Big Data and Cloud Computing Platform for Energy Internet

被引：0

作者：

Fu, Rui ^{[2
]}

Gao, Feng ^{[2
]}

Zeng, Rong ^{[1
]}

Hu, Jun ^{[1
]}

Luo, Yi ^{[2
]}

Qu, Lu ^{[2
]}

机构：

[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China

[2] Tsinghua Univ, Energy Internet Res Inst, Beijing 100084, Peoples R China

来源：

PROCEEDINGS OF 2017 CHINA INTERNATIONAL ELECTRICAL AND ENERGY CONFERENCE (CIEEC 2017) | 2017年

关键词：

MapReduce; Spark; Lambda Architecture; BaaS; Microservice Architecture; Complementary Operation of Multi-form Energy System;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Energy Internet is a developing trend of electrical power energy industry. The core message is to implement the next-generation of cyber-physical systems shaping future energy industry-that is based on a deep merge of operational technology and internet information technology. The growth of energy internet is dependent on the availability of high performance computing and analytics technology to process a massive amount of data set. The paper discusses two core techniques that would support the growth of energy internet, big data and clouding computing, with a focus on the platform architecture that is particularly adaptive to handle a variety of characteristics of energy industry data. Finally, the paper summarizes and proposes a comprehensive, technical solution for energy big data and IoT cloud computing platform with applications focusing on energy consumption monitoring and complementary operation of multi-form energy system that support all aspects within a data lifetime cycle, e.g., acquisition, storage, analytics, and visualization.

引用

页码：681 / 686

页数：6

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