DeepTech — the term for technologies not focused on end-user services that include artificial intelligence, robotics, blockchain, advanced material science, photonics and electronics, biotech and quantum computing — has been an identified category for investment for as long as the tech industry itself.
Digitalisation has led to radical changes in the distribution of goods and services across various sectors. The tendency is to move from traditional buyer-seller markets to subscription-based "smart" matching platforms, enabled by information and communication technologies. For Energy, the driving force behind this lies in the fact that assets, which were scarce in the past, are now readily abundant, approaching a regime of zero marginal costs. This is also becoming a reality in electrified energy systems, due to the substantial growth of distributed renewable energy sources such as solar and wind, as well as the increasing number of small-scale storage units such as batteries and heat pumps, and the availability of flexible loads that enable demand-side management.
Our UNITY platform proposes a data-driven system architecture, based on a logical (virtual) association of spatially distributed (physical) assets – solar panels that are digitised. By using this approach, we can demonstrate how virtual microgrids can operate as a software-defined energy network (SDEN). Further, the SDEN enables tokenisation of assets and streaming protocol, offering packetised energy management. The system presumes that electrical energy is shared among its members, enabled in the cyber domain by a blockchain protocol. This application, inspired by resource allocation methods used in computer networks, wireless communications, and peer-to-peer internet applications, creates a transactive and interactive grid.
The proposed system
(i) reduces the complexity of current market-based solutions by removing unnecessary and costly mediations and
(ii) balancing the local micro-grid by guaranteeing energy access to all virtual microgrid members according to their individual.