Changhong Zhao, PhD, Assistant Professor

Department of Information Engineering

The Chinese University of Hong Kong (CUHK)

Google Scholar

PhD students

- Yujin Huang, 8/2023 -

- Bohang Fang, 8/2021 - 7/2025 (expected).

- Heng Liang, 8/2021 - 7/2025 (expected).

- Tong Wu, 12/2019 - 7/2021 (co-advised with Angela Zhang). Cornell Tech (postdoc). University of Central Florida (8/2024).

MPhil student

- Runjie Zhang, 8/2023 - 7/2025 (expected).

Postdocs

- Kaiping Qu, 2/2024 - 3/2025 (co-advised with Yue Chen). Fuzhou University.

- Wei Lin, 8/2021 - 9/2022. PolyU, HKU (postdoc). Chongqing University (1/2025).

- Wanjun Huang, 11/2021 - 8/2022. Beihang University.

- Sidun Fang, 5/2020 - 8/2021. Chongqing University.

Research projects

Joint optimization of distribution network topology and nonlinear power flow.

- Consider an optimal topology and power flow (OTPF) problem in power distribution networks, which jointly optimizes the on/off status of switches on power lines and the generations, loads, and power flows, for more reliable, economical, and sustainable operation.

- Develop OTPF solution algorithms with improved scalability and optimality, considering the practical three-phase unbalanced nonlinear AC power flow models, the uncertainties of renewable generations and loads, and the key reliability indices, e.g., voltage stability, that do not have closed-form expressions.

Machine learning for reliable and efficient power system operation.

- Develop a neural-network-based machine-learning method to design decentralized nonlinear frequency and voltage feedback controllers for the power grid.

- Steer the power system dynamics to a new equilibrium after drastic changes in operating conditions, while guaranteeing asymptotic stability and transient safety of frequency and voltage.

- Optimize transient performance such as the maximum frequency and voltage deviations, their variances in the presence of noisy power injections and measurements, and the integral of control efforts over time.

Optimizing fast frequency response of distributed energy resources.

- Develop a systematic framework for DERs to provide fast frequency response to the transmission network, under realistic nonlinear AC power flow models and voltage safety limits of distribution networks.

- At the distribution level, the capabilities of DERs to provide fast frequency reserves are quantified under realistic nonlinear distribution network models.

- At the transmission level, the power exchanges at substations are controlled to optimize the rate of change of frequency, frequency overshoot, settling time, and steady state.

Optimizing three-phase power flow via convex relaxation and distributed feedback.

- Develop an (exact) convex semidefinite relaxation to solve for the global optimum of nonconvex optimal power flow (OPF) problems in unbalanced three-phase networks.

- Develop a scalable, computationally efficient algorithm through distributed feedback to approach the OPF solution.