Electric Power Systems Research · 2022

Towards balanced three-phase charging: Phase optimization in adaptive charging networks

Zixin Ye, Tongxin Li, Steven Low

Electric Power Systems Research

How should electric vehicle demand be assigned across electrical phases?

PXA solves a relaxation of the phase optimization problem, with convergence guarantees under specified conditions. Its MPC implementation updates decisions online. Experiments use adaptive charging network data to examine energy delivery, charging costs, and phase balance.

Research themes

Cite this paper

Zixin Ye, Tongxin Li, Steven Low. Towards balanced three-phase charging: Phase optimization in adaptive charging networks. Electric Power Systems Research, 2022. https://doi.org/10.1016/j.epsr.2022.108322

BibTeX
@article{tongxin-phase-optimization,
  title = {{Towards balanced three-phase charging: Phase optimization in adaptive charging networks}},
  author = {Zixin Ye and Tongxin Li and Steven Low},
  year = {2022},
  journal = {Electric Power Systems Research},
  url = {https://doi.org/10.1016/j.epsr.2022.108322},
  doi = {10.1016/j.epsr.2022.108322}
}
2026Applied Energy

Counterfactual load forecasting with LLM-structured events and representation learning

Yujie Chen, Yifei Gao, Runyao Yu, Yuhe Wu, Guangyu Wang, Yue Chen, Tongxin Li

NACF turns news into structured treatments and estimates load trajectories under alternative event conditions. Reweighting and representation balancing address observed confounding. Experiments examine factual accuracy and interpretable demand perturbations without claiming that unobserved counterfactual outcomes can be directly validated.