Optimal Capacity Planning for Integrated Charging Microgrids Along Highways Considering Seasonal Fluctuation and Risk Management
Xuetao Liu, Junjie Hu, Ruzhou Li, Chengming Xu, Shunbo Lei
Abstract
Upgrading highway service stations to integrated electric-hydrogen charging microgrids (IEHCMs) has become a significant aspect of coordinated decarbonization in the energy and transportation sectors. However, the increasing integration of variable renewable energy and charging loads intensifies uncertainties within the IEHCMs, potentially leading to energy imbalances on multiple timescales, thereby introducing a need for flexible and reliable options. This paper proposes a novel two-stage capacity planning method for interconnected IEHCMs that considers energy sharing. The method incorporates year-round operation based on a reconstructed full-scenario time series and a conditional value-at-risk model with extreme scenario tail risk characteristics. Photovoltaic generation, interconnected DC lines, and short-term and seasonal hydrogen storage resources are optimally allocated to provide a solution for the IEHCMs that balances reliability and economics, managing fluctuations on multiple timescales while keeping risk below acceptable levels. Numerical results show that the proposed model helps integrate renewables for future highway service stations and provides more reliable planning results.