Frequency Control Ancillary Services and Bidding in the National Electricity Market (国家电力市场中的频率控制辅助服务和竞标)

光华讲坛——社会名流与企业家论坛第6691期

主题：Frequency Control Ancillary Services and Bidding in the National Electricity Market (国家电力市场中的频率控制辅助服务和竞标)

主讲人：澳大利亚新南威尔士大学 莫华东教授

主持人：西南财经大学 管理科学与工程学院副院长 肖辉

时间：12月19日10:00

地点：柳林校区通博楼D301会议室

主办单位：管理科学与工程学院

主讲人简介：

Dr. Huadong Mo (IEEE SMC Early Career Award Receptor 2024) joined the University of New South Wales in Australia as a lecturer in 2019 and was promoted to senior lecturer in 2021. He is currently the coordinator of the Systems Engineering Discipline under the School of Systems and Computing. He was previously a postdoctoral fellow at the Swiss Federal Institute of Technology Zurich. Dr. Mo obtained a bachelor’s degree in Automation from the University of Science and Technology of China in 2012 and a Ph.D. in Industrial Engineering and Engineering Management from the City University of Hong Kong in 2016.

Dr. Mo has been engaged in research on enhancing better resilience, performance, and security of complex systems with learning-based algorithms, which primarily lay in the emerging field of power and energy systems, cyber-physical systems, and manufacturing systems, leveraging the capacity to collect and analyze data to reveal patterns of system evolution against uncertainties for many years, publishing over 60 SCI and conference papers, as well as one monograph.

Dr. Mo has supervised four doctoral students to graduate, with over 15 doctoral students currently enrolled and serves as a member of the editorial board in approximately 10 relevant SCI journals and international conferences. Dr. Mo is currently the IEEE Senior Member and Chair of the IEEE SMC ACT Chapter.

莫华东博士（IEEE SMC早期职业奖获得者2024）于2019年加入澳大利亚新南威尔士大学担任讲师，并于2021年晋升为高级讲师。他目前是系统与计算学院系统工程学科的协调员。他曾在苏黎世瑞士联邦理工学院担任博士后研究员。他于2012年获得中国科学技术大学自动化学士学位，并于2016年获得香港城市大学工业工程与工程管理博士学位。多年来致力于利用基于学习的算法提高复杂系统的弹性、性能和安全性的研究，主要集中在电力和能源系统、网络物理系统和制造系统筹新兴领域，利用数据收集和分析能力揭示系统在不确定性下的演化模式，发表了60多篇SCI和会议论文，并出版了一本专著。莫博士指导了4名博士研究生，目前在读的博士生超过15名，并担任了大约10个相关SCI期刊和国际会议的编委会成员。莫博士目前是IEEE高级会员和IEEE SMC ACT分会主席。

内容简介：

In this talk, I will first introduce the electricity market background, specifically the frequency control ancillary services (FCAS) market rules and bidding model. Then, I will present the bilevel model, which consists of a) adjusting the bidding strategy for the battery energy storage system to maximize FCAS revenue and b) adjusting the purchased capacity for the National Electricity Market (NEM) Dispatch Engine to minimize overall FCAS cost. I employed the reinforcement learning method to solve the current bilevel model. I will also present two new approaches under construction to accelerate the computation – quantum reinforcement learning and fixed-time gradient dynamics.

在本次讲座中，我将首先介绍电力市场的背景，特别是频率控制辅助服务（FCAS）的市场规则和投标模式。然后，我将介绍双层模型，该模型包括a）调整电池储能系统的投标策略，以最大限度地提高FCAS收入，以及b）调整国家电力市场（NEM）调度引擎的购买容量，以最大程度地降低FCAS的总成本。我采用了强化学习的方法来求解当前的双层模型。我还将介绍两种正在建设中的加速计算的新方法——量子强化学习和固定时间梯度动力学。