Keng Weng Lao

Prof. Keng Weng Lao

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Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 September 2018 in IEEE Transactions on Power Systems
Verified
Journal Article
Closed access
QNQuan Huy Nguyen
Quan Huy Nguyen
Harsha Vardhana PadullapartiHarsha Vardhana Padullaparti
Harsha Vardhana Padullaparti
Keng Weng LaoKeng Weng Lao
Keng Weng Lao
SSSurya Santoso
Surya Santoso
XKXinda Ke
Xinda Ke
NSNader A. Samaan
Nader A. Samaan
Smart inverters provide additional control capability to help optimize the operation of distribution systems. This paper proposes a framework for exact optimal active and reactive power dispatch of distributed photovoltaic (PV) generation, switched capacitors, and tap changers in large multi-phase unbalanced distribution systems. The objectives of the optimal dispatch are minimization of the energy loss, PV active power curtailment, and capacitor and tap changer switching operations, in addition to elimination of voltage violations and reverse power flow. The optimization problem is formulated in rectangular coordinates as a nonlinear, nonconvex problem. Effective computational strategies are proposed to allow the application of predictorcorrector primal-dual interior point method to solve optimization problems in real-time with a large number of constraints and variables, including discrete variables corresponding to switched capacitors and tap changers. The accuracy of the numerical solution and the ability to implement the proposed framework are validated using the unbalanced multi-phase IEEE 34-bus and EPRI 2,998-bus distribution systems with 15-minute load and PV data. The results show a significant loss reduction and complete removal of both voltage violations and reverse power flow.
31 January 2023 in IEEE Transactions on Industrial Informatics
Verified
Journal Article
Closed access
YCYulin Chen
Yulin Chen
Keng Weng LaoKeng Weng Lao
Keng Weng Lao
Donglian QiDonglian Qi
Donglian Qi
HHHongxun Hui
Hongxun Hui
SYShaohua Yang
Shaohua Yang
YZYi Zheng
Yi Zheng
Distributed event-triggered secondary control in microgrids has been widely investigated to improve system efficiency. But most of them are based on consecutive triggering condition monitors, which would in turn increase the computation burden of the system. To this end, this article presents distributed self-triggered algorithmic solutions to the frequency restoration control and active power sharing control of islanded microgrids. Different from event-triggered control schemes, in our self-triggered solutions, each distributed generator is equipped with a local algorithm that enables it to pre-compute the next triggering time instant according to the states at the previous one. Our starting point is to design a triggering condition with a novel estimate error. Then, the next triggering time instant is determined by solving a quadratic equation established based on the triggering condition, rather than monitoring the triggering condition consecutively. Theoretical analysis and simulation results show that the proposed distributed self-triggered secondary controllers can highly reduce the communication and computation costs simultaneously.
19 June 2023 in IEEE Transactions on Power Systems
Verified
Journal Article
Closed access
SYShaohua Yang
Shaohua Yang
Keng Weng LaoKeng Weng Lao
Keng Weng Lao
YCYulin Chen
Yulin Chen
HHHongxun Hui
Hongxun Hui
To maintain the power system balance, flexible load resources have been widely employed to provide operating reserves, which is named demand response (DR). The heating, ventilation, and air conditioning (HVAC) loads cover a high percentage of the total power consumption and have a significant regulation potential that deserves further investigation. To dispatch such dispersed HVACs, distributed control techniques are developed in the DR field due to their flexibility and scalability. However, the distributed DR system is vulnerable to potential cyber-attacks, i.e., false data injection (FDI) attacks, which may lead to DR failure. This article proposes a resilient distributed controller to protect HVACs against FDI attacks. Firstly, an HVAC-based DR system is built by using distributed control to provide operating reserves for the power grid. Then, the adverse effect of FDI attacks is quantified with mathematical derivation. It is found that a small FDI attack can lead to severe power output deviations, which is a lethal problem for DR. On this basis, an FDI attack-resilient distributed controller is designed for HVACs so as to meet the grid's operating reserve requirements even under attacks. Moreover, the convergence of the proposed controller is proved based on the Laplace transform and final value theorem. Finally, case studies validate the effectiveness of the proposed resilient controller.
25 March 2024 in IEEE Transactions on Power Systems
Verified
Journal Article
Closed access
SYShaohua Yang
Shaohua Yang
Keng Weng LaoKeng Weng Lao
Keng Weng Lao
HHHongxun Hui
Hongxun Hui
YCYulin Chen
Yulin Chen
Demand response (DR) is a crucial component of power systems that can offer operating reserves by utilizing flexible loads on the demand side. With the development of communication, information, and control technologies, DR has formed a cyber-physical system. While deep cyber-physical coupling improves the performance of DR, it also introduces cyber-security threats, i.e., deception cyber-attacks (DCAs), which can lead to DR out-of-control and thus threaten the power system's safe operation. To this end, this paper proposes a secure distributed control to safeguard DR against DCAs. First, a cyber-physical DR community is developed based on a distributed control framework for offering operating reserve to power systems. In addition, considering different patterns, the impacts of DCAs on DR are quantified, revealing that different attack patterns can lead to various adverse consequences on DR, such as power deviation, delayed response, power fluctuation, etc. Furthermore, an anti-attack secure distributed control is developed for DR to counteract against arbitrary DCAs. In addition, rigorous proof based on Lyapunov theorem demonstrates that the proposed control can ensure the stability and convergence for the DR power regulation required by power systems, despite arbitrary DCAs. Finally, case studies validate the efficacy of the proposed control method.
5 October 2021 in IEEE Transactions on Transportation Electrification
Verified
Journal Article
Closed access
LLLi Liu
Li Liu
ZZZhipeng Zhou
Zhipeng Zhou
NDNingyi DAI
Ningyi DAI
Keng Weng LaoKeng Weng Lao
Keng Weng Lao
YSYonghua Song
Yonghua Song
The railway power conditioner (RPC) based on the back-to-back modular multilevel converter (MMC), named multilevel hybrid RPC (MHRPC), was proposed to compensate for the power quality problems in traction power supply system (TPSS), such as negative sequence current, reactive power, and harmonics. Since TPSS is a 25 kV medium-voltage system, the phase-shifted pulsewidth modulation (PS-PWM) was chosen for MHRPC considering the number of submodules. However, the conventional PS-PWM suffers from higher distortion in output voltage or extra harmonics in circulating currents when applying to MHRPC. Various approaches were investigated to suppress harmonics, such as modified PWM methods, tailor-made filters, or additional transformers, but all increase control complexity or initial cost. In this article, a 2-D fast Fourier transform (FFT) harmonic model is developed to analyze how the phase displacement between stacks and legs impacts the harmonic distortion. Then an interpolated PS-PWM (IPS-PWM) is proposed, which sets the initial phase of carriers by coordinating four stacks of a single-phase MMC. It provides more output voltage stairs and eliminates the voltage unbalance states between the dc bus and two legs. Thus, MHRPC achieves better performance without extra hardware or increasing switching frequency. Simulation and experiment results verify the effectiveness of the proposed method.
26 August 2022 in IEEE Transactions on Instrumentation and Measurement
Verified
Journal Article
Closed access
LCLIDAN CHEN
LIDAN CHEN
Keng Weng LaoKeng Weng Lao
Keng Weng Lao
YMYongliang Ma
Yongliang Ma
ZZZhe Zhang
Zhe Zhang
Using remote data analysis to estimate smart electricity meters (SMs) and detect SMs’ anomaly has aroused considerable discussion in power industry, because its lower cost and higher efficiency compared with the traditional field calibration. However, the trouble of lacking topology and parameter of the distribution grid and the ill-posed problem in SMs’ error estimation and anomaly detection (AD) are not well-resolved in most energy-conservation-theorem-based SM AD methods. This article presents a sorted Top-N AD mechanism to generate a list of suspicious anomalous SMs. The error estimation model (EEM) only using SMs’ electricity consumption data is investigated. The truncated singular value decomposition regularization with the L-curve optimization (TSVD+L) method is proposed to address the model’s ill-posedness. Three data processing modes, namely, one-pot mode, segmentation mode, and sliding window technique (SWT), are suggested to obtain multiple calculation results for SMs’ error comprehensive evaluation. The top $N$ % SMs in error sequence are proposed for onsite calibration instead of full inspection. The effectiveness and practicality of the proposed method are verified through both the simulation case and practical distribution network application. The results show that the proposed method has higher accuracy in SMs’ AD, compared with the ordinary least-squares (OLS) method, the recursive least-squares (RLS) method, and the Tikhonov regularization (Tik) method.