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

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.

Energy consumption,air quality,and air pollution spatial spillover effects:evidence from the Yangtze River Delta of China

Based on analysis of the theoretical impact of energy consumption on air quality,taking 20 heavily polluted cities in the Yangtze River Delta of China as the object,we construct a Spatial Dubin Model,and estimate the effect of energy consumption on air quality and the spatial spillover effects of air pollution.We come to the following conclusions:First,the regional air quality has significant spatial dependence and spatial heterogeneity.Second,under three kinds of spatial associated mode,energy consumption has a negative impact on air quality,and the air pollution arising from energy consumption has a negative intra-regional spillover effect.The effect is strongest under the spatial distance weight matrix,followed by the economic distance,and the adjacent spatial weight matrix,which are−0.7926,−0.4547,and−0.4539,respectively.Third,in addition,under the adjacent space and economic distance space matrix,energy consumption has a significant negative effect on air quality,and the inter-regional spillover effects are−0.1513 and−2.5736,respectively.Meanwhile,considering spatial distance and economic development,the inter-regional spillover effect is much larger than is the intra-regional spillover effect.In general,the total spillover effect is at−0.6053 and−3.0284.

Modeling of Energy Consumption and Effluent Quality Using Density Peaks-based Adaptive Fuzzy Neural Network

Modeling of energy consumption(EC) and effluent quality(EQ) are very essential problems that need to be solved for the multiobjective optimal control in the wastewater treatment process(WWTP). To address this issue, a density peaks-based adaptive fuzzy neural network(DP-AFNN) is proposed in this study. To obtain suitable fuzzy rules, a DP-based clustering method is applied to fit the cluster centers to process nonlinearity.The parameters of the extracted fuzzy rules are fine-tuned based on the improved Levenberg-Marquardt algorithm during the training process. Furthermore, the analysis of convergence is performed to guarantee the successful application of the DPAFNN. Finally, the proposed DP-AFNN is utilized to develop the models of EC and EQ in the WWTP. The experimental results show that the proposed DP-AFNN can achieve fast convergence speed and high prediction accuracy in comparison with some existing methods.

Energy consumption of electrooxidation systems with boron-doped diamond electrodes in the pulse current mode

A pulse current technique was conducted in a boron-doped diamond （BDD） anode system for electrochemical waste- water treatment. Due to the strong generation and weak absorption of hydroxyl radicals on the diamond surface, the BDD elec- trode possesses a powerful capability of electrochemical oxidation of organic compounds, especially in the pulse current mode. The influences of pulse current parameters such as current density, pulse duty cycle, and frequency were investigated in terms of chemical oxygen demand （COD） removal, average current efficiency, and specific energy consumption. The results demon- strated that the relatively high COD removal and low specific energy consumption were obtained simultaneously only if the current density or pulse duty cycle was adjusted to a reasonable value. Increasing the frequency slightly enhanced the COD re- moval and average current efficiency. A pulse-BDD anode system showed a stronger energy saving ability than a constant-BDD anode system when the electrochemical oxidation of phenol of the two systems was compared. The results prove that the pulse current technique is more cost-effective and more suitable for a BDD anode system for real wastewater treatment. A kinetic analysis was presented to explain the above results.

Scheduling an Energy-Aware Parallel Machine System with Deteriorating and Learning Effects Considering Multiple Optimization Objectives and Stochastic Processing Time

Currently,energy conservation draws wide attention in industrial manufacturing systems.In recent years,many studies have aimed at saving energy consumption in the process of manufacturing and scheduling is regarded as an effective approach.This paper puts forwards a multi-objective stochastic parallel machine scheduling problem with the consideration of deteriorating and learning effects.In it,the real processing time of jobs is calculated by using their processing speed and normal processing time.To describe this problem in a mathematical way,amultiobjective stochastic programming model aiming at realizing makespan and energy consumption minimization is formulated.Furthermore,we develop a multi-objective multi-verse optimization combined with a stochastic simulation method to deal with it.In this approach,the multi-verse optimization is adopted to find favorable solutions from the huge solution domain,while the stochastic simulation method is employed to assess them.By conducting comparison experiments on test problems,it can be verified that the developed approach has better performance in coping with the considered problem,compared to two classic multi-objective evolutionary algorithms.

The effect of human capital on energy consumption:Evidence from an extended version of STIRPAT framework

Human capital is an important aspect of energy consumption,exerting crucial effects on economic growth,technological progress,and economic restructuring.This paper presents an in-depth investigation of the effect of human capital on energy consumption using an extended version of the Stochastic Impacts by Regression on Population,Affluence,and Technology framework.The estimated results using a panel dataset covering China’s 30 provincial regions during the period 1997-2018 and applying fixed effects with instrumental variables and the generalized method of moments indicated that an increase in human capital significantly drove energy consumption.A 1%increase in human capital increased energy consumption by approximately 0.3%.A two-step channel analysis to test scale,technical,and structural effects revealed that the positive effect of human capital on energy consumption is based primarily on the scale effect.However,highly educated human capital alleviates the energy pressure of this effect.In contrast to the scale effect,both the technical and structural effects of human capital reduced energy consumption,and this reduction is primarily correlated with enterprises’utility-oriented technological progress.Finally,we present strategic energy control policy implications related to human capital.

Digital finance and renewable energy consumption:evidence from China

While digital finance and renewable energy consumption(REC)are two timely issues,it remains unclear whether the former affects the latter,especially in developing economies.This paper examines the impact of digital finance on China’s REC between 2011 and 2018 and explores the underlying mechanisms.Results show that digital finance,along with its coverage breadth and usage depth,significantly improved REC in China and that digital finance in the area of credit has had the most significant impact.Additionally,the results show that loan scale and income level are the main mediation variables,through which digital finance affects REC.The findings also suggest that economic growth and technological progress have increased REC in China,while carbon dioxide emissions have had no meaningful effect on this consumption.The results further indicate that policymakers must pay close attention to the role of digital finance when formulating policies on REC.To promote REC and environmental sustainability,developing economies like China should strengthen the breadth and depth of digital finance development,focus on the influence channels of digital finance,and promote economic growth and technological progress.

Comparison of Energy Consumption of the 12 Classroom Typical School Buildings in Selected 4 City in Turkey

School is a special place where students come together to become productive individuals of society,acquire basic skills and acquire citizenship knowledge.With the introduction of the new education system(4+4+4)in Turkey in 2012-2013,some difficulties occurred in the spatial structure of the schools.After the new system,increasing number of students and decreasing student requirements have been tried to be solved with temporary solutions.At the same time that millions of students studying in primary schools all over Turkey have the same architectural feature as one type of architectural school project,regardless of the geographical and social situation began to be implemented in all parts of the city.Therefore,the increase in consumption varies depending on the geographical reasons where the type projects are implemented.Selected regions of the four thermal zones in Turkey for this research are provided below:1^st Thermal district in Antalya;2^nd Thermal district in Bursa;3^rd Thermal district in Elaz??;4^th Thermal district in Kars.The calculation of the energy consumption created by the above cities by means of BEP-TR program and comparing classes.

The Spatial Effect of Green Tax Policy on Energy Efficiency: Evidence from China

Based on the 30 provinces(cities,autonomous regions)panel data of China from 2007 to 2016,this paper establishes a Spatial Durbin Model to explore the spatial effects of green tax policies in broad and narrow sense on energy efficiency.The results show that:(1)China's provincial energy efficiency has significant spatial correlation.(2)the relationship between the intensity of narrow sense green tax policy and the energy efficiency of the surrounding areas is an inverted U-shaped curve.(3)the relationship between the generalized green tax policy intensity and the energy efficiency of the surrounding areas is a U-shaped curve.

电化学水处理技术降低循环水硬度的实验研究

使用电化学法处理某焦化企业实际循环水的实验,探究了循环水的硬度和碱度去除率随处理时间的变化情况。分析了电流密度、水力停留时间、极板间距等实验操作参数以及商用阻垢剂对电解效果和能耗的影响。结果表明:硬度和碱度去除率随处理时间呈现先上升后平稳的趋势,且碱度去除率总是高于硬度去除率;电流密度为70 A/m^(2)、水力停留时间为6 min、极板间距为3 cm时电解效果最佳,硬度和碱度去除率可达27%以上,单位能耗低至13 kWh/kg;商用阻垢剂对电解效果具有阻碍作用。

基于气泡雾化喷嘴的低能耗含油污水处理实验研究

微气泡气浮技术在低能耗下对含油污水的高效处理是目前的研究热点。利用气泡雾化喷嘴作为微气泡发生器,搭建了低能耗微气泡射流气浮处理含油污水的实验系统,系统研究了气液质量流量比(ALR)和工作压力(p)对微气泡群尺度分布特征和除油效果的影响,并计算了气泡雾化喷嘴的能耗。实验结果表明,利用气泡雾化喷嘴形成液下射流可以产生大量微气泡,其中尺度小于150μm的气泡数量占比在55%以上、小于600μm的气泡数量占比在98%以上;随着ALR的增加,微气泡数量整体呈现先增后减的变化趋势,最佳ALR=0.15;当p=0.2 MPa、ALR=0.15时,微气泡群的索特尔平均直径可降低至238μm,出水含油质量浓度为29.73 mg/L,微气泡射流气浮装置处理1 kg含油污水时能耗仅为6.53×10^(-4) kW·h,较溶气气浮能耗降低35%以上。

地铁活塞效应的节能综述研究

随着地铁行业的蓬勃发展,利用活塞风降低车站能耗成为目前研究的热点之一。首先整理与活塞效应相关的国内外文献,研究活塞效应的形成机理和特性,分析活塞效应对地铁环控系统产生的影响,发现两者间潜在的节能关系。其次分别对隧道活塞风与车站活塞风的利用策略进行综述研究,这些策略主要与通风井的相关设计、列车的行驶、站台门的选择以及门帘的安装等有关,合理地采用这些策略可以为车站降低能耗。最后提出了活塞风的利用原则,在活塞风满足乘客需求的情况下应当优先利用活塞通风,应根据风量、温湿度、二氧化碳浓度以及颗粒物浓度等参数评价活塞风是否满足需求。

Characteristic and correlation analysis of influent and energy consumption of wastewater treatment plants in Taihu Basin

The water quality and energy consumption of wastewater treatment plants(WWTPs)in Taihu Basin were evaluated on the basis of the operation data from 204 municipal WWTPs in the basin by using various statistical methods.The influent ammonia nitrogen(NH3-N)and total nitrogen(TN)of WWTPs in Taihu Basin showed normal distribution,whereas chemical oxygen demand(COD),biochemical oxygen demand(BOD5),suspended solid(SS),and total phosphorus(TP)showed positively skewed distribution.The influent BOD5/COD was 0.4%-0.6%,only 39.2%SS/BOD5 exceeded the standard by 36.3%,the average BOD5/TN was 3.82,and the probability of influent BOD5/TP>20 was 82.8%.The average energy consumption of WWTPs in Taihu Basin in 2017 was 0.458 kWh/m^3.The specific energy consumption of WWTPs with a daily treatment capacity of more than 5×10^4 m^3 in Taihu Basin was stable at 0.33 kWh/m^3.A power function relationship was observed between the reduction in COD and NH3-N and the specific energy consumption of pollutant reduction,and the higher the pollutant reduction is,the lower the specific energy consumption of pollutant reduction presents.In addition,a linear relationship existed between the energy consumption of WWTPs and the specific energy consumption of influent volume and pollutant reduction.Therefore,upgrading and operation with less energy consumption of WWTPs is imperative and the suggestions for Taihu WWTPs based on stringent discharge standard are proposed in detail.

产业数字化对碳生产力的影响研究

在数字经济时代背景下,借助产业数字化平衡经济发展与碳排放之间的关系,对“双碳”目标的实现具有重要意义。本文基于2013~2021年的省级面板数据构建产业数字化水平指标体系,测度后实证探讨产业数字化对碳生产力的影响及作用机制,并多维度比较分析其影响差异。研究发现:产业数字化的发展能够显著促进碳生产力的提升,但该促进作用具有异质性。在中、西部和数字技术水平低的地区,产业数字化对碳生产力的提升作用更强;相比农业和工业数字化,服务业数字化对碳生产力的提升作用更显著。进一步的机制分析表明,产业数字化可通过促进绿色技术创新和优化能源消费结构推动碳生产力提升。本文为深入推进产业数字化的发展以及充分发挥其在实现“双碳”目标中的关键作用提供了理论指导及政策启示。

大规模矿山的长距离胶带输送系统设计探讨

国外某大型矿山,生产规模达6 000万t/a,且地处内陆地区,矿体狭长,距离选矿工业场地较远、地势起伏陡峭、地形自然坡度大。该项目矿石运输兼具运量大、运距长、运输难度大等特点。对于大规模矿山而言,带式输送机因其具有运输量大、可长距离运输、自动化程度高、并能实现连续运输的优势,在矿山生产过程中发挥着极其重要的作用。与此同时,由于需要输送的距离越来越长,单段带式输送机很难满足矿山整体的散料输送要求,大运量、大角度接力运输的带式输送机系统得到普遍应用。本文借鉴现有矿山带式输送机接力系统的生产数据,以该大型矿山为背景,对带式输送机系统的可靠性和能耗情况进行分析计算,为类似项目提供参考。

炼化企业中低温多效蒸馏海水淡化技术的应用

低温多效蒸馏海水淡化技术是一种利用水平管降膜蒸发器或竖直管蒸发器串联并划分为若干效组,以一定量的输入蒸汽作为热源,经多次蒸发、冷凝,利用二次蒸汽潜热,得到多倍加热蒸汽量的蒸馏海水的海水淡化技术。该技术具有传热效率高、产品水质好、负荷调节范围大、工艺温度低等特点,可用于发电厂、化工厂、低温核反应堆等领域,是国际主流海水淡化技术之一。文章结合某炼化企业节能降耗中低温多效蒸馏海水淡化技术创新应用,分析了该技术应用经济效益,并对技术应用前景进行展望,以期促进该技术推广应用和创新发展。

超高层连体建筑——核心区域立体城市的切片探析

超高层建筑在近20年呈现出不可思议的蓬勃发展之势,也伴生了一定的质疑与讨论。本文从规模效应、中国城镇化现状与低能耗目标出发,探讨了超高层建筑、超高层建筑群的适用范围,并以近期的超高层连体建筑实践为例,分析说明了其在设计过程中面临的重点与难点,以对超高层连体建筑的设计提出一定的建议。

智慧水厂能耗监测评价与异常诊断管理平台研究

为提升污水处理厂水处理过程的运行能效,加速推进智慧水厂向节能化、数字化方向转型,设计了一种面向污水处理厂的能耗监测评价与异常诊断管理平台。平台基于建筑信息模型和能耗管理系统,通过采集污水处理厂运行数据与气象数据等信息,建立基于机器学习算法的动态监督能耗预测模型,实现厂区运行状况实时监测与评价。运维管理人员可依据平台生成的状态评价指数,进行厂区能源结构调整与异常用能识别与诊断。最后,以实际案例数据验证了平台各功能模块的可行性与有效性。分析结果表明,平台预警模块可以监测反馈96%的异常用能情况。

基于混合模型的脱硫废水旁路蒸发系统能耗特性

脱硫废水旁路蒸发系统抽取部分空预器入口热烟气会使锅炉效率降低、煤耗增加。为了实现对抽取热烟气造成能耗增加的精准预测,提出了一种机理模型与人工神经网络有机结合的混合模型预测方法。采集广东某660MW电厂的运行数据作为样本,以空气预热器进口的风温、空气的流量、抽取烟气量、抽取烟气温度、锅炉负荷以及给煤量6个参数作为输入,建立了用于预测经过空气预热器空气换热量的BP神经网络模型,对不同隐含层结构进行模拟计算,分析比较确定了网络的最优结构是6-9-1,最终模型的决定系数R^(2)是0.99478,预测模型的相对误差在1%附近波动,整体预测效果较好。在此基础上结合机理模型,针对机组负荷波动及抽取烟气量波动的典型工况进行了能耗预测,获得了旁路蒸发系统能耗的定性规律。