Publications
Working Paper
- Ruicheng Cheng, Naihao Shi, Zhaoyu Wang and Zixiao Ma, “Optimal Power Flow for Integrated Primary-Secondary Distribution Networks with Service Transformers,” IEEE Transactions on Power Systems, under review.
Journal Paper
[J15] Liming Liu, Naihao Shi, Dingwei Wang, Zixiao Ma, Zhaoyu Wang, Matthew J. Reno, and Joseph A. Azzolini, “Voltage Calculations in Secondary Distribution Networks via Physics-Inspired Neural Network Using Smart Meter Data,” IEEE Transactions on Smart Grid, early access, 2024. PDF
[J14] Zixiao Ma, Zhaoyu Wang, Yuxuan Yuan and Tianqi Hong, “Singular Perturbation-based Large-Signal Order Reduction of Microgrids for Stability and Accuracy Synthesis with Control,” IEEE Transactions on Smart Grid, early access, 2024. PDF
[J13] Zixiao Ma, Zhaoyu Wang and Rui Cheng, “Analytical Large-Signal Modeling of Inverter-based Microgrids With Koopman Operator Theory for Autonomous Control,” IEEE Transactions on Smart Grid, vol. 15, no. 2, pp. 1376-1387, Mar. 2024. PDF
[J12] Zixiao Ma, Qianzhi Zhang and Zhaoyu Wang, “Safe and Stable Secondary Voltage Control of Microgrids Based on Explicit Neural Networks,” IEEE Transactions on Smart Grid, vol. 14, no. 5, pp. 3375-3387, 2023. PDF
[J11] Zixiao Ma, Yingmeng Xiang and Zhaoyu Wang, “Robust Conservation Voltage Reduction Evaluation using Soft Constrained Gradient Analysis,” IEEE Transactions on Power Systems, vol. 37, no. 6, pp. 4485-4496, 2022. PDF
[J10] Zixiao Ma, Bai Cui, Zhaoyu Wang and Dongbo Zhao, “Parameter Reduction of Composite Load Model using Active Subspace Method,” IEEE Transactions on Power Systems, vol. 36, no. 6, pp. 5441-5452, 2021. PDF
[J9] Zixiao Ma, Zhaoyu Wang, Yifei Guo, Yuxuan Yuan and Hao Chen, “Nonlinear Multiple Models Adaptive Secondary Voltage Control of Microgrids,” IEEE Transactions on Smart Grid, vol. 12, no. 1, pp. 227-238, 2021. PDF
[J8] Jun Fu, Zixiao Ma, Yue Fu and Tianyou Chai, “Hybrid Adaptive Control of Nonlinear Systems with Non-Lipschitz Nonlinearities,” Systems & Control Letters, vol. 156, no. 105012, 2021. PDF
[J7] Jian Xie, Zixiao Ma, Kaveh Dehghanpour, Zhaoyu Wang, Yishen Wang, Ruisheng Diao and Di Shi, “Imitation and Transfer Q Learning-based parameter identification for composite load modeling,” IEEE Transactions on Smart Grid, vol. 12, no. 2, pp. 1674-1684, 2021. PDF
[J6] Qianzhi Zhang, Zixiao Ma, Yongli Zhu and Zhaoyu Wang, “A Two-Level Simulation-Assisted Sequential Distribution System Restoration Model With Frequency Dynamics Constraints,” IEEE Transactions on Smart Grid, vol. 12, no. 5, pp. 3835-3846, 2021. PDF
[J5] Fankun Bu, Zixiao Ma, Yuxuan Yuan and Zhaoyu Wang, “WECC Composite Load Model Parameter Identification using Evolutionary Deep Reinforcement Learning,” IEEE Transactions on Smart Grid, vol. 11, no.6, pp. 5407-5417, 2020. PDF
[J4] Zixiao Ma, Zhaoyu Wang, Dongbo Zhao and Bai Cui, “High-Fidelity Large-signal Order Reduction Approach for Composite Load Model,” IET Generation, Transmission & Distribution, vol. 14, no. 21, pp. 4888-4897, 2020. PDF
[J3] Zixiao Ma, Zhaoyu Wang, Yishen Wang, Ruisheng Diao and Di Shi, “Mathematical Representation of WECC Composite Load Model,” Journal of Modern Power Systems and Clean Energy, vol. 8, no. 5, pp. 1015-1023, 2020. PDF
[J2] Jiao Li, Zixiao Ma and Jun Fu, “Exponential Stabilization of Switched Discrete-Time Systems with All Unstable Modes,” Asian Journal of Control, vol. 20, no. 1, pp. 608-612, 2018. PDF
[J1] Taifang Li, Jun Fu and Zixiao Ma, “Improved Event-Triggered Control for a Class of Continuous-Time Switched Linear Systems,” IET Control Theory & Application, vol. 12, no. 7, pp. 1000-1005, 2018. PDF
Conference Paper
[C1] Zixiao Ma and Baosen Zhang, “Controlling Grid-Connected Inverters under Time-Varying Voltage Constraints,” 2024 IEEE Power & Energy Society General Meeting, Seattle, WA, USA, Jul. 22-25, 2024. Acceptance rate: 50%
[C2] Zixiao Ma, Naihao Shi, Zhaoyu Wang and Wen Fan, “Time-Varying Conservation Voltage Reduction Evaluation with Ground Truth Validation,” 2024 IEEE Power & Energy Society General Meeting, Seattle, WA, USA, Jul. 22-25, 2024. Acceptance rate: 50%