OCTOBER 06, 2020
Implementing data-driven processes crucial for the smart grid
Energy Tech Summit 2020 in Vilnius was held this year as a ‘virtual week’ at the end of September with themes ranging from battery technology and e-mobility to automation and AI. We were proud not only to be part in a panel discussion but also to hold a keynote. Here is a short summary of that keynote speech by our sales director Henrik Winberg, on how new technology enables the transformation of the electrical grid.
At the Energy Tech Summit in Vilnius, there was a clear consensus among participants that regulations and other macro deterrents are the main impediments to the essential transformation of the grid, on a regional as well as a global scale. These policies prevent the introduction of new innovations from the start-up ecosystem into the power distribution sector.
However, to continue to move forward towards a modern approach – addressing tomorrow’s challenges – the industry needs to act today. If the current barriers are set aside for a moment, a more interesting question comes into focus: what are the main drivers for creating the smart grid?
The transformation from yesterday’s grid – defined as a one-way energy transmission between producer and consumer – to the grid of the future, where there is a need for a two-way communication of data and energy, requires a whole new set of innovative solutions.
Transforming the grid into a vast network of intelligent nodes will require a significant number of sensors, which inevitably will lead to a huge amount of data collection resulting in a data lake without comparison. The natural next step is to extract information and gain insight from this vast amount of data. That means using analysis based on advanced AI software to tackle the velocity, variety, and volume of data. We need algorithms that will be able to detect complex patterns facilitating for the possibility to anticipate upcoming situations in the grid.
So, AI will be essential when creating the smart grid, but that will not be enough on its own. We need to add the organizational aspect to the equation. We need to talk about working processes and behaviours, and not only information delivery. Information originating from the data lake needs to be contextualized, its meaning transformed into meaningful knowledge, allowing for further implementation in different parts of the organisation and its internal processes. We need less dashboard design and more data-driven behaviour. The contextualization of data and the actions based on that knowledge, are critical steps in the necessary transformation.
The transformation of the electrical grid is a step-by-step process, starting with connecting and collecting grid data, then gaining insights through AI powered analysis, and ending by converting information to meaningful knowledge. And that is what dLab’s dInsight Analytics platform is set up to do for you.