广大师生：
bat365中文官方网站“海内外优秀青年学者论坛”，旨在面向全球邀请拥有不同学术背景的青年才俊，围绕国际科学前沿、热点研究领域以及行业产业的技术问题等展开探讨和交流。希望籍此平台，互相启迪、开拓视野，增强国际交流与合作，促进双方共同发展。
一、论坛时间：2023年11月17日（星期五）
二、论坛地点：bat365中文官方网站五山校区9号楼225报告厅
三、论坛议程
时间 | 议程 | 内容 |
9:00—9:10 | 开幕 | 致欢迎词，介绍主讲嘉宾 |
9:10—10:00 | 学术报告1 | 题目：电力系统稳定-换流器并网影响及其构网能力的发展 |
10:00—10:30 | 学术报告2 | 题目：铁基纳米晶磁芯在感应式无线充电系统中的应用研究 报告人：罗志超博士（bat365中文官方网站 准聘副教授） |
10:30—11:00 | 学术报告3 | 题目：大规模风电并网的电力系统不确定性优化研究。 报告人：林镇佳博士（香港理工大学 博士后） |
欢迎广大师生参加。
电力学院
2023年11月14日
学术报告1
讲座题目：
电力系统稳定—换流器并网影响及其构网能力的发展
内容摘要：
换流器引起的稳定性问题已被纳入电力系统稳定分类当中。此外，换流器的构网能力已受到电力系统的重视。本报告就上述两点在背景和发展上展开探讨和交流。
学术报告2
讲座题目：
Research on the performance of the Fe-based nanocrystalline core in the inductive power transfer system
内容摘要：
MnZn-based ferrite materials like the EPCOS N87 or K2004 are commonly used as magnetic cores in inductive power transfer (IPT) applications. However, the performance and the reliability of IPT systems are limited by ferrite’s intrinsic brittleness and low flux density saturation point. On the other hand, nanocrystalline materials, such as FeCuNbSiB, present several advantages that make them attractive for IPT applications. Firstly, compared to ferrite, nanocrystalline ribbons are mechanically more robust and can be formed into various geometries. This allows for a more robust, reliable, and flexible design. Second, it has a higher relative permeability, which reaches values up to 300 000 and is several orders of magnitude higher than that of ferrite. Moreover, nanocrystalline alloys saturate at 1.25 T, which is more than twice the saturation point of ferrite. Recently, a novel structure of Fe-based nanocrystalline, called nanocrystalline flake ribbon, is proposed which can effectively reduce the eddy current loss in the core in the high-frequency application. In this webinar, the magnetic characteristic comparison between ferrite N87 and nanocrystalline cores will be presented under different temperatures. The manufacturing process and the magnetic performance of the nanocrystalline flake ribbon core will be discussed. Furthermore, the design consideration of the 11 kW nanocrystalline-based IPT system and its thermal analysis will be introduced.
报告人简介：
Zhichao Luo (S’16-M’19) received the B.S. degree in automotive engineering from the South China University of Technology, Guangzhou, China, in 2014. He received the Ph.D. degree in automotive engineering from Tongji University, Shanghai, China, in 2019. From 2019 to 2021, he was a Postdoctoral Fellow with the Department of Electrical and Computer Engineering at the University of Toronto, Canada. From 2021 to 2023, he worked as a Postdoctoral Research Associate at the University of Cambridge, U.K. He also joined the Trinity College as a Postdoctoral Society Fellow at the University of Cambridge. In 2023, he joined the School of Electric Power Engineering at the South China University of Technology, Guangzhou, China, where he is currently an Associate Professor. He has also served as the industry liaison chair of TC9: Wireless Power Transfer Systems in PELS.
His current research interests include wireless power transfer technologies, high frequency magnetic components, novel soft magnetic material, magnetic field modeling, and power electronics in electric vehicles.
学术报告3
讲座题目：
Researches on Uncertainty Optimization for Power Systems with Large-scale Wind Power Integration
内容摘要：
This presentation will delve into the research surrounding uncertainty optimization for the power systems with large-scale wind power integration. As the penetration of wind energy into power systems steadily increases, the importance of effectively handling the uncertainties of the renewables becomes increasingly prominent. The report will talk the cases of robust optimization and distributionally robust optimization methods in providing robust solutions for the power systems under high penetration of renewables. Additionally, the application of AI-based deep reinforcement learning methods in power system optimization will be explored.The focus of this talk will be on how the integration of traditional mathematical optimization and data-driven methods can lead to more reliable and efficient power systems.
报告人简介：
林镇佳，香港理工大学博士后研究员。本硕博毕业于bat365中文官方网站电力学院，主要从事考虑可再生能源并网的不确定性优化、数据驱动决策分析及其在电力/能源系统的应用研究。近五年以第一/通讯作者发表SCI/EI 论文10余篇，核心参与国家重点研发计划、国家自然科学基金重点项目、面上项目等多个国家级、省级项目。2019年入选广州市“菁英计划”项目；2022年入选香港“创新及科技基金”研究人才库；能源国际学术会议ICAE 2022&2023, CUE 2022&2023, CEN 2023秘书及分论坛主席；期刊PCMP(SCI/EI Index)青年助理编辑；期刊Energy Proceedings青年助理编辑；AEii国际应用能源协会秘书；能源公众号“2C能者无疆EnerarXiv”负责人。同时，担任多个IEEE Transactions, Applied Energy, CSEE JPES等SCI期刊审稿人。