As prices drop and competition intensifies in the world of solar and wind, can generators use machine learning to maintain healthy margins?
Imagine looking at a graph of your home’s energy usage and knowing exactly what's shaping it. Would you find this information valuable? Bidgely is betting yes and has the machine learning capability to deliver.
The days of easy oil are over. No longer can a wildcatter don a hardhat, set up a derrick, and strike it rich in Oklahoma. Operators must now use 3D printing to unlock hard-to-reach resources.
How will predictive maintenance impact NRG's competitive positioning?
By collecting data and utilizing machine learning, the midstream oil and gas industry is improving operational efficiency.
Given the importance of addressing climate change and adding renewable generation to the energy grid, Xcel Energy is using machine learning to overcome the challenges of the intermittent nature of wind power.
In 2015 and 2016 the UK Government took a new approach to attract interest to its oil &amp; gas resources, adopting an open innovation model as a short and long term value driver in the country’s energy sector. First steps included large investments in acquisition of seismic data to be later published openly to academia and companies. Further measures included the creation of an oil &amp; gas national data repository to provide enhanced and trusted data on the widest possible terms. In this essay, I describe the UK Government’s incentives to adopt this megatrend; additionally, some further questions are outlined in relation to the sector’s motivations to further commit to this development process.
“Data is just like crude. It’s valuable, but if unrefined it cannot really be used.” 
Sunrun faces the unintended consequences of the US solar market's shift toward protectionism, a paradigm that can severely undermine the very industry it intends to protect.
Rio Tinto, the second largest diversified mining company in the world, combats different types of climate change risks across its geographically diverse global footprint.