PDF(3716 KB)
Construction of New Energy Monitoring and Big Data Platform Based on Cloud-Side Collaboration
WANG Lijie, ZHANG Xiping, FENG Qiang, WU Junyi
Distributed Energy ›› 2021, Vol. 6 ›› Issue (1) : 44-50.
PDF(3716 KB)
PDF(3716 KB)
Construction of New Energy Monitoring and Big Data Platform Based on Cloud-Side Collaboration
In order to solve the problems of chaotic control and inefficient maintenance of new energy stations, with the rapid development of big data, cloud platform, internet of things and other related technologies, the construction of new energy monitoring and big data center can improve the management and control ability of new energy stations. At present, new energy big data platforms launched in the industry mostly focus on the intelligent optimization of a single model or station and lack the overall coordination of the group-level new energy business, which makes it difficult to achieve the coordination and integration of various equipment and different systems. In view of the limitations of new energy big data platform construction at the present stage, it has become inevitable for the development of the new energy industry to build a group-level new energy monitoring and big data center to achieve a high degree of integration and sharing of resources and experience. In this paper, relying on the construction background of China Datang Corporation new energy two-level center, sorting out the business process of new energy production equipment management and control and designing the platform technical architecture of cloud-side collaboration, could realize the multilevel fusion of from the bottom perception to the top decision-making and provide guidance for analysis and processing of new energy heterogeneous assets and data and design of group-level new energy big data platform.
cloud-side collaboration / monitoring and big data platform / architecture design / new energy
| [1] |
张喜平,赵维,王丽杰. 新能源大数据平台物联网数据接入架构设计与实现[J]. 分布式能源,2020, 5(6): 33-38.
|
| [2] |
吕明明. 集控中心在风电企业管理中的创新研究[J]. 神华科技,2019, 17(5): 3-7.
|
| [3] |
吴智泉. 推进智慧风电建设,提高风电核心竞争力[J]. 中国经济周刊,2019 (10): 108-109.
|
| [4] |
吴智泉,王政霞. 智慧风电体系架构研究[J]. 分布式能源,2019, 4(2): 8-15.
|
| [5] |
侯彦全,程楠,侯雪. 远程运维服务模式研究——以金风科技为例[J]. 工业经济论坛,2017, 4(2): 68-73.
|
| [6] |
朱程. 远景“智慧风场管理”:运用物联网技术实现“无人值守”[J]. 中国信息安全,2016(10): 60-62.
|
| [7] |
孙一琳. 量云:智慧让风电场“能动”起来[J]. 风能,2019(7): 38-40.
|
| [8] |
孙玉敏. 上海电气掘金“智慧风场”[J]. 上海国资,2016 (5): 56-57.
|
| [9] |
阳熹,杨源. 智慧型海上风电场一体化监控系统方案设计[J]. 南方能源建设,2019, 22(1): 48-54.
|
| [10] |
刘凤友,权锋,徐汉坤. 基于数字化的可视化风电项目智慧管理解决方案[J]. 水力发电,2020, 46(4): 101-104.
|
| [11] |
陈国旗. 风电场集控中心综合管理平台远程监控系统的设计与实现[D]. 长春:吉林大学,2015.
|
| [12] |
赵少东,王程斯. 基于异构计算与实时可视化技术的综合能源大数据平台研究与应用[J]. 微型电脑应用,2019, 35(11): 96-99.
|
| [13] |
石睿,马风雷. 基于数据挖掘技术的风电新能源大数据平台构建[J]. 吉林工程技术师范学院学报,2017, 33(12): 108-110.
|
| [14] |
张自强,延亮,周识远. 基于云架构的分布式新能源智能服务平台构建[J]. 电子设计工程,2020(21): 154-158.
|
| [15] |
孙伟,叶林. 区域风电集控中心集中式风功率预测系统关键技术研究[C]//中国农业机械工业协会风力机械分会.第七届中国风电后市场交流合作大会论文集:中国农业机械工业协会风力机械分会,2020: 5.
|
| [16] |
姚惠. 风电场功率预测预报问题及其管理提升建议[J]. 企业改革与管理,2020(1): 209-210.
|
| [17] |
武佳卉,邵振国,杨少华,等. 数据清洗在新能源功率预测中的研究综述和展望[J]. 电气技术,2020, 21(11): 1-6.
|
| [18] |
王旭东. 面向智慧风场的运维管理关键技术研究. [D] 杭州:浙江大学,2019.
|
| [19] |
魏嘉. 大数据下风电机组齿轮箱故障诊断方法研究[D] 北京:华北电力大学,2017.
|
/
| 〈 |
|
〉 |