IEEE Energy Sustainability Magazine · 2025

Robust Solar Hosting Capacity for Pasadena's Decarbonization: A Mathematical Program for Robustness Against Uncertainty

Han Xu, Yiheng Xie, Wenqi Cui, Tongxin Li, Steven Low

IEEE Energy Sustainability Magazine

How much distributed solar can a grid accommodate under uncertainty?

The Pasadena case study formulates solar hosting capacity planning as a robust optimization problem. It connects uncertainty in renewable generation and demand to distribution network constraints and practical choices along a municipal decarbonization pathway.

Research themes

Cite this paper

Han Xu, Yiheng Xie, Wenqi Cui, Tongxin Li, Steven Low. Robust Solar Hosting Capacity for Pasadena's Decarbonization: A Mathematical Program for Robustness Against Uncertainty. IEEE Energy Sustainability Magazine, 2025. https://doi.org/10.1109/ESM.2025.3606174

BibTeX
@article{tongxin-solar-hosting,
  title = {{Robust Solar Hosting Capacity for Pasadena's Decarbonization: A Mathematical Program for Robustness Against Uncertainty}},
  author = {Han Xu and Yiheng Xie and Wenqi Cui and Tongxin Li and Steven Low},
  year = {2025},
  journal = {IEEE Energy Sustainability Magazine},
  url = {https://doi.org/10.1109/ESM.2025.3606174},
  doi = {10.1109/ESM.2025.3606174}
}
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.