Associate Professor Ir. Ts. Dr. Teh Jiashen
Last Updated on 27.09.2024
PhD, University of Manchester. B.Eng (Hons), Universiti Tenaga Nasional. Chartered Engineer (CEng) (UK), MIET, MIEEE Researcher ID : I-8860-2016 Last Updated on 19.06.2023 I studied for my first Electrical and Electronic Engineering degree in the National Energy University (translated from Universiti Tenaga Nasional) at Selangor, Malaysia. Following this I completed a PhD in the University of Manchester at the UK. This saw me work on the dynamic ratings of transmission networks and the probabilistic modelling of the power systems. Please click the Google Scholar link below to see the live update of my publications: Last Updated on 13.12.2019 Last Updated on 13.12.2019 Please contact me if you have an excellent academic background and an enthusiasm for research in the following areas: Probabilistic modelling of Funding from me is considered on a case-by-case basis. General funding opportunities can be found at http://www.ips.usm.my/ Last Updated on 27.11.2019Personal Info
Tel : +604-599 6016
Fax : +604-599 6909
Email:
ORCID : 0000-0001-9741-6245
Scopus ID : 56992718600
GoogleScholar ID : BA9V8QoAAAAJ
USM Expertise Link : https://experts.usm.my/cvitae/jiashentehBiography
Publications
Google ScholarGrants
Amount: RM94,600.00
Status: Active (September 2019 - August 2022)
Role: Principal Investigator
Source: Ministry of Education Fundamental Research Grant Scheme (FRGS)
Amount: RM 70,000
Atatus: Active (September 2018 – May 2020)
Role: Principal Investigator
Source: USM Research University Grant
Amount: RM 20,000 (~TWD 150,000)
Status: Active (May 2018 – May 2020)
Role: Principal Investigator
Source: UPE Power Co. Ltd Grant
Amount: RM 10,000
Status: Completed (Janury 2018 – September 2018)
Role: Principal Investigator
Source: USM Bridging Grant
Amount: RM 37,500
Status: Completed (October 2016 – September 2018)
Role: Principal Investigator
Source: USM Short Term GrantOpportunities
- DTR system
- DSM
- Renewable energy sources
-Energy storage systems
-ICTs
-EVs
-FACTS
-New algorithms to more efficiently optimize power flows