Global Challenge - 'Smart Grid Big Data' Workshop Overview

Big data is revolutionising and redefining all aspects of our lives as individual consumers, as businesses and as a society. ‘High performance data analytics’ has been recognised as a major player and a game changer for the modern electric power industry. The workshop aims to bring together international experts from both academia and industry in the UK, China, Ireland and US to address big data challenges in smart grid modernisation. Smart grid modernisation is a key component of China’s ambition to deliver a clean, reliable electricity supply to all its citizens, and in particular in rural areas.

Topics of interest include, but are not limited to: 
  • Real-time PMU based data analytics and visualisation 
  • Energy forecasting with increased embedded renewable generation 
  • Data driven demand side management 
  • Smart Grid wide-area monitoring and visualisation 
  • Smart Grid Cyber Security
The workshop will be held in Zhejiang University over 2 days from 19 Nov to 20 Nov 2016 and will include an industrial visit to Shanghai Minhang Huadian Energy on 21 Nov 2016. The ultimate goal of the workshop is to provide a platform for attendees to share ideas and develop a road map for future collaborations to address major challenges that exist around big data with application in the clean energy domain. 

Main objectives of the workshop 
  • Provide a platform for stakeholders to exchange experiences, and identify promising research directions to address the big data challenges in the smart grid area, with a particular focus on improving the security of electricity supply to rural communities and creating business opportunities for these communities as ‘prosumers’ (i.e. selling services to the grid)
  • Identify topics where Queen's University Belfast and China can collaborate to deliver high quality research outputs in the smart grid big data area and explore opportunities for future grant applications to support these collaborations. 

Scientific Organising Committee

Chair:        Prof Sean McLoone, Queen’s University Belfast, s.mcloone@qub.ac.uk
Co-Chair:  Dr Xueqin (Amy) Liu, Queen’s University Belfast, x.liu@qub.ac.uk
Co-Chair:  Prof Lei Xie, Zhejiang University, leix@iipc.zju.edu.cn
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