Research on Smart Energy Monitoring and Management System Based on Digital Twin Technology

Smart energy monitoring and management system lays a foundation for the application and development of smart energy. However, in recent years, the work efficiency of smart energy development enterprises has generally been low, and there is an urgent need to improve the application efficiency, resilience and sustainability of smart energy monitoring and management system. Digital twin technology provides a data-centric solution to improve smart energy monitoring and management system, bringing an opportunity to transform passive infrastructure assets into data-centric systems. This paper expounds on the concept and key technologies of digital twin, and designs a smart energy monitoring and management system based on digital twin technology, which has dual significance for promoting the development of smart energy field and promoting the application of digital twin.

Design and Implementation of Monitoring System for Buildin~ Energy Consumption

This paper analyzes the shortcomings of ECOTECT simulation software, puts forward the real-time energy consumption monitoring software. According to the structural characteristics of large public buildings, the paper proposes the key technology development and the functions of the software platform, and provides RS485 communication code. The research results in this paper have some practical value on energy consumption of large-scale construction monitoring.

A Predictive Energy Management Strategies for Mining Dump Trucks

The plug-in hybrid vehicles(PHEV)technology can effectively address the issues of poor dynamics and higher energy consumption commonly found in traditional mining dump trucks.Meanwhile,plug-in hybrid electric trucks can achieve excellent fuel economy through efficient energy management strategies(EMS).Therefore,a series hybrid system is constructed based on a 100-ton mining dump truck in this paper.And inspired by the dynamic programming(DP)algorithm,a predictive equivalent consumption minimization strategy(P-ECMS)based on the DP optimization result is proposed.Based on the optimal control manifold and the SOC reference trajectory obtained by the DP algorithm,the P-ECMS strategy performs real-time stage parameter optimization to obtain the optimal equivalent factor(EF).Finally,applying the equivalent consumption minimization strategy(ECMS)realizes real-time control.The simulation results show that the equivalent fuel consumption of the P-ECMS strategy under the experimentally collected mining cycle conditions is 150.8 L/100 km,which is 10.9%less than that of the common CDCS strategy(169.3 L/100 km),and achieves 99.47%of the fuel saving effect of the DP strategy(150 L/100 km).

Development of Hybrid Propulsion System for Energy Management and Emission Reduction in Maritime Transport System

Given the strategic importance of energy and air pollution in the today world and due to the fact that the maritime transport system is one of the main sources of energy consumption and emissions in the environment, particularly contamination of water, so in recent years, fuel consumption and emissions reduction in the maritime transport industry has received considerable attention. Thus, in this paper, a new method is provided for typical boat hybridization, so by adding an electric motor and battery to boat power transmission system, dynamic performance will improve fuel consumption and emissions reduces. For this purpose, power transmission system elements are modelled and boat function is evaluated in real terms of movement by defining energy management strategy between power sources. The simulation results show that boat hybridization considerably reduces fuel consumption and emissions.

A FUNCTION NODE-BASED MULTIPLE PAIRWISE KEYS MANAGEMENT PROTOCOL FOR WIRELESS SENSOR NETWORKS AND ENERGY CONSUMPTION ANALYSIS

In this letter, a Function node-based Multiple Pairwise Keys Management (MPKMF) protocol for Wireless Sensor Networks (WSNs) is firstly designed, in which ordinary nodes and cluster head nodes are responsible for data collection and transmission, and function nodes are responsible for key management. There are more than one function nodes in the cluster consulting the key generation and other security decision-making. The function nodes are the second-class security center because of the characteristics of the distributed WSNs. Secondly, It is also described that the formation of function nodes and cluster heads under the control of the former, and five kinds of keys, i.e., individual key, pairwise keys, cluster key, management key, and group key. Finally, performance analysis and experiments show that, the protocol is superior in communication and energy consumption. The delay of establishing the cluster key meets the requirements, and a multiple pairwise key which adopts the coordinated security authentication scheme is provided.

An optimal energy management development for various configuration of plug-in and hybrid electric vehicle

Due to soaring fuel prices and environmental concerns, hybrid electric vehicle(HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV's fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. An optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.

Energy and Latency Optimization in Edge-Fog-Cloud Computing for the Internet of Medical Things

In this paper,the Internet ofMedical Things(IoMT)is identified as a promising solution,which integrates with the cloud computing environment to provide remote health monitoring solutions and improve the quality of service(QoS)in the healthcare sector.However,problems with the present architectural models such as those related to energy consumption,service latency,execution cost,and resource usage,remain a major concern for adopting IoMT applications.To address these problems,this work presents a four-tier IoMT-edge-fog-cloud architecture along with an optimization model formulated using Mixed Integer Linear Programming(MILP),with the objective of efficiently processing and placing IoMT applications in the edge-fog-cloud computing environment,while maintaining certain quality standards(e.g.,energy consumption,service latency,network utilization).A modeling environment is used to assess and validate the proposed model by considering different traffic loads and processing requirements.In comparison to the other existing models,the performance analysis of the proposed approach shows a maximum saving of 38%in energy consumption and a 73%reduction in service latency.The results also highlight that offloading the IoMT application to the edge and fog nodes compared to the cloud is highly dependent on the tradeoff between the network journey time saved vs.the extra power consumed by edge or fog resources.

Prospect of energy management system for large steel enterprise

The energy management system(EMS),which acts as the heart of the energy management center of a steel enterprise,is a large computer system focused on the concentrative monitor and control of the production and utilization of energy.Although Chinese steel industry was well developed in the latest decade, so far the levels of the comprehensive energy consumption per ton steel among Chinese steel enterprises are remarkably distinct,and the average value of the comprehensive energy consumption per ton steel of them has still been much higher than the value of those in developed countries.This bad situation,in the opinion of the author,partially results from the poor ability for most Chinese steel enterprises to manage the production and utilization of energy.National policies associated to energy-saving and ejection-decreasing call for steel enterprises to build the EMS;and more and more steel enterprises themselves also desire to achieve EMS projects so that they can optimize their energy production and utilization.Baosteel,the largest and most advanced steel enterprise in China,has got plenty of experience in the EMS due to its incessant practice for more than 30 years in the design,construction,application,and revampment of its EMS.In the present article,the features of an advanced EMS is described and discussed based on the design practice of the EMS of Baosteel Zhanjiang Project.An advanced EMS should be an optimized and integrated system,which possesses of the characteristic of high managing efficiency,enough openness in expansion,friendly interfaces, and simple structure.Furthermore,it could support many-sided applications,e.g.,energy related data mineing,energy network combination and co-supply,application of geographic information technology,and other technical researched on energy-saving aspects.It is known that some energy-related indexes of Baosteel have stood on a high level better than those of some worldwide famous steel enterprises.Moreover,it goes without saying that the indexes of Baosteel Zhanjiang will be better than those of present Baosteel.Therefore, one can easily expect that the new EMS of Baosteel Zhanjiang will be much more advanced,which will be more helpful to fulfil systematiclly saving of energy,to elevate the efficiency of energy utilization,to lower the comprehensive energy consumption per ton steel.

Assessment of Rainwater Harvesting Reticulation Systems to Reduce High Management Costs in Household Buildings

Rainwater harvesting?provides an important alternative source of water in household buildings which?increases water security in urban areas. However, high energy cost consumption by the rainwater harvesting systems results in higher management costs which may derail the investment viability of these systems in households. This prompted this study to establish ways through which the management cost of rainwater harvesting systems can be minimized in household buildings. A survey of 200 households from Greenspan, Komarock, Utawala, Kileleshwa and Runda in Nairobi?County was undertaken as?well?as?data?on?the?type?of?rainwater harvesting?systems, their operation and maintenance cost collected using observation checklists and questionnaires. The findings indicated that rainwater harvesting typologies 1, 2, 4 and 5 had their water pumped from first-level storage to the second-level storage then supplied to usage points by gravity. Whereas, typologies 3 and 6 had their water moved manually and by gravity respectively. On annual operation cost, 100% of households with typology 3 and 6 spent no money whereas, 100%, 75% and 70.6% with typology 4 and 5, 1 and 2 respectively spent Ksh. 1?-?5000. On annual maintenance cost, 100%, 93.7% and 77.8% of households with typology 5 and 6, 3 and 4 respectively spent Ksh. 1?-?5000 while 25% and 22.2% of households with typology 1 and 2 respectively spent Ksh. 5000?-?10,000. Advanced typology 6 with one-level storage point supplies rainwater to all parts of the household by gravity. This eliminates operation costs spent on energy consumption due to pumping of water,?thus minimizing overall management cost spent on rainwater harvesting systems in household buildings.

Platform Construction of Regional Energy Management Center

Based on the analysis of different requirements of energy management center construction and the data acquisition of various industries in wide area network, as well as the practices of real-lime online system, the paper puts forward the construction scheme of regional energy management center （REMC） which can achieve real time online monitoring of organizations＇ energy consumption via data collection, and also proposes the design idea of energy data acquisition based on national standards.

An Assessment for Energy Management in Retail Stores

Retail stores are responsible for large energy consumption, which requires more intensified action to improve energy efficiency. Effective energy management can improve energy efficiency in retail stores. However, it is a challenge to implement energy management in retail stores due to different stakeholders’ roles and diverse store features. Literally, technical and management aspects of energy management have received much attention in research. However, limited studies systemically investigate internal and external factors and stakeholders’ involvement in the energy management of retail buildings. With multi-cases in the Philippines, this paper examines the energy profiles in retail stores and develops an assessment for energy management in retail stores. The assessment includes store features, internal and external stakeholders, climate, electricity price and grid condition, energy consumption, and management. The assessment can assist retail stores to develop their energy management plans with their store profile.

浅议BIM技术、智能监测、绿色节能在建设工程项目管理中的应用

文章研究了BIM和智能监测的建设工程项目管理在绿色节能领域的创新应用。通过详细分析和探讨,揭示这一整合应用的核心原理和关键作用。通过综合BIM、智能监测和绿色节能理念,强调了这一整合应用对于实现可持续建筑和更高效能源利用的重要性,为未来建筑工程的发展提供了方向。

融合工况预测的燃料电池汽车里程自适应等效氢耗最小控制策略

为有效地提高插电式燃料电池汽车的经济性,实现燃料电池和动力电池的功率最优分配,考虑到行驶工况、电池荷电状态(State of charge,SOC)、等效因子与氢气消耗之间的密切联系,制定融合工况预测的里程自适应等效氢耗最小策略.通过基于误差反向传播的神经网络来实现未来短期车速的预测,分析未来车辆需求功率变化,同时借助全球定位系统规划一条通往目的地的路径,智能交通系统便可获取整个行程的交通流量信息,利用行驶里程和SOC实时动态修正等效消耗最小策略中的等效因子,实现能量管理策略的自适应性.基于MATLAB/Simulink软件,搭建整车仿真模型与传统的能量管理策略进行仿真对比验证.仿真结果表明,采用基于神经网络的工况预测算法能够较好地预测未来短期工况,其预测精度相较于马尔可夫方法提高12.5%,所提出的能量管理策略在城市道路循环工况(UDDS)下的氢气消耗比电量消耗维持(CD/CS)策略下降55.6%.硬件在环试验表明,在市郊循环工况(EUDC)下的氢气消耗比CD/CS策略下降26.8%,仿真验证结果表明了所提出的策略相比于CD/CS策略在氢气消耗方面的优越性能,并通过硬件在环实验验证了所提策略的有效性.

可穿戴生理信息监测的自供电系统研究

设计与制作了一种应用于可穿戴生理信息监测的自供电系统,利用压电-光电复合能量收集装置采集人体运动时足底的机械能和室内光能。复合能量收集装置以运动鞋为载体,设计了多种结构压电能量收集器固定在鞋底,光电能量收集器粘接在鞋面,收集到的能量存储在超级电容中,同时设计了一套能够定时、按需供电的能量管理控制电路,控制生理信息监测系统每隔20 min上电一次,并且测量结束即刻断电。经测试,光电能量收集装置在室内从早上7点至晚上7点的平均输出功率达到590μW,压电能量收集装置在1.2 m/s的匀速步行状态驱动下的平均输出功率达540μW以上,复合能量输出功率能够稳定在1.124 mW以上,即20 min产电1.349 J。对系统各单元进行数据采集测试以及功耗测试,得出系统一个工作周期耗能1.04 J。从能量收支平衡来看,利用运动机械能与光能复合供电的生理信息采集系统可实现自我维持定时工作,具有一定的应用参考价值。

考虑驾驶风格的混合动力汽车强化学习能量管理策略

为了提升混合动力汽车能量管理策略对不同风格驾驶员的适应性,基于深度强化学习和等效燃油消耗最小策略(equivalent consumption minimization strategy,ECMS),提出一种考虑驾驶风格的混合动力汽车能量管理策略。通过实车试验采集驾驶员行驶数据,基于采集数据进行驾驶员驾驶风格的聚类分析,建立驾驶风格识别模型;构建基于强化学习和ECMS的能量管理策略,将驾驶风格系数作为强化学习状态变量,利用多种驾驶风格的组合工况训练深度确定性策略梯度智能体,获取不同工况和驾驶风格下ECMS等效因子,采用ECMS求解最优发动机、电机转矩分配以及变速箱挡位;搭建硬件在环测试平台,并基于实际采集的不同驾驶员驾驶数据构建测试工况,验证所提出控制策略的有效性。研究结果表明,相较于基于规则策略、基于等效因子比例修正的自适应ECMS以及DRL-SAC策略,提出的考虑驾驶风格的强化学习能量管理策略使整车能量消耗分别降低16.35%、11.11%和7.56%,所提控制策略的有效性得到了验证。

综合管理模式对腹膜透析患者蛋白质能量消耗和高磷血症的影响

目的:探讨综合管理模式对腹膜透析(PD)患者蛋白质能量消耗(PEW)和高磷血症的影响。方法:选择2021年5~12月在安徽中医药大学第一附属医院肾内科接受治疗的60例PD患者为研究对象,随机分成干预组和对照组。对照组按常规护理方法进行管理。干预组由专科护师联合医、药、营养师运用综合管理模式进行干预3个月。观察对比两组患者干预前后相关知识掌握程度、蛋白质消耗、血磷、血钙、钙磷乘积、营养状况指标以及用药依从性。结果:实施综合管理模式干预后,干预组患者的相关知识掌握程度高于对照组(P<0.05),干预组的营养状况指标优于对照组(P<0.05),干预组的血磷、血钙、钙磷乘积指标优于对照组,干预组的高磷血症发生率低于对照组(P<0.05),干预组用药依从性高于对照组(P<0.05)。结论:综合管理模式可以减少PD患者PEW,降低高磷血症的发生率。

基于ARIMA模型的校园能耗监测与分析系统的设计与实现

设计了一种基于ARIMA模型(自回归移动平均)的校园能耗监测与分析系统,该系统主要由数据采集、数据存储、预测分析以及数据展示等功能模块组成.研究结果表明,该系统不仅可提升校园能源管理的自动化和智能化水平,而且还可有效提高校园能耗的预测精确度,且优于其他的能耗管理系统;因此,该系统可为提高校园能源使用效率提供良好支持.

基于充电行为电量规划的自适应能量管理策略

为提高插电式混合动力汽车(PHEV)的燃油经济性,以并联式PHEV为研究对象,考虑驾驶员充电行为,提出基于充电行为电量规划和等效燃油消耗最小策略(ECMS)的自适应能量管理策略。构建了包含不同类型工况的组合工况。根据驾驶员的充电行为特征(充电频率、充电上限、放电下限)进行充电行为分析,并进行4类工况电量消耗与燃油消耗ECMS策略下的离线仿真数据获取。根据驾驶员充电行为以及离线数据进行SOC轨迹的规划。结果表明:在电池SOC初始值分别为0.9、0.6时,提出的能量管理策略相较于基于电量消耗维持的等效燃油消耗策略,整车燃油经济性分别提升7.87%和13.1%。

基于数字孪生模型的数字化电网能耗自动监测系统研究

当前使用的数字化电网中,存在感知终端种类较多,对于传统的能耗自动监测系统来说获取的数据传输实时性不足,导致监测结果出现偏差,为此设计一种基于数字孪生模型的数字化电网能耗自动监测系统。系统主要从硬件和软件两方面进行设计:在硬件设计中,根据不同的应用层次,设计系统的总体架构。主要对硬件中的无线通信网络进行搭建,选择基于LoRa无线通信技术的RTU设备作为通信主体。设计LoRa无线开关电路,实现ZigBee设备之间的无线数据传输和交换;软件设计中,设计能耗数据采集主线程,分析数字孪生模型映射交互关系,基于数字孪生模型与实际运行工况之间的映射关系实现能耗指标实时监测。实验结果表明,与传统系统相比,设计得到的检测结果与实际的能耗情况更加相符。

“双碳”背景下热轧厂能源管理体系构建与实施

现阶段,中国能源体系和发展模式进入崭新阶段。热轧是钢铁企业的关键工序,热轧厂绿色、低碳、高效能源体系建设尤为重要。在“双碳”背景下,通过建立健全能源管理制度、构建“1+14”能源管理模式、建设多终端能源管理平台、产能提升助力高效节能、推行节能技术革新、建立精细化多重预警机制、强化体制机制保障等多措并举,成功构建实施了绿色、低碳、高效热轧厂能源管理体系,创新了管理理念,优化了管理架构,创新了管控模式,热轧厂综合工序能耗降幅明显,取得了显著的经济效益。