Machine Learning Redefining Energy Industry Analytics

wind farmThe rise of renewable generation is steadily redefining the relationships between energy suppliers and distributors because every plant on the network is now a data node and the flow of energy is no longer entirely a one way street. This creates an opportunity for machine learning toolset providers.

Exploiting data that springs from distributed cogeneration is becoming an important source of competitive advantage. Industry pundits now talk about smarter energy ecosystems in which both supply and demand are weighed up every few minutes in an effort to optimise returns against a dynamic market.

More specifically, in the solar energy sector, the commoditisation of photovoltaic cell technology is seeing steadily eroding reseller margins even though adoption is gathering pace. So the industry is looking for other ways to create value and remain competitive. Leveraging data points created by networks of solar systems is one approach. This can range from optimising storage battery usage through to monitoring the state and positioning of the hardware.

IBM has been working with the U.S. Department of Energy to provide better numerical weather modelling in order to balance solar generation against other energy sources. Smart metering and networking fully opens the possibility of remote monitoring and aggregation of solar energy sources into the grid. Machine intelligence could therefore enable virtual energy companies in the future.

On the fossil fuel side of the equation, companies such as BP are investing in machine learning tech as a consequence of lessons learned in the wake of the horrific loss of the Deepwater Horizon platform. The aim is to have far better analytics on hand to manage oil field diagnostics, in order to avoid risks to oil field workers and the environment. There are also opportunities to deploy data science to manage and analyse the vast amounts of data that arises from oil basin prospecting.

Gains from machine intelligence technologies within the energy sector will become increasingly significant. Most importantly these tools will better enable efficiencies and scale in the renewable energy scene. That’s good for all of us.