Tag: energy

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Microsoft and Eneco team up to drive sustainable business transformations: powering the cloud with clean energy

New work on offshore wind energy

ROTTERDAM, Netherlands, and REDMOND, Wash. — May 23, 2019 — On Wednesday, Microsoft Corp. announced a new wind energy agreement in the Netherlands. Microsoft will purchase 90 MW from the massive 731.5 MW offshore wind project, Borssele III/IV, from Dutch sustainable energy company and wind farm developer Eneco. Eneco will provide Microsoft’s datacenters with green power for 15 years starting in 2022.

This is Microsoft’s second purchase of wind energy in the Netherlands in a year, which brings its total wind energy purchases to 270 MW in the Netherlands — one of the largest corporate renewable energy portfolios in the country.

“Tech companies are facing the challenge to reduce their carbon footprints, mostly due to the vast energy consumption of their datacenters,” said Hans Peters, chief customer officer, Eneco. “A global frontrunner like Microsoft does not see this as a challenge, but as an opportunity to boost the energy transition. We are proud we can help them switch to a sustainable, smart and clean energy supply in the Netherlands. As a result, Microsoft is creating local opportunity, growth and impact while enabling Eneco to continue to invest in large-scale renewable energy projects like Borssele III/IV.”

“Our purchasing of renewable energy helps improve the sustainability of our operations and local grids,” said Brian Janous, general manager, Energy and Sustainability, Microsoft. “This agreement is our 14th renewable energy power purchase agreement and brings our total clean energy portfolio to more than 1.5 GW. The electricity generated will help support the continued long-term growth of Microsoft cloud services delivered from the Netherlands, which is one of 54 Azure regions announced and part of one of the largest and most innovative cloud infrastructures in the world.”

Digital transformation and smart energy solutions

The power purchase agreement is a next step in the ongoing partnership between Eneco and Microsoft. In 2018, Eneco selected Microsoft as its preferred partner for cloud services, signing a three-year deal with Microsoft Azure, which enables Eneco to achieve the company’s goals and ambitions in the area of digital transformation.

About Eneco and Borssele III/IV

Eneco is a Dutch-based company active in the area of sustainable energy and innovation. Together with our customers, partners and employees, we are working on the realization of our mission: everyone’s sustainable energy. We invest in wind farms, biomass power plants, heating and solar parks in order to increase the supply of renewable energy. Eneco is one of the shareholders of Borssele III/IV, an offshore wind project that is currently being developed in the Dutch part of the North Sea. Eneco has also secured a 15-year power purchase agreement for half of the power generated by Borssele III/IV. Previously, Eneco came to agreements with Dutch-based companies Stedin, DSM and Royal Schiphol Group to purchase power from Borssele III/IV.

About Microsoft

Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.

For more information, press only:

Microsoft Media Relations, WE Communications for Microsoft, (425) 638-7777, [email protected]

Arie Spruit, Eneco spokesperson, +316 218 79407, [email protected]

 

Note to editors: For more information, news and perspectives from Microsoft, please visit the Microsoft News Center at http://news.microsoft.com. Web links, telephone numbers and titles were correct at time of publication, but may have changed. For additional assistance, journalists and analysts may contact Microsoft’s Rapid Response Team or other appropriate contacts listed at http://news.microsoft.com/microsoft-public-relations-contacts.

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BP has a new AI tool for drilling into data – and it’s fueling smarter decisions

Deep inside the Earth, miles down in many cases, rock-sealed pockets hold buried treasures.

These hydrocarbon reservoirs are packed with organic compounds that make the world go ‘round. When the contents are extracted and refined, the resulting oil and gas help light cities, transport people and run industries.

For some engineers at BP, Job One is locating the reservoirs. Job Two is accurately predicting what percentage of hydrocarbons are retrievable, also known as “recovery factor.”

Traditionally, that task has been iterative, resource-heavy and can have an element of human bias. Data scientists, tapping their own expertise and experiences, may try six or seven different algorithms as they work to dial in the best prediction model. This can take weeks.

But by using Azure Machine Learning service, BP is working to reduce the time needed to pinpoint prediction models while also boosting the productivity of its data scientists. Automated machine learning empowers customers to identify an end-to-end, machine-learning pipeline for any problem.

Transform recently caught up with Manish Naik, BP’s principal for digital innovation, at his London office to learn more about the company’s new method for drilling down into its data.

TRANSFORM: What is the value that BP gains by improving its recovery factor forecasts?

MANISH NAIK: This prediction of recovery factor from underlying data is a crucial activity – the basis of key decisions made by the company that are potentially worth billions of dollars. This data is vast and complex, involving hundreds of geological properties or features.

To complement the current ways of prediction, which tend to have some qualitative input, we decided to explore machine learning to see if we can improve prediction. We sought to answer these questions: Can we improve the quality of the prediction? Can we eliminate some of the human bias?

Manish Naik sits in from of a large window that looks out on a city.
Manish Naik. Courtesy of BP.

TRANSFORM: How do your data scientists use automated machine learning?

NAIK: They give it broad direction. With one line of code, it runs through different algorithms within the prediction family and the different parameter (or variable) combos that previously were manually tested by the scientists. The power of the cloud comes in here. The results are comparable to what the data scientists produced.

TRANSFORM: One line of code, wow. How much time does this save them?

NAIK: Depending on the amount of data, type of activity – such as the prediction or classification – and algorithm family, automated machine learning could potentially reduce the effort down from weeks to days or days to hours.

TRANSFORM: How often is the prediction model that BP developed for recovery factor now used across the company?

NAIK: This model is in production and used by hundreds of subject matter experts globally in BP on a daily basis.

TRANSFORM: As automated machine learning becomes a core tool for BP’s data scientists, what are the larger, potential benefits for the company?

NAIK: It will make data scientists more productive, which means faster time to market for machine-learning (ML) projects

And as data scientists continue to use more and more of automated machine learning, they will develop trust in the output it provides. That can become a starting point for the work of our data scientists. In the future, this will form a part of a robust benchmarking process for all ML projects, thus improving quality.

TRANSFORM: More broadly, in what ways do you foresee Artificial Intelligence (AI) and the cloud further reshaping the oil and gas industry?

NAIK: Oil and gas companies across the value chain – from exploration to retail – generate significant amounts of data. This means there are lots of opportunities to exploit this data using AI, ML and cloud technologies.

In broad terms, there is significant potential for these technologies to help improve the efficiency of our operations and help us make better, more accurate and informed decisions.

Top photo: The logo of BP plc is seen at a BP petrol station in Liverpool on February 7, 2018. (Paul Ellis/AFP/Getty Images)