数字技术对工业节能提效具有加速作用，通过对产品绿色设计、生产工艺优化、能源管控、工序协同和资源调度等环节进行智慧管理与优化，实现能源利用效率提升。利用5G、工业互联网、大数据等新一代信息技术实现能量流、物质流等信息采集监控、智能分析、精细管理、系统优化，实现能源、资源、环境管理水平提升是工业领域数字化绿色化协同转型技术发展方向。
（一）电力物联网高速载波数据采集及供电系统优化技术，利用电力物联网高速载波技术对低压供电台区供用电数据、设备运行参数、环境状态等信息进行高频采集和实时监控分析，实现供电线路状态监控、用电负荷感知和调节。该技术适用于工业企业供配电系统运维管理及改造。技术提供单位为北京智芯微电子科技有限公司。在智慧供电系统监测及线损治理示范项目中，运用电力物联网高速载波数据采集及供电系统对居民用电数据进行采集和用电负荷进行精准调节，节能量为120万千瓦时/年。
（二）基于无线通信及多约束条件人工智能算法的公辅车间管理系统，通过可视化方式展示车间设备运行状况，通过大数据可视化技术、窄带恒压技术、多约束多参数控制算法和边缘计算技术等对设备进行智能控制，协助实现空压站运行提质稳压。该技术适用于工业企业空压站房等公辅车间运维管理及改造。技术提供单位为蘑菇物联技术（深圳）有限公司。在某汽车装配工厂空压站云智控改造项目中，空压站设备平均加载率由95%提高至98%，节能量为65万千瓦时/年。
（三）基于大数据的工业企业用能智能化管控技术，采用电气设备指纹提取、负荷用电数据预测等算法对工业企业用能信息数据进行监控、采集，在此基础上，基于人工智能和大数据技术进行智能分析及管理，以数字化手段协助用能管控与能效提升。该技术适用于工业园区整体能源管理及改造。技术提供单位为天津市普迅电力信息技术有限公司。在某营业厅节能改造项目中，系统综合能效比由1提升至2.50，节能率20%，节能量为3万千瓦时/年。
（四）基于工业互联网的设备运行智能化协同管理技术，依托物联网、人工智能、大数据、云计算等技术，通过工业互联网平台对设备运行状态和环境参数进行监控及分析，实现基于算法模型的自预警、自诊断及优化，降低设备能耗。该技术适用于工业企业设备运行管理及改造。技术提供单位为劲旅环境科技股份有限公司。在安徽省某设备运行智能化协同管理改造项目中，搭建预测性维护与智能运维平台，节能量为729万千瓦时/年。
（五）流程工业能源系统运行调度优化技术，以大数据库构建智能化能源管理平台，结合多能源介质产耗预测技术、预测数据和优化调度技术、非线性规划求解技术等，建立能源管网智能模拟和协同平衡模型，实现能源系统多周期动态优化调度。该技术适用于流程工业能源系统运维管理及改造。技术提供单位为浙江中控技术股份有限公司。在辽宁省某能源管理优化项目中，企业万元产值综合能耗下降3.15%，节能率3%，可节约标准煤2万吨/年。
（六）基于工业互联网面向工业窑炉高效燃烧的大涡湍流算法，通过大涡湍流燃烧模拟算法设计适用于该工业炉窑的燃烧系统并根据模拟所得参数对炉窑现有燃烧系统进行改造，同时采用工业互联网技术对工业燃烧动态参数进行即时运算和呈现，实现精细化燃烧。该技术适用于基础工业产品热加工及热处理用燃烧系统改造。技术提供单位为江阴优燃科技有限公司。在中国某特种装备制造公司表面加热控制系统改造项目中，以大涡湍流燃烧模拟为基础设计一套表面加热燃烧控制系统，与国内现有的加热排管相比，节省天然气40%，可节省天然气40万立方米/年。
（七）基于云计算的能源站智能化能效管控技术，通过网关采集设备和系统运行数据，利用优化算法和专家模型，实现对能源站设备及系统状态感知、诊断和优化。同时利用虚拟对象技术及参数可编程技术，扩充适用能源站类型，扩展节能优化算法。该技术适用于工业企业能源系统运维管理及改造。技术提供单位为杭州哲达科技股份有限公司。在河南省某化工有限责任公司压缩空气系统节能改造项目中，空压站基准电耗降低0.05千瓦时/标立方米，节能量为880万千瓦时/年。
（八）基于工业大数据动态优化模型的离散制造业用能管控技术，以离散制造业中能流动态模型为主线，对生产场景内能流、价值流进行解耦分析，利用工业互联网体系和大数据采集分析手段，结合精益管理途径，提供节能工艺参数优化、节能排产优化等优化措施。该技术适用于离散制造业企业压铸、热处理等工序运维管理及改造。技术提供单位为重庆工业大数据创新中心有限公司。在重庆市某大型机械加工企业改造项目中，建设基于工业大数据驱动的绿色制造智能产线管理平台，设备运行效率提升27%，生产能效提升21%，节能率6%。
（九）基于大数据分析的企业用能智能化运营技术，采用大数据、云计算等信息技术，实现对企业用能24小时连续监测监控以及存储、计算、分析，结合实时预警策略，对工业企业和园区内能源系统进行调控配置。该技术适用于工业企业及园区能源系统运维管理及改造。技术提供单位为青岛海尔能源动力有限公司。在山东省某智慧能源改造项目中，建设基于大数据分析的企业用能智慧运营平台对用能设备进行分布式监控和集中管理，项目节能率为20%，节能量为18万千瓦时/年。
（十）基于第五代移动通信（5G）及大数据的数字设备节能管理技术，通过第五代移动通信获取数字设备运行功率数据及开关权限，通过微控制单元（MCU）实现集中管理及分路独立计量，并基于大数据技术实现差异化备电、远程使用授权等功能。该技术适用于工业和通信企业数字设备运维管理及改造。技术提供单位为中国铁塔股份有限公司重庆市分公司。在重庆市某商圈电源配套改造项目中，对36个基站电源配套机柜增加智能配电单元及相关设备，平均每站电量消耗为63千瓦时/天，节能率为12.5%，节能量为12万千瓦时/年。
（十一）钢铁烧结过程协同优化及装备智能诊断技术，通过关键工艺参数和生产指标感知技术，建立烧结过程产量、质量、能耗多目标优化与智能控制模型，实现烧结过程能耗降低与质量提高，以及智能化与无人化作业。该技术适用于钢铁工业烧结工厂新建及改造。技术提供单位为中冶长天国际工程有限责任公司。在河北省某公司215平方米烧结工程智能制造系统EPC项目中，工序能耗降低1.5千克标准煤/吨矿，电耗降低15千瓦时/吨矿，煤气消耗降低约10立方米/吨矿。
翻译：
Digital technology can accelerate industrial energy saving and efficiency improvement. Through intelligent management and optimization of green product design, production process optimization, energy control, process coordination and resource scheduling, energy utilization efficiency can be improved. Using 5G, industrial Internet, big data and other new generation of information technology to achieve energy flow, material flow and other information collection and monitoring, intelligent analysis, fine management, system optimization, to achieve the improvement of energy, resources, environmental management level is the development direction of digital green collaborative transformation technology in the industrial field.
(I) High-speed carrier data acquisition and power supply system optimization technology of the electric Internet of Things.
High-frequency acquisition and real-time monitoring and analysis are carried out on information such as power supply data, equipment operating parameters and environmental status of low-voltage power supply station area by using high-speed carrier technology of the electric Internet of Things, so as to realize status monitoring of power supply lines, perception and regulation of power load. The technology is suitable for operation and maintenance management and transformation of power supply and distribution system in industrial enterprises. The technology provider is Beijing Zhixin Microelectronics Technology Co., LTD. In the demonstration project of intelligent power supply system monitoring and line loss control, high-speed carrier data acquisition and power supply system of the electric Internet of Things are used to collect residential electricity data and accurately adjust electricity load, saving energy of 1.2 million KWH/year.
(2) The public auxiliary workshop management system based on wireless communication and multi-constraint artificial intelligence algorithm displays the operation status of the workshop equipment in a visual way, carries out intelligent control of the equipment through big data visualization technology, narrow-band constant pressure technology, multi-constraint and multi-parameter control algorithm and edge computing technology, and assists in the improvement of the operation quality and pressure of the air compressor station. The technology is suitable for operation and maintenance management and transformation of public auxiliary workshops such as air compressor station building in industrial enterprises. The technology provider is Mogoku Internet of Things Technology (Shenzhen) Co., LTD. In the Yunzhi control transformation project of air compressor station in an automobile assembly factory, the average loading rate of air compressor station equipment increased from 95% to 98%, and the energy saving was 650,000 KWH/year.
(3) Intelligent energy use management and control technology of industrial enterprises based on big data.
It adopts algorithms such as fingerprint extraction of electrical equipment and load power consumption data prediction to monitor and collect energy use information data of industrial enterprises. On this basis, intelligent analysis and management are carried out based on artificial intelligence and big data technology to assist energy use control and energy efficiency improvement by digital means. The technology is suitable for overall energy management and transformation in industrial parks. The technology provider is Tianjin Puxun Electric Power Information Technology Co., LTD. In an energy-saving renovation project of a business hall, the comprehensive energy efficiency ratio of the system was increased from 1 to 2.50, the energy saving rate was 20%, and the energy saving was 30,000 KWH/year.\
(4) Intelligent collaborative management technology of equipment operation
Intelligent collaborative management technology of equipment operation based on the industrial Internet, monitoring and analysis of equipment operating status and environmental parameters through the industrial Internet platform relying on the Internet of Things, artificial intelligence, big data, cloud computing and other technologies, to achieve self-warning, self-diagnosis and optimization based on algorithm model, and reduce equipment energy consumption. The technology is suitable for industrial enterprise equipment operation management and transformation. The technology provider is Jinlv Environmental Technology Co., LTD. In the transformation project of intelligent cooperative management of equipment operation in Anhui Province, predictive maintenance and intelligent operation and maintenance platform was built, which saved 7.29 million KWH/year.
(5) Operation scheduling optimization technology of process industrial energy system, building intelligent energy management platform with large database, combining multi-energy medium production and consumption forecasting technology, forecast data and optimization scheduling technology, nonlinear programming solution technology, etc. Establishing intelligent simulation and collaborative balance model of energy pipe network, realizing multi-cycle dynamic optimization scheduling of energy system. The technology is suitable for operation and maintenance management and transformation of energy system in process industry. The technology provider is Zhejiang Zhongcong Technology Co., LTD. In an energy management optimization project in Liaoning province. The comprehensive energy consumption per 10,000 yuan of output value of the enterprise decreased by 3.15%. The energy saving rate was 3%, and 20,000 tons of standard coal could be saved per year.
(6) Based on the large eddy turbulence algorithm for efficient combustion of industrial kilns on the industrial Internet.
The combustion system suitable for the industrial furnace is designed through the large eddy turbulence combustion simulation algorithm. And the existing combustion system of the furnace is reformed according to the simulated parameters. At the same time, the industrial Internet technology is used to carry out real-time calculation and display of the dynamic parameters of industrial combustion. So as to achieve fine combustion. The technology is suitable for the transformation of combustion system for hot processing and heat treatment of basic industrial products. The technology provider is Jiangyin Youzhan Technology Co., LTD. In the surface heating control system renovation project of a special equipment manufacturing company in China. A set of surface heating combustion control system was designed based on large eddy turbulence combustion simulation. Compared with the existing domestic heating row pipe. The system can save 40% of natural gas and 400,000 cubic meters of natural gas per year.
(7) Intelligent energy efficiency management and control technology of energy station based on cloud computing. Collecting equipment and system operation data through the gateway. And using optimization algorithms and expert models to realize the perception, diagnosis and optimization of energy station equipment and system status. At the same time, virtual object technology and parameter programmable technology are used to expand the applicable energy station types and extend the energy-saving optimization algorithm. The technology is suitable for operation and maintenance management and transformation of energy system in industrial enterprises. The technology provider is Hangzhou Zheda Technology Co., LTD. In the compressed air system energy-saving renovation project of a chemical company in Henan Province. The benchmark power consumption of the air compressor station was reduced by 0.05 KWH/standard cubic meter. And the energy saving was 8.8 million KWH/year.
(8) Energy use management and control technology of discrete manufacturing based on dynamic optimization model of industrial big data.
Taking energy flow dynamic model of discrete manufacturing industry as the main line, decoupling analysis is carried out on energy flow and value flow in production scenes. And optimization measures such as energy-saving process parameter optimization and energy-saving production scheduling optimization are provided by using industrial Internet system and big data collection and analysis means combined with lean management approach. The technology is suitable for operation and maintenance management and transformation of die casting, heat treatment and other processes in discrete manufacturing enterprises. The technology provider is Chongqing Industrial Big Data Innovation Center Co., LTD. In the transformation project of a large mechanical processing enterprise in Chongqing. A green manufacturing intelligent production line management platform driven by industrial big data was built. And equipment operation efficiency was increased by 27%, production energy efficiency by 21%, and energy saving rate by 6%.
(9) Intelligent operation technology of enterprise energy use based on big data analysis.
Information technologies such as big data and cloud computing are adopted to realize 24-hour continuous monitoring, storage, calculation and analysis of enterprise energy use. Combined with real-time warning strategy, regulation and configuration of energy systems in industrial enterprises and parks are carried out. The technology is suitable for operation and maintenance management and transformation of energy system in industrial enterprises and parks. The technical provider is Qingdao Haier Energy Power Co., LTD. In a smart energy transformation project in Shandong Province. An enterprise energy intelligent operation platform based on big data analysis was built to conduct distributed monitoring and centralized management of energy consumption equipment. The project’s energy saving rate was 20% and energy saving was 180,000 KWH/year.
(10) Based on the fifth generation mobile communication (5G) and big data digital equipment energy-saving management technology. Through the fifth generation mobile communication to obtain the digital equipment running power data and switching rights. Through the micro control unit (MCU) to achieve centralized management and independent metering. And based on big data technology to achieve differentiated backup power, remote use authorization and other functions. The technology is suitable for industrial and communication enterprise digital equipment operation and maintenance management and transformation. The technology provider is Chongqing Branch of China Tower Company Limited. In a power supply supporting renovation project of a business district in Chongqing. Intelligent distribution units and related equipment were added to 36 base station power supply supporting cabinets. The average power consumption of each station was 63 KWH/day. The energy saving rate was 12.5%, and the energy saving was 120,000 KWH/year.
(11) Collaborative optimization of iron and steel sintering process and intelligent diagnosis technology of equipment.
Multi-objective optimization and intelligent control model of output. Quality and energy consumption in sintering process is established through key process parameters and production index perception technology. So as to achieve energy consumption reduction and quality improvement in sintering process, as well as intelligent and unmanned operation. The technology is suitable for the construction and transformation of sintering plant in iron and steel industry. The technology provider is China Metallurgical Changtian International Engineering Co., LTD. In the EPC project of 215 square meters of intelligent manufacturing system for a sinter project of a company in Hebei Province. The process energy consumption is reduced by 1.5 kg standard coal per ton ore. The power consumption is reduced by 15 KWH per ton ore. And the gas consumption is reduced by about 10 cubic meters per ton ore.
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