IEEE Power & Energy Magazine - May/June 2018 - 56
For Power Grid
For Third Parties
figure 1. A framework for big data analytics in the electric power industry.
figure 2. A word cloud for big data analytics projects in
the electric power industry supported by the NSFC.
ogy funded another five-year project, "fundamental theory
of the Planning and operation of Power systems with high
Proportion of renewable energy," the first and largest phase
of which is big data analytics for energy forecasting, demand
response targeting, and net load characteristic analysis.
besides these government-funded research projects,
many power companies have also sponsored various big
data projects including data collection, integration, mining,
and forecasting. through the implementation of these projects, big data analytics in the electric power industry is moving from fundamental and applied research to field practice.
the increasing prevalence of big data technologies has been
challenging and is changing traditional power system planning and operation practices. it has also stimulated the birth
of many start-up companies.
this article introduces some recent progress in the application of big data analytics in china's electric power industry.
selected applications include demand response, renewable
integration, system operations, and equipment monitoring.
we conclude by discussing some particular opportunities
Demand-Side Big Data Analytics
us$3.3 million). figure 2 depicts a word cloud of these project
titles, which cover a wide range of topics within the power
industry, including energy forecasting, equipment monitoring, and renewable integration. in 2015, the Ministry of science and technology funded a five-year project, "Key technologies of big Data analytics for intelligent Distribution and
utilization." in 2017, the Ministry of science and technol56
ieee power & energy magazine
big data analytics is revolutionizing marketing practices
across various industries. the big chinese e-commerce players, such as alibaba and Jingdong, rely heavily on big data
analytics to exploit insights from customers' purchasing
and web-browsing behaviors for the purpose of customized
marketing. in addition, power grid operators and electricity retailers are attempting to analyze customers' electricity