Smart Charge

The Smart Charge Project was initiated in October 2019 through collaborative efforts between the Computer Science and Computational Engineering Department at UiT, The Arctic University of Norway, and The Lapland University of Applied Sciences in Rovaniemi, Finland. The project was an endeavor funded by Interreg. This project aimed to promote a relationship between electric mobility (e-mobility) and smart homes. The project’s primary focus was energy consumption, load management, and renewable energy utilization within the challenging landscape of Arctic rural areas.

The Smart Charge Project emerged as a response to the need for innovative solutions in regions characterized by limited access to energy resources. Arctic rural areas often grapple with energy scarcity, significantly impacting daily life and potential economic activities. Sustainable tourism in the Arctic, a burgeoning industry, necessitated a reevaluation of energy systems. As a result, the project aimed to address these issues by introducing a novel energy paradigm centered around electric snowmobiles. The Lapland University of Applied Sciences led in developing electric snowmobiles, while a consortium comprising Aurora Powertrains, Saga Energy, Narvik Municipality, Vattenfall, and the Snow Hotel lent their expertise to the project.

Methodology

The Smart Charge Project enlisted the expertise of the AI Group at UiT Narvik, which played a pivotal role in analyzing the electricity requirements for charging snowmobiles. Moreover, the group was instrumental in the development of intelligent control systems. These systems enabled dynamic energy exchanges between residences and snowmobiles, facilitating load balancing. The control system leveraged a multi-agent framework, conceptualizing snowmobiles as self-interested agents capable of diverse charging and discharging strategies. The project harnessed reinforcement learning to optimize economic outcomes amidst intricate constraints, a dynamic approach that adapts to evolving conditions.

Results

The project concluded in June 2023, marked by the presentation of findings at the 27th International Conference & Exhibition on Electricity Distribution (CIRED 2023) in Rome. A paper titled “Using Light Electric Vehicles for V2G Services in the Arctic” showcased innovative machine-learning techniques for single- and multi-step predictions. This paper presented a fundamental component of the project’s control and management system. Furthermore, Bernt Bremdal delivered a compelling presentation titled “Predicting Peak Prices in the Current Day-Ahead Market,” introducing a pioneering approach to forecasting price fluctuations in Norwegian price zones influenced by developments in European price zones.

The contributions of the AI Group extended beyond these achievements, encompassing research on federated machine learning for home energy management and load predictions. Another noteworthy endeavor explored edge computing and time series clustering to optimize the control and management of demand-response operations.

Conclusion

The Smart Charge Project embodied collaborative excellence, innovation, and a steadfast commitment to addressing pressing energy challenges. The research outcomes offer promising avenues for the future of energy management in remote and demanding environments. The project’s contributions are expected to inspire further exploration and innovation within sustainable energy solutions.