Hanno Schoklitsch is the CEO and founder of Kaiserwetter Energy Asset Management.
Communication makes the right points when they promise to accelerate the energy transition and clearly state that Artificial Intelligence, Internet of Things and Cloud Computing can have an important impact on tackling environmental challenges. However, the specific impact on the energy transition is ignored.
For an accelerated energy transition, just more renewables are not enough. Germany, for example, has an installed renewable capacity of almost 120 Gigawatt whilst peak demand is never higher than 75 Gigawatt.
Nevertheless, Germany is far behind its climate targets. You see: We need more efficiency and accurateness in the energy transition. This is above all a data problem, but it is a problem that is easily be resolvable by innovative technology.
The future of energy, driven by IoT and AI
To understand the whole context, we have to see: The future of energy will be marked by the radical decentralization of energy supply, including so-called flexibility options like storage, load management, power-to-heat or power-to-gas.
Virtual power plants will assume a central role. All those technologies will help to realize a demand-side economic approach. This means that the power supply follows the energy demand.
And for this approach Internet of Things (IoT) combined with Artificial Intelligence (AI: Machine Learning, Deep Learning) is key. They will help to optimize the match between regional generation and regional demand – something that is unthinkable without advanced data intelligence.
For more than a century, we have lived in a baseload world which means that a few central megawatt power plants run the whole year, more or less independently from the actual demand. The unintelligent, inefficient usage of dirty energy resources is doubtlessly the main cause of the climate crisis.
Therefore, the energy transition must be seen as a shift towards renewables and energy intelligence. To fulfil the Paris goals, we need a faster energy transition, for sure, but above all, we need a more intelligent energy system.
The Energy Cloud for Nation – our approach to attaining energy intelligence
While most of the energy value chain will be organized in a decentralised way, data collection and analytics must be organised centrally. There are solutions providing national and international governments and authorities with detailed insights into their energy systems based on real-time production.
Planning of new capacities, including renewable generation, storage, grid expansion and load shifting gains a new, unprecedented accurateness. Speeding up energy transition without the risk of false decision-making and failed investments becomes possible.
IoT and AI can help governments and authorities to cope with the increasing complexity of the energy transition – an important point especially for countries that aspire a pioneering role in climate policy but fear the energy transition’s ramifications.
Attracting and activating the needed investment capital is one of the major challenges, and risk mitigation and investment certainty will need to be considered as key. IoT and AI can make a crucial difference.
The Green Revolution – also a digitisation revolution
The combination of IoT and AI will be key drivers for a successful, risk-minimized shift to a green economy in general. Inefficient usage of resources was characteristic of the 19th and 20th centuries.
The digitisation will make it easy to open a new economy mode characterized by the efficient, spatially and timely accurate match between supply and demand. The energy sector will be the front-runner followed by other sectors that use critical resources such as water, agriculture, transportation and so on.
It is based on that reasoning that I am convinced that IoT and AI can make a major contribution to securing the planet for generations to come.