Volume 59

Refined Strategies and Benefit Evaluation of “Vehicle-Building-Grid” Collaborative Optimization in Shenzhen Business Districts Cheng Fan, Jiena Cai, Yonghang Xie, Yutian Lei

Abstract

The rapid growth of electric vehicles (EVs) presents challenges to power system stability. This study investigates six core business districts in Shenzhen, using a 500-meter spatial grid and proposing a fine-grained “vehicle-building-grid” coordinated optimization framework to enhance urban energy resilience. Commercial building energy profiles are modeled using prototype buildings, while EV load data are generated via Monte Carlo simulations. Incorporating time-of-use electricity pricing and regional energy patterns, the study regulates unordered EV charging behavior to quantify EV flexibility and emergency power potential. Results show that optimized charging reduces energy costs by an average of 2.68% at the district level and by 0.81%–3.59% at the spatial grid level. When minimizing the peak-valley load gap, average reductions reach 37.7%, with spatial grid-level reductions ranging from 17.18% to 42.63%. The study provides both theoretical and empirical support for planning distributed urban energy storage systems.

Keywords business districts, electric vehicles, Monte Carlo simulation, optimization control, benefit evaluation