The Smart System Group Congratulate Sonam Norbu who has been chosen as the Winner of 2021 EPS Postgraduate Research 2nd Year Prize from the Institute of Sensors, Signals and Systems, The School of Engineering and Physical Science (EPS). The prize will be awarded at the upcoming Annual EPS Postgraduate Research (PGR) Day, the 18th October, […]
Tag: Dr Valentin Robu
Early Access Publication: Modeling Economic Sharing of Joint Assets in Community Energy Projects under LV Network Constraints
The Smart Systems Group congratulate Sonam Norbu, Dr. Benoit Couraud, Dr. Merlinda Andoni, Dr. Valentin Robu and Prof. David Flynn on the acceptance of their paper “Modeling Economic Sharing of Joint Assets in Community Energy Projects under LV Network Constraints“, published in IEEE Access (Early Access) today. “The trend of decentralization of energy services has […]
New Publication: Prediction of voltage distribution using deep learning and identified key smart meter locations
The energy landscape for the Low-Voltage (LV) networks is undergoing rapid changes. These changes are driven by the increased penetration of distributed Low Carbon Technologies, both on the generation side (i.e. adoption of micro-renewables) and demand side (i.e. electric vehicle charging). The previously passive ‘fit-and-forget’ approach to LV network management is becoming increasing inefficient to […]
New Publication: Analysis of Strategic Renewable Energy, Grid and Storage Capacity Investments via Stackelberg-Cournot modelling
Congratulations to Dr. Merlinda Andoni, Dr. Valentin Robu, Dr. Benoit Couraud, Dr. Wolf-Gerrit Fruh, Mr. Sonam Norbu and Prof. David Flynn for the acceptance of their manuscript “Analysis of Strategic Renewable Energy, Grid and Storage Capacity Investments via Stackelberg-Cournot modelling” for publication in IEEE Access. IEEE Access is an award-winning, multidisciplinary, all-electronic archival journal, continuously presenting the […]
New Publication: A Machine Learning Degradation Model for Electrochemical Capacitors Operated at High Temperature
Congratulations to Darius Roman, Valentin Robu and David Flynn for acceptance of their research to IEEE Access. Their publication “A Machine Learning Degradation Model for Electrochemical Capacitors Operated at High Temperature” was a collaborative work between the Smart Systems Group, the Argonne National Laboratory, Baker Hughes, the Center for Advanced Life Cycle Engineering (CALCE) and […]
New method for controlling and sharing the benefits from community energy projects
Congratulations to Sonam Norbu, Benoit Couraud, Valentin Robu, Merlinda Andoni and David Flynn on the acceptance of their publication “Modelling the redistribution of benefits from joint investments in community energy projects” to Elsevier’s Applied Energy journal. Applied Energy provides a forum for information on innovation, research, development and demonstration in the areas of energy conversion and conservation, the optimal […]
Upcoming Webinar 17th September 2020: Artificial Intelligence and Machine Learning for Demand-Side Response
We are pleased to announce an upcoming webinar hosted by IEEE Smart Grid, titled “Artificial Intelligence and Machine Learning for Demand-Side Response” presented by Ioannis Antonopoulos, Benoit Couraud and Valentin Robu of the Smart Systems Group. This event will be held Thursday, September 17, 2020 – 11:00am EDT In the recent years, there has been […]
New Publication: Prognostics and Health Management for the Optimization of Marine Hybrid Energy Systems
In 2018, Heriot-Watt University won the British Renewable Energy Association (BREA) award for the decarbonisation of transport, recognising quality, commitment and innovation in low carbon vehicles – cars, vans, buses, road freight or on farm vehicles, powered by clean electricity or sustainable biofuels – and alternative vehicle fuels. We are very pleased to now provide […]
New Publication: Artificial Intelligence and Machine Learning Approaches to Energy Demand-Side Response: A Systematic Review
The Smart Systems Group, in collaboration with the Center for Collective Intelligence at Massachusetts Institute of Technology, the School of Engineering at University of Edinburgh, the Office of Gas and Electricity Markets (Ofgem) and Upside Energy are pleased to announce the publication of “Artificial Intelligence and Machine Learning Approaches to Energy Demand-side Response: A Systematic […]
A Safety Framework for Critical Systems Utilising Deep Neural Networks
It is our pleasure to announce the publication of “A Safety Framework for Critical Systems Utilising Deep Neural Networks” by Dr. Xingyu Zhao of the Smart Systems Group, in collaboration with partners at the University of Liverpool and the Defence Science and Technology Laboratory (DSTL). This research paper will be published in Springer-Verlag Lecture Notes […]