As electric vehicle (EV) adoption accelerates, utilizing private EVs as decentralized electricity storage through vehicle-to-grid (V2G) technology becomes increasingly feasible. To optimize electricity grids on the urban or regional scales, understanding the impact of time-of-use (TOU) tariffs on EV charging and discharging behaviors is crucial. This paper introduces a time-electricity-expanded network, where each node representing unique vehicle states, each link between nodes signifies operations like traversing, queuing, parking, and charging/discharging, and each path outlines a travel-activity chain. Focusing on the modeling of EV charging/discharging activities at workplace equipped with V2G chargers, this paper proposes a time-dependent network equilibrium problem and formulates it as a linear programming model, in which individual commuters aim to minimize their own travel-parking-charging-discharging costs. To accelerate solution convergence, a Dantzig-Wolfe decomposition approach is employed for the linear programming model. Numerical validation is conducted using a small-scale travel-parking network example.