Clustering of Electricity Consumption Behavior Dynamics Toward Big Data Applications

By Yi Wang, Qixin Chen, Chongqing Kang, Qing Xia. IEEE Transactions on Smart Grid, 2016

317 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Signal Processing

View Paper: https://www.semanticscholar.org/paper/e7e6a66f48a861e1793e32be9b9b67c08ac765b7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Chongqing Kang
2. Yi Wang
3. Qixin Chen
4. Chen-Ching Liu

In Electrical and Electronic Engineering

1. Chongqing Kang
2. Qixin Chen
3. Yi Wang
4. Sijie Chen
5. Tao Hong
6. Chen-Ching Liu
7. Rafal Weron

In Signal Processing

1. Chongqing Kang
2. Yi Wang
3. Qixin Chen

Citations in the corpus

• From demand response to transactive energy: state of the art (2017, background): “, to develop demand response strategies for specific loads [35], such as HVAC loads, batteries, electric vehicles (EVs), data centers, and computer servers.”
• Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges (2018, methodology): “For low granularity (such as 15 minutes) smart meter data, symbolic aggregate approximation (SAX), a classic time series data compression method, was used in [29] and [180] to reduce the dimensionality of load profiles before clustering.”