2026
Unveiling the Full Potential of Mobility-Aware Coordinated Electric Vehicle Charging for Regional Grid Resilience
Jingchun Wang, Yi Ju, Lunlong Li, Zhe Wang, Xinyi Wang, Bhuvan Atluri, Jinhua Zhao, Scott J. Moura
Transportation Research Board (TRB) Annual Meeting 2026
An extended study quantifying the maximum potential of leveraging EV demand flexibility to mitigate distribution network overloading, incorporating broader mobility datasets and network constraints.
Unveiling the Full Potential of Mobility-Aware Coordinated Electric Vehicle Charging for Regional Grid Resilience
Jingchun Wang, Yi Ju, Lunlong Li, Zhe Wang, Xinyi Wang, Bhuvan Atluri, Jinhua Zhao, Scott J. Moura
Transportation Research Board (TRB) Annual Meeting 2026
An extended study quantifying the maximum potential of leveraging EV demand flexibility to mitigate distribution network overloading, incorporating broader mobility datasets and network constraints.
Unveiling the Full Potential of Mobility-Aware Coordinated Electric Vehicle Charging for Regional Grid Resilience
Yi Ju, Lunlong Li, Jingchun Wang, Scott J. Moura
American Control Conference (ACC) 2026
Quantifies the maximum potential of leveraging EV demand flexibility to mitigate distribution network overloading through a scalable coordinated charging framework, demonstrated on high-resolution mobility data at regional scale.
Unveiling the Full Potential of Mobility-Aware Coordinated Electric Vehicle Charging for Regional Grid Resilience
Yi Ju, Lunlong Li, Jingchun Wang, Scott J. Moura
American Control Conference (ACC) 2026
Quantifies the maximum potential of leveraging EV demand flexibility to mitigate distribution network overloading through a scalable coordinated charging framework, demonstrated on high-resolution mobility data at regional scale.
Trajectory-Integrated Accessibility Analysis of Public Electric Vehicle Charging Stations
Yi Ju, Jiaman Wu, Zhihan Su, Lunlong Li, Jinhua Zhao, Marta C. González, Scott J. Moura
Sustainable Cities and Society 2026
Introduces a novel accessibility metric (TI-acs) that incorporates individuals' travel trajectories to assess public EV charging station accessibility for ~6 million Bay Area residents, revealing significant spatial and racial disparities beyond conventional home-based metrics.
Trajectory-Integrated Accessibility Analysis of Public Electric Vehicle Charging Stations
Yi Ju, Jiaman Wu, Zhihan Su, Lunlong Li, Jinhua Zhao, Marta C. González, Scott J. Moura
Sustainable Cities and Society 2026
Introduces a novel accessibility metric (TI-acs) that incorporates individuals' travel trajectories to assess public EV charging station accessibility for ~6 million Bay Area residents, revealing significant spatial and racial disparities beyond conventional home-based metrics.
Coordinating Multiple UPS Batteries in Datacenter for Load Flexibility and Cost Reduction
Lunlong Li, Yang Pu, Yi Ju, Ziqi Hu, Zhe Wang
Energy and Buildings 2026
Investigates coordination strategies for multiple UPS batteries in datacenters to provide load flexibility and reduce electricity costs, leveraging energy storage for demand-side management.
Coordinating Multiple UPS Batteries in Datacenter for Load Flexibility and Cost Reduction
Lunlong Li, Yang Pu, Yi Ju, Ziqi Hu, Zhe Wang
Energy and Buildings 2026
Investigates coordination strategies for multiple UPS batteries in datacenters to provide load flexibility and reduce electricity costs, leveraging energy storage for demand-side management.
Optimal Battery Sizing Using Stochastic Programming to Consider Building Load Variation and Peak Demand Charge
Parastoo Mohebi, Ziqi Hu, Lunlong Li, F. Golzar, Zhe Wang
Energy Conversion and Management 2026
Proposes a stochastic programming approach for optimal battery sizing that accounts for building load variation and peak demand charges, enabling more cost-effective energy storage deployment.
Optimal Battery Sizing Using Stochastic Programming to Consider Building Load Variation and Peak Demand Charge
Parastoo Mohebi, Ziqi Hu, Lunlong Li, F. Golzar, Zhe Wang
Energy Conversion and Management 2026
Proposes a stochastic programming approach for optimal battery sizing that accounts for building load variation and peak demand charges, enabling more cost-effective energy storage deployment.
2025
Shaving Monthly Peak Load by Overestimating Future Load in Microgrid Model Predictive Control
Lunlong Li*, Yi Ju, Scott J. Moura, Zhe Wang (* equal contribution)
Building Simulation Conference 2025
Proposes a model predictive control strategy for microgrids that intentionally overestimates future load to reduce monthly peak demand charges, demonstrating peak shaving benefits for building energy management.
Shaving Monthly Peak Load by Overestimating Future Load in Microgrid Model Predictive Control
Lunlong Li*, Yi Ju, Scott J. Moura, Zhe Wang (* equal contribution)
Building Simulation Conference 2025
Proposes a model predictive control strategy for microgrids that intentionally overestimates future load to reduce monthly peak demand charges, demonstrating peak shaving benefits for building energy management.
2024
Quantifying the Impact of Building Load Forecasts on Optimizing Energy Storage Systems
Lunlong Li*, Yi Ju*, Zhe Wang (* equal contribution)
Energy and Buildings 2024
This paper quantifies how building load forecast accuracy impacts the optimization of energy storage systems, providing insights into the trade-offs between forecast quality and storage scheduling performance.
Quantifying the Impact of Building Load Forecasts on Optimizing Energy Storage Systems
Lunlong Li*, Yi Ju*, Zhe Wang (* equal contribution)
Energy and Buildings 2024
This paper quantifies how building load forecast accuracy impacts the optimization of energy storage systems, providing insights into the trade-offs between forecast quality and storage scheduling performance.