Coordinated expansion planning of coupled power and transportation networks considering dynamic network equilibrium
Abstract
As electric vehicles (EVs) rapidly proliferate, they intensify the demands on coupled power and transportation networks (CPTNs), leading to operational challenges such as congestion and overload. To address these challenges and enhance the dynamic performance of CPTNs, this paper proposes a coordinated expansion planning model based on a dynamic modeling method to support the upgrading of CPTNs (in distribution lines, distributed generators, chargers and roads). The spatial–temporal evolution and interaction of power flow in power distribution systems and traffic flow in transportation networks is incorporated into a dynamic network equilibrium, revealing the impact of network expansion on system performance. Uniquely, it replaces static link models with a novel point queue model to better track queuing and charging dynamics at fast charging stations. A scenario-based bi-level stochastic optimization model is formulated to determine the optimal coordinated expansion strategies, considering the diversity of electric and traffic demand scenarios. The optimization problem is solved using a designed marginal-cost-based particle swarm optimization algorithm. Case studies demonstrate the model’s effectiveness in alleviating 95.89% traffic congestion and reducing 4.75% low voltage risk and 28.86% overload risk, marking a significant advancement in CPTN management.
Yuanyi Chen
PhD Student
Simon Hu
Assistant Professor
