Robots and virtual electricity grids

    Etienne Goffin
    Etienne Goffin

    Humans beings need food. Uber understood that and recently started a meal delivery service in the Benelux. But robots also need to be fed. A similar peer-to-peer model could be developed to deliver electricity. Robots could also power their own virtual electricity grids.

    Several electrical engineers believe that artificial intelligence and batteries will soon cause a major upheaval in the energy sector. Dubois et. al. (2017) point out that the emergence of electric vehicles (EVs), combined with the rise of renewable energy production capacities, will strongly impact the way electricity is produced, distributed and consumed in the very near future. Ernst (2017) further explains how large fleet of self-driving EVs can deliver green electricity at cheaper price than the utility grid.

    Belgium and Netherlands are pioneers in smart grids and smart energy management systems. Extremely innovative solutions are being deployed along the Ourthe in Esneux (BE), in the AEG factory in Warstein-Belecke (BE), in the PowerMatching City in Hoogkerk (NL), in the Princess Elisabeth Station in Antarctic (Commission de régulation de l’énergie, 2014). By combining photovoltaics, small hydraulic and wind turbines with mass storage batteries, we can already get rid of the electricity grid.

    The development of cost-effective mass storage batteries brings new ways to transport energy from point A to point B. For instance, self-driving cars and trucks could go to the wind farms to harvest electricity and deliver it where needed. Similarly, boats could replace underwater cables and harvest energy where it is abundant (Scharff & Ernst, 2017). These decentralized systems are much more agile and flexible than the conventional utility grids. They will become viable business models as the price of batteries decreases and their energy density increases.

    The impact of virtual electricity grids would be considerable for both for the transport and distribution of energy:

    • Self-driving vehicles could be used to load and unload electricity. Cars could be booked online (following Uber’s model) to drive autonomously to charging stations (shared in a similar fashion than rooms on Airbnb) and deliver electricity to places disconnected from the grid (O’Connel et. al., 2011; Scharff & Ernst, 2017). According to Damien Ernst, if the 5 million cars currently on the roads in Belgium were all EV, it would be sufficient to transport twice the total daily electric consumption of the whole country.
    • Abandoned oil and gas platforms in the North Sea could be transformed into facilities that convert electricity from offshore wind farms into hydrogen and synthetic gas (Jepma, 2015). After the closing of nuclear power plant, container ships could come to Antwerp or Rotterdam to discharge green energy collected where it is cheap to produce (e.g. in international waters, deserts or mountains).

    With a combination of new technologies, existing infrastructures and means of transport are excepted play a very different role in the future of energy supply.

    SOURCES:

    Caramanis, M. and Foster, J. M. (2009). Management of electric vehicle charging to mitigate renewable generation intermittency and distribution network congestion. Proceedings of the 48th IEEE Conference on, pages 4717–4722. IEEE.

    Commission de régulation de l’énergie (2014). Les projets de microgrids dans des quartiers ou des zones commerciales. Smart Grids.

    Dubois, A., Wehenkel, A., Fonteneau, R., Olivier, F., and Ernst, D. (2017). An App-based Algorithmic Approach for Harvesting Local and Renewable Energy Using Electric Vehicles. Proceedings of the 9th International Conference on Agents and Artificial Intelligence, 187-197.

    Ernst, D. (2017). Uber-like Models for the Electrical Industry. Keynote presentation.
    http://orbi.ulg.ac.be/handle/2268/205035

    Jepma., C. (2015). Smart sustainable combinations in the North Sea Area (NSA): Make the energy transition work efficiently and effectively. Energy Delta Institute.

    O’Connell, N., Wu, Q., Østergaard, J., Nielsen, A. H., Cha, S. T., and Ding, Y. (2011). Electric vehicle (ev) charging management with dynamic distribution system tariff. Innovative Smart Grid Technologies (ISGT Europe), 2011 2nd IEEE PES International Conference and Exhibition on, 1–7. IEEE.

    Olivier, F., Aristidou, P., Ernst, D., and Van Cutsem, T. (2016). Active management of low-voltage networks for mitigating overvoltages due to photovoltaic units. IEEE Transactions on Smart Grid, 7(2):926–936.

    Palensky, P., Widl, E., Stifter, M., and Elsheikh, A. (2013). Modeling intelligent energy systems: Co-simulation platform for validating flexible-demand ev charging management. IEEE Transactions on Smart Grid, 4(4):1939–1947.

    Scharff, C. and Ernst, D. (2017). Les batteries vont bouleverser notre quotidien. L’Echo 05/01/2017.

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