Our vision on the Energy domain can be summarized in the following action lines:
- Empower energy producers to optimize their energy production;
Specific to energy producers, we foresee a number of applications to deal with spikes and drops in energy production. This consists of using AI and data analytics to forecast demand better, and scale capacity accordingly. Furthermore, we apply mechanics from modern portfolio theory to deal with uncertainty in demand as well as supply, creating a system of interrelated nodes that together guarantee a relatively stable production of energy in all but the most extreme situations.
- Empower energy consumers to optimize their energy use;
Specific to energy consumers, we foresee a number of applications around reducing energy waste. Sensors can be used to infer behavior and manage power consumption accordingly. For instance, lights and heating in an office building can automatically be switched off for areas that are not being used, or devices which are idle for large periods can be switched to a low-powered mode until they are needed. Over time, pattern recognition can take place to better match local energy consumption to the actual needs of the consumer, leading to energy savings during downtime without any reduction in experienced comfort. Finally, smart meters can be used to increase awareness about energy costs in a dynamic fashion (higher prices during peak hours) which can stimulate consumers to make efforts to reduce or defer their consumption.
- Optimize supply and demand to eliminate waste of scarce energy resources;
As mentioned, supply and demand are a constant balancing act. However, we believe that there is a lot of potential to optimize this locally, as consumers are more and more frequently becoming ‘prosumers’. In this situation where each consumer is also capable of producing some energy of their own, it becomes less about ensuring adequate production on the whole, but more about matching local excesses to shortages elsewhere. For instance, an excess of solar energy during a drought could be used to cover a shortage in wind energy. By creating a production-consumption system based on agents, multiple agents can arrive at optimal solutions locally without requiring the central governance of a power plant.