Changhong Zhao, Associate Professor

Department of Information Engineering

The Chinese University of Hong Kong (CUHK)

Google Scholar

Graduate students

- PhD candidate: Yujin Huang (BE: Tsinghua University).

- 2025 MPhil: Runjie Zhang, PhD student in SEEM at CUHK.

- 2025 PhD: Bohang Fang, to be postdoc at Dartmouth College.

- 2025 PhD: Heng Liang, to join Huawei Hong Kong Research Center.

- 2021 PhD: Tong Wu (with Angela Zhang), University of Central Florida (8/2024).

Postdocs

- To join: Yi Huang (PhD: Wuhan University).

- Current: Zhenyi Yuan (PhD: UCSD).

- 2024 - 2025: Kaiping Qu (with Yue Chen), Fuzhou University.

- 2021 - 2022: Wanjun Huang, Beihang University.

- 2021 - 2022: Wei Lin, Chongqing University (1/2025).

- 2020 - 2021: Sidun Fang, 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 power lines and the generations, loads, and power flows, for more reliable and efficient operation.

- Develop OTPF solution algorithms with improved scalability and optimality, considering unbalanced three-phase nonlinear AC power flow models, uncertainties of renewable generations and loads, and stability indexes without closed-form expressions.

Accelerating large-scale optimization of nonlinear power flow.

- Develop a hierarchical, distributed, spatially recursive algorithm with improved gradient calculation to solve large-scale nonlinear optimal power flow (OPF) problems fast and accurately.

- Integrate hierarchical distributed computing with decentralized neural networks learned from data to predict iterative descent directions of decision variables, for faster solution.

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 power systems.

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

- Reduce the maximum frequency and voltage deviations, their variances under noisy power injections and measurements, and control efforts integrated over time.

Optimizing fast frequency response of distributed energy resources (DERs).

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

- At the distribution level, quantify the capabilities of DERs to provide fast frequency reserves.

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