Researchers from the Institute for Power Generation and Storage Systems at the Technical University of Braunschweig, Germany, have explored the potential of integrating Vehicle-to-Grid (V2G) technology in the Non-Road Mobile Machinery (NRMM) sector. Their study, published in the journal Applied Energy, investigates the economic and technical feasibility of this approach, which could open new avenues for energy market participation and revenue generation.
The researchers focused on NRMM, such as electric construction equipment and agricultural machinery, which often spend significant time idling. These assets, equipped with substantial battery capacities, could potentially provide grid services and support energy markets. The study introduces a novel methodology that combines Bayesian Optimization (BO) to optimize energy infrastructure and an operating strategy optimization to reduce electricity costs while enhancing grid interaction.
The research highlights the financial opportunities for electric NRMM rental services, demonstrating that V2G technology could generate additional revenue streams. However, the study acknowledges several limitations, including the lack of real-world data on electric NRMM usage and the absence of regulatory challenges related to V2G. The researchers emphasize the need for further studies to improve model accuracy and validate their findings.
For the energy sector, this research suggests that integrating V2G technology in the NRMM sector could enhance grid stability and provide new revenue opportunities. By optimizing energy infrastructure and operating strategies, energy companies could reduce costs and improve their market participation. However, addressing regulatory challenges and gathering more real-world data will be crucial for the widespread adoption of this technology.
The study, titled “Economic and Technical Feasibility of V2G in Non-Road Mobile Machinery sector,” was published in the journal Applied Energy, volume 324, in November 2022. The research team included Rößler Nicolas, Khan Irfan, Schade Thomas, Wellmann Christoph, Cao Xinyuan, Kopynske Milan, Xia Feihong, Savelsberg Rene, and Andert Jakob.
This article is based on research available at arXiv.