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

Arega Getaneh Abate, Xiaobing Zhang, Xiufeng Liu and Dogan Keles

Papers from arXiv.org

Abstract: Integrating electric mobility (electric vehicles (EVs), electric trucks (ETs)) and renewable energy sources (RES) with the power grid is paramount for achieving decarbonization, efficiency, and stability. Given the rapid growth of decentralized technologies and their critical role in decarbonization, two critical challenges emerge: first, the development of a digital platform for operational coordination; and second, rigorous research into their cost-benefit profile. This paper addresses this by presenting a comprehensive cost-benefit analysis (CBA) of an AI-driven operational digital platform (ODP) designed for holistic, cross-sectoral optimization. The ODP aims to enhance energy efficiency, grid reliability, and environmental sustainability. A seven-step CBA framework, aligned with EU guidelines, quantifies economic, reliability, and environmental benefits against capital and operational expenditures, explicitly linking benefit magnitude to AI-driven ODP and optimization efficiencies, such as quantified improvements in market arbitrage from ODP, enabled forecasting, and enhanced operational efficiencies across various services.

Date: 2025-06
References: Add references at CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2506.20631 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2506.20631

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().