大数据和云计算技术在燃煤电厂节能减排中的应用设计Application of Big Data and Cloud Computing Technology in Energy Conservation and Emission Reduction of Coal-Fired Power Plants
张志勇,禾志强,那钦,陈媛媛,龙建平
ZHANG Zhiyong,HE Zhiqiang,Naqin,CHEN Yuanyuan,LONG Jianping
摘要(Abstract):
以我国火电行业节能减排技术发展需求为牵引,以燃煤电厂烟气数据采集、数据存储、数据安全、数据分析为着力点,将大数据、云计算、物联网等现代化技术应用于燃煤电厂节能减排过程中,搭建了节能减排监控平台。该平台具有实时监测、设备故障分析、环保对标、技术监督、电价核算等功能,可实现火电厂大气污染物的实时监管和设备状态的智能监测,为电厂智慧化运行管理提供技术支撑,为电网绿色节能调度提供数据信息。
Guided by the development requirements of energy conservation and emission reduction technology in the thermal power industries, of China focusing on flue gas data acquisition, data storage, data security and data analysis of coal fired power plants, big data, cloud computing technology, Internet of things and other modern technologies are applied in the process of energy conservation and emission reduction of coal fired power plants. The energy conservation and emission reduction monitoring platform is built, which has the functions as real-time monitoring, equipment fault analysis environmental protection benchmarking, technical supervision, electricity price accounting, and so on, which realizes the real-time supervision of air pollutants in thermal power plants and intelligent monitoring of equipment status, provides technical support for intelligent operation and management of power plants, and provides data information for green energy-saving dispatching of power grid.
关键词(KeyWords):
大数据;云计算技术;燃煤电厂;监控平台;节能减排
big data;cloud computing technology;coal fired power plant;monitoring platform;energy conservation and emission reduction
基金项目(Foundation): 内蒙古自治区应用技术研究与开发基金计划“基于云计算大数据的内蒙古电网节能减排监控关键技术开发及应用研究”(201701010)
作者(Author):
张志勇,禾志强,那钦,陈媛媛,龙建平
ZHANG Zhiyong,HE Zhiqiang,Naqin,CHEN Yuanyuan,LONG Jianping
参考文献(References):
- [1]国务院.“十三五”节能减排综合工作方案:国发(2016)74号[Z].北京:国务院,2017.
- [2]国家发展和改革委员会,国家能源局.能源发展“十三五”规划:发改能源(2016)2744号[Z].北京:国家发展和改革委员会,2016.
- [3]国家发展和改革委员会,国家能源局.电力发展“十三五”规划(2016—2020年)[Z].北京:国家发展和改革委员会,2016.
- [4]国务院.打赢蓝天保卫战三年行动计划[Z].北京:国务院,2018.
- [5]国务院.促进大数据发展行动纲要:国发(2015)50号[Z].北京:国务院,2015.
- [6]沈发荣.火力发电企业节能减排的形势[J].云南电力技术,2011,39(2):106-111.
- [7]朱红梅,刘晓波,宋达.电力系统大用户节能减排有效措施[J].贵州电力技术,2015,18(6):79-81.
- [8]郦建国,朱法华,孙雪丽.中国火电大气污染防治现状及挑战[J].中国电力,2018,51(6):2-10.
- [9]环境保护部,国家质量监督检验检疫总局.火电厂大气污染物排放标准:GB/T 13223—2011[S].北京:中国环境科学出版社,2011.
- [10]中国电力企业联合会节能环保分会.燃煤电厂环境污染第三方治理脱硫、脱硝生产指标绩效对标管理办法(试行)[Z].北京:中国电力企业联合会节能环保分会,2018.
- [11]中华人民共和国.中华人民共和国环境保护税法[Z].北京:中国法制出版社,2016.
- [12]国家发展和改革委员会,环境保护部.燃煤发电机组环保电价及环保设施运行监管办法:发改价格(2014)536号[Z].北京:国家发展和改革委员会,2014.
- [13]龙建平,江平,丁伟.基于数据挖掘的燃煤机组健康状态评价方法研究[J].广西电力,2019,42(3):36-39.
- [14]王正风,陈实,马大卫.安徽省燃煤火电机组脱硝在线监测系统建设[J].东北电力技术,2017,38(9):54-56,59.
- [15]朱庆会,韩青云.燃煤电厂大气污染防治对策思考[J].资源节约与环保,2016(3):132-133.
- [16]陈理帅,张东明,赵盼龙.燃煤电厂超低排放系统能耗关键因素分析[J].浙江电力,2020,39(12):117-121.
- 大数据
- 云计算技术
- 燃煤电厂
- 监控平台
- 节能减排
big data - cloud computing technology
- coal fired power plant
- monitoring platform
- energy conservation and emission reduction