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Accepting PhD Students

20122022
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Personal profile

Research interests

Profile 

Dr Li  graduated from both University of Bath and North China Electric Power University in 2011 with BEng in electrical power engineering.

He received his PhD in 2014 from Bath, with thesis entitled “Load profiling on time-frequency domain: from big data to smart data”.

Between 2014 and 2015, Ran worked as research associate (RA) in an EPSRC UK-China smart grid project. He took up a lectureship in September 2015.

Research interests

Dr Li has developed a set of big data analytic techniques based on statistics and spectral analysis in order to address challenges brought by smart grid and smart meters. He has extensive experience in working with UK power industry and regulator in low carbon distribution network development and smart metering reform.

Willing to supervise PhD

Interested in supervising students. PhD studentship available. Interested candidates should contact Dr Li directly.

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Smart meters Engineering & Materials Science
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Industry Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2015 2022

Customer-Led Distribution System (From DNO to DSO)

Li, F., Gu, C., Hernando Gil, I., Li, R., Ma, K. & Pei, X.

19/10/1718/10/22

Project: UK industry

Carbon
Learning systems
Costs
Scheduling
Pumps

EMBOSSA

Li, R., Le Blond, S. & Li, F.

1/04/1731/03/18

Project: Research council

Electricity
Energy security
Kerosene
Costs
Toxic materials

P2P SmarTest

Li, F. & Li, R.

1/01/1531/12/17

Project: EU Commission

Communication
Energy resources
Industry
Project management
Telecommunication traffic

Research Output 2012 2019

A Statistical Approach to Estimate Imbalance-Induced Energy Losses for Data-Scarce Low Voltage Networks

Fang, L., Ma, K., Li, R., Wang, Z. & Shi, H., 9 Jan 2019, In : IEEE Transactions on Power Systems. p. 1-1 1 p.

Research output: Contribution to journalArticle

Open Access
File
1 Citation (Scopus)

Big Data Analytics for Flexible Energy Sharing: Accelerating a Low-Carbon Future

Li, F., Li, R., Zhang, Z., Dale, M., Tolley, D. & Ahokangas, P., 1 May 2018, In : IEEE Power and Energy Magazine. 16, 3, p. 35-42

Research output: Contribution to journalArticle

Open Access
File
14 Citations (Scopus)

Deep Learning for Household Load Forecasting – A Novel Pooling Deep RNN

Shi, H., Xu, M. & Li, R., 30 Sep 2018, In : IEEE Transactions on Smart Grids. 9, 5, p. 5271-5280 10 p.

Research output: Contribution to journalArticle

Open Access
File
Uncertainty analysis
Recurrent neural networks
Spectrum analysis
Learning algorithms
Learning systems

Electric Vehicle Load Disaggregation Based on Limited Activation Matching Pursuits

Li, R., Evans, A., Li, F. & Wang, S., 2018.

Research output: Contribution to conferencePaper

Mitigating load forecast errors for suppliers by utilizing energy storage at a substation level

Yan, X., Ma, Q., Wyman-Pain, H., Gu, C., Li, R. & Li, F., 16 Jan 2018, Proceedings of IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 . IEEE, p. 1-5 5 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Energy storage
Costs
Cost reduction
Economics

Thesis

3D Face Recognition Using Multicomponent Feature Extraction from the Nasal Region and its Environs

Author: Gao, J., 23 Nov 2016

Supervisor: Evans, A. (Supervisor) & Li, R. (Supervisor)

Student thesis: Doctoral ThesisPhD

File

Load Profiling on Time and Spectral Domain: From Big Data to Smart Data

Author: Li, R., 19 Jan 2015

Supervisor: Li, F. (Supervisor)

Student thesis: Doctoral ThesisPhD

File