Dr. Siqi Bu
Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
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12Years (2015-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 January 2023 in Journal of Modern Power Systems and Clean Energy
Journal Article
DDDajun Du
Dajun Du
MZMinggao Zhu
Minggao Zhu
XLXue Li
Xue Li
MFMinrui Fei
Minrui Fei
Siqi BuKLKang Li
Kang Li
+1
Potential malicious cyber-attacks to power systems which are connected to a wide range of stakeholders from the top to tail will impose significant societal risks and challenges. The timely detection and defense are of crucial importance for safe and reliable operation of cyber-physical power systems (CPPSs). This paper presents a comprehensive review of some of the latest attack detection and defense strategies. Firstly, the vulnerabilities brought by some new information and communication technologies (ICTs) are analyzed, and their impacts on the security of CPPSs are discussed. Various malicious cyber-attacks on cyber and physical layers are then analyzed within CPPSs framework, and their features and negative impacts are discussed. Secondly, two current mainstream attack detection methods including state estimation based and machine learning based methods are analyzed, and their benefits and drawbacks are discussed. Moreover, two current mainstream attack defense methods including active defense and passive defense methods are comprehensively discussed. Finally, the trends and challenges in attack detection and defense strategies in CPPSs are provided.
17 January 2020 in IEEE Transactions on Industrial Electronics
Journal Article
Lasantha MeegahapolaSiqi BuDWDarshana Prasad Wadduwage
Darshana Prasad WadduwageCCChi Yung Chung
Chi Yung ChungXYXinghuo Yu
Xinghuo YuOscillatory stability has received immense attention in recent years due to the significant increase of power-electronic converter (PEC)-interfaced renewable energy sources. Synchrophasor technology offers superior capability to measure and monitor power systems in real time, and power system operators require better understanding of how it can be used to effectively analyze and control oscillations. This paper reviews state-of-the-art oscillatory stability monitoring, analysis, and control techniques reported in the published literature based on synchrophasor technology. An updated classification is presented for power system oscillations with a special emphasis on oscillations induced from PEC-interfaced renewable energy generation. Oscillatory stability analysis techniques based on synchrophasor technology are well established in power system engineering, but further research is required to effectively utilize synchrophasor based oscillatory stability monitoring, analysis and control techniques to characterize and mitigate PEC-induced oscillations. In particular, emerging big-data analytics techniques could be used on synchrophasor data streams to develop oscillatory stability monitoring, analysis and damping techniques.
14 October 2015 in IEEE Transactions on Power Systems
Journal Article
YLYi Liu
Yi Liu
WDWenjuan Du
Wenjuan DuLXLiye Xiao
Liye Xiao
HWHaifeng Wang
Haifeng Wang
Siqi Bu
Jun CaoA frequency-based approach is proposed in this paper to size a battery-supercapacitor energy storage system for maintaining power balance of an isolated system with high penetration of wind generation, thus to maintain the grid frequency stability with the stochastic wind power fluctuations being considered. The sizing method proposed makes full use of the combined technical merits of two types of energy storage systems, battery and supercapacitor, as their specific power/energy densities and the corresponding expected life cycle cost/year are different. The power imbalance between hourly dispatched wind power and the corresponding actual real-time wind power output is decomposed into different time-varying periodic components by use of the Fourier transformation. Then two different types of energy storage systems are applied to balance the low-frequency and intermediate-frequency component respectively. A computational procedure is developed in the paper for choosing the optimal cut-off frequencies in determining the range of low and intermediate frequency for sizing the hybrid energy storage system. Comparative studies of a real isolated system in China are presented in the paper to demonstrate the effectiveness of the proposed method.
13 January 2020 in IEEE Transactions on Industrial Informatics
Journal Article
Current maintenance mode for high-speed railway (HSR) power equipment are so outdated that can hardly adapt to the high-standard modern HSR. Therefore, a new possibility is proposed in this paper to update the obsoleting maintenance mode of the HSR power equipment by adopting both predictive maintenance and proactive maintenance. With the combination of data-driven (predictive) and model-based (proactive) approaches, two principal constituents, i.e., the sample generator and the maintenance predictor, are designed. The maintenance predictor which is powered by the long short-term memory recurrent neural network (LSTM-RNN) is developed to realize the goal of predictive maintenance. The sample generator which is formulated by the physical degradation and failure model of HSR power equipment is proposed towards the goal of proactive maintenance. Test results on a gas-insulated switchgear have shown the powerful collaboration between the generator and the predictor, to not only accurately predict future maintenance timing of the switchgear based on historical sample data, but also enrich the data supply proactively to deal with potential data deficiency problems.
9 June 2024 in Journal of Manufacturing Systems
Journal Article
CHChao Huang
Chao HuangSiqi BuHLHiu Hung Lee
Hiu Hung Lee
CCChun Hung Chan
Chun Hung Chan
SKShu Wa Kong
Shu Wa KongWYWinco K.C. Yung
Winco K.C. Yung
1 July 2018 in Renewable Energy
Journal Article
Shiwei XiaKCK.W. Chan
K.W. Chan
XLXiao Luo
Xiao Luo
Siqi BuZDZhaohao Ding
Zhaohao Ding
BZBin Zhou
Bin Zhou
About Me
Siqi Bu (Senior Member, IEEE) received a Ph.D. degree in electrical engineering from the Electric Power and Energy Research Cluster, The Queen's University of Belfast, Belfast, U.K., in 2012.
He continued his postdoctoral research work in The Queen's University of Belfast before entering industry. He was with National Grid UK as an experienced UK National Transmission System Planner and Operator. He is currently an Assistant Professor with The Hong Kong Polytechnic University, Kowloon, Hong Kong, and also a Chartered Engineer with U.K. Royal Engineering Council, London, U.K. His research interests include power system stability analysis and operation control, including wind power generation, plug-in electric vehicle (PEV), high-voltage direct current, FACTS, energy storage system (ESS), and variable speed generator (VSG).
Dr. Bu is an Associate Editor for IEEE Access and CSEE Journal of Power and Energy Systems, a Guest Editor of IET Renewable Power Generation and Energies, and an Editor for Protection and Control of Modern Power Systems. He is the recipient of various prizes due to excellent performances and outstanding contributions in operational and commissioning projects during the employment with National Grid UK. He was also the recipient of Outstanding Reviewer Awards from the IEEE Transactions on Sustainable Energy, IEEE Transactions on Power Systems, Applied Energy, Renewable Energy, and International Journal of Electrical Power & Energy Systems.