Dynamic Flow Equilibrium of Transportation and Power Distribution Networks Considering Flexible Traveling Choices and Voltage Quality Improvement

TL;DR

This paper develops a dynamic model of transportation and power networks with EV charging, addressing voltage quality issues and proposing a solution for stable equilibrium considering uncertainties and flexible travel choices.

Contribution

It introduces a coupled network model incorporating EV charging behavior, voltage regulation, and a fixed-point equilibrium solution with enhanced computational methods.

Findings

The model effectively captures EV queuing and voltage deviations.

The equilibrium exists under mild conditions.

Simulation results demonstrate robustness under uncertainty.

Abstract

The increasing global spread of electric vehicles (EVs) has introduced significant interdependence between transportation and power networks. Most of the previous studies on coupled networks focus on the formation of equilibrium states between transportation and distribution networks but neglect diminishing the adverse influences of the interaction, especially the voltage quality problems caused by large and fluctuating charging loads. This paper constructs a dynamic interaction model of coupled networks considering both economic and safe operation. First, the dynamic traffic assignment problem is established considering both departure time and route choices, and a dynamic queuing model is designed to describe the EV queuing behaviors at fast charging stations (FCSs). Then, the charging load fluctuation toll is designed as an ancillary toll at FCSs and the bus voltage deviation penalty is considered in optimal power flow to guide the interaction of two networks and tackle the voltage deviation issue. Moreover, the equilibrium state is designed as a fixed-point problem and the solution's existence is proved under mild assumptions. Third, the linearization and convex relaxation techniques are used to improve computational efficiency and a Monte Carlo simulation technique is developed to evaluate the influence of uncertain travel demands on coupled networks. Numerical simulations of coupled networks interaction analyses in deterministic and uncertain conditions are presented.