报告时间：2022年1月13日16:30

报告方式：

线上：腾讯会议（ID：947 184 489）

线下：东区机自大楼537D

报告题目：Data Analytics Facilitating Net Zero Energy Systems

报告摘要：In 2019, the UK was the first to embrace a legal obligation to achieve net-zero carbon emissions by 2050. The energy sector plays a vital role to deliver this target, as transportation, energy supply, commercial use of electricity & heating homes accounts for about 80% of emissions. Consequently, demand electrification and increased renewable generation became the major pathway in addressing climate change.

Artificial Intelligence and big data are transforming the world, in many sectors from banking, insurance to healthcare. In this talk, we introduce some recent work carried out in Queen’s University Belfast on smart grid data analytics to facilitate Net Zero Energy Systems. This includes (1) estimation of aggregated small scale solar generation, which is unseen to the power system operators and introduces large volatility to the electric net demand. (2) monitoring the health of the power networks, reliably detecting abnormal behaviours (e.g. oscillations), diagnosing the failures, and taking control actions.

报告人简介：Dr Xueqin (Amy) Liu received her Ph.D. degree in electrical and electronic engineering from Queen's University Belfast (QUB), U.K., in 2009, under the joint training with the Institute of Cyber-Systems and Control, Zhejiang University. She continued her academic career in QUB as a research assistant (2009-2011), Lecturer (2013-2019), and Senior Lecturer with the School of Electronics, Electrical Engineering and Computer Science.

Her research focuses on smart grid data analytics, to address major challenges emerging in the energy industry. She has published over 70 papers in leading journals/conferences. She organized and chaired an EPSRC global challenge ‘Smart Grid Big Data’ international workshop with Zhejiang University in 2016. She is Co-I leading QUB’s research in the £7Million EU SPIRE2 project, investigating a Storage Platform for the Integration of Renewable Energy in the Island of Ireland. Her QUB SPIRE2 team has developed a diagnostic software for identifying the source of oscillations which has been tested and validated in Eirgrid & System Operator Northern Ireland. Her team has won the Best Graduate Student Poster Award at the prestigious 2021 IEEE Power and Energy Society General Meeting. She contributed data analytics expertise as PI or Co-I for projects, including EU Horizon 2020 ‘Future-Proof’, British Council ‘TIIWAM’, £11 Million Ofgem low carbon networks ‘Smart Street’, and EPSRC industrial CASE ‘load forecasting’. She is a past director of QUB’s MSc in Electrical & Electronics Engineering, and an Associate Editor of Energy Conversion & Economics (IET).