Spatial dynamics and competitive pricing in charging-as-a-service markets: The quest for cleaner urban development

• A game theoretic model for the spatial pricing game for urban CaaS markets. • An agent-based simulation framework for urban CaaS markets. • Utilization of realistic GIS data for enhanced practical relevance. • Insights into the time-spatial evolution of urban CaaS markets. To redefine the mobility and energy usage patterns in urban cities, the exponential rise in fast-charging loads of electric vehicles (EVs) necessitates a new operating paradigm. In this context, a competitive market emerges where multiple oligarchic Charging-as-a-Service (CaaS) providers vie for profit. However, analyzing such systems, especially in a long-term rolling horizon, poses significant challenges due to complex strategic interactions among multiple entities. This article proposes an agent-based model to analyze the evolution of spatial CaaS markets. Firstly, we propose a strategic pricing game among CaaS firms based on multinomial logit user choice model, and formally prove the existence of Nash equilibria. For equilibrium finding, an iterative algorithm method leveraging the Nikaido–Isoda function and Barzilai-Borwein step size rule is presented. Furthermore, an agent-based market simulation algorithm is developed to model investment decisions of CaaS firm agents based on equilibrium prices. The proposed model is validated using real world data from Shenzhen, and results indicate the efficacy of the equilibrium solving algorithm in reducing computational burden. This study reveals that deregulated competition among CaaS providers, while promoting social welfare, poses risks to long-term sustainability due to regional inequality and market saturation. Timely policy intervention is recommended to guide the sustainable evolution of the CaaS economy.