_(2)·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.
文摘为解决区域综合能源系统中多主体利益冲突、用户侧分布式储能投资成本高昂、容量利用不均以及碳排放量较高等问题,提出一种基于云储能服务商-综合能源系统运行商(integrated energy system operators,IESO)-负荷聚合商(load aggregators,LA)联盟三层博弈的区域综合能源系统低碳运行策略。首先,构建租赁云储能的IESO与LA的能源交易框架。其次,考虑到多个理性主体对盈利最大化的诉求,建立综合能源系统三层博弈模型。第一层为以IESO为主导者、LA联盟为伴随者的主从博弈;第二层为以云储能服务商为供给者、IESO为接收者的主从博弈;第三层是LA联盟成员之间的合作博弈,并采取非对称纳什议价法分配收益。最后,利用二分法、KKT条件结合交替方向乘子法(alternating direction multiplier method,ADMM)对该模型进行求解。仿真结果表明,该策略不仅能够促进系统低碳运行,而且能够满足各主体的经济性需求。
