How machine learning could help countries keep up with energy demand

How machine learning could help countries keep up with energy demand

Date: 11 November 2018

Artificial Intelligence (AI) is among the group of emerging technologies that’s predicted to transform the way the world will work in the future. 

Machine Learning (ML) is usually what most people are describing when discussing AI.  This widely-used method relies on huge amounts of statistical data and the computers ‘learn’ or work-out all the potentially unique options of the subject and provide potentially new outcomes.

If such data-crunching were done by a human, it would take years, yet Machine Learning can achieve these results in hours.

One of the most enticing aspects of employing this technology comes in when looking at increasing the efficiency, and management of power systems, as researchers are looking to the future and plan on scaling smart energy grids.

The benefits of applying Machine Learning (ML) to Energy Grid designs, mean that such a system that is carefully planned & built out over time, with each Data Node (a point or device where information is collected or received) is connected permanently in real-time to all the other elements of the ‘Smart Super-Grid’.

Through generation, storage, and load balancing, to the control system management, an AI controlled system could provide all the data necessary to run and operate a mixed supply power generating and distribution system; balance load against demand, making such a design, the most efficient form of energy generation and distribution.

So, what can we expect to experience with the advent of AI in power systems?

Machine learning has the potential to solve the problem of processing and analysing data collected by smart sensors and producing real-time analysis to spot patters and anomalies in datasets. This computing power is set to revolutionise demand and supply of energy by improving generation management, optimising assets, using analytics to predict and identify outages, and understand consumer behaviour.

AI also presents opportunities for new ways of building plants in places previously not possible. By use of local energy storage, demand, and supply being managed by Artificial Intelligence (AI) could provide huge cost savings, along with a decreasing carbon foot-print.

Scientists continue to develop, and refine energy storage solutions, and the continue refining efficiency of Solar Panel (PV), Wind, Marine /Tidal technologies. Along with the progress in development of long-distance Energy Transmission, the addition of a new Control System which employs real-time internet connected Artificial Intelligence (AI) which itself is likely to make use of Quantum Computing would be the final element required to create a new system of delivering power to the world in the coming years.