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arXiv · 2506.20631

Cost-benefit analysis of an AI-driven operational digital platform for integrated electric mobility, renewable energy, and grid management

Abstract

Integrating electric mobility, including electric vehicles (EVs), electric trucks (ETs), and renewable energy sources (RES) with the power grid is paramount for decarbonization, efficiency, and stability. A critical gap remains, however: existing smart-grid and e-mobility cost-benefit analysis (CBA) approaches do not yet provide a unified framework for appraising AI-driven operational digital platforms (ODPs) that jointly coordinate EV/ET charging, renewable generation, and grid operations across sectoral and national boundaries. This paper develops a seven-step CBA framework tailored to this class of platform. The framework maps each layer of a multi-layered AI architecture to traceable, monetizable benefit streams-panning economic efficiency, grid reliability, and environmental externalities--while explicitly accounting for AI-specific capital and operational expenditures that conventional appraisals omit. Applied to a ten-year, three-country deployment across Austria, Hungary, and Slovenia, the analysis indicates a robust positive investment case under the modeled assumptions, confirmed through scenario sensitivity analysis, one-way parameter ranking, and probabilistic simulation. Benefit composition and country-level drivers differ systematically across national contexts, yet the economic rationale is preserved in each, reflecting the framework's adaptability to heterogeneous electrification trajectories. The findings indicate the economic viability of AI-driven digital platforms for cross-sectoral energy--mobility integration and highlight the critical role of ODPs in advancing decarbonization in the mobility--power nexus. To that end, they have direct implications for the design and appraisal of digital infrastructure investments under the EU's Fit for 55 and REPowerEU programmes.

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Arega Getaneh Abate, Xiaobing Zhang, Xiufeng Liu, Dogan Keles. 2026-03-22. Cost-benefit analysis of an AI-driven operational digital platform for integrated electric mobility, renewable energy, and grid management. https://arxiv.org/abs/2506.20631

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