Why Data Is Essential For The Big Oil Transformation

The Big Oil Transformation

“This is a very bleak year, but I am more confident than ever for the clean energy transition.”

Those are the words of the International Energy Agency’s Executive Director, Faith Birol, speaking in 2020. The IEA figurehead recognises that the landscape that once favoured fossil fuel providers so well has changed. Big Oil is facing a shake-up like never before.

As suppliers with giant environmental footprints target net-zero emissions, what can they do to ensure a successful energy transformation? One former fossil-fuel provider has already proven that going green is possible, but that data must play a central role.

Big Oil has to navigate a new political and economic landscape

2020 has seen an acceleration of the carbon-neutral agenda. In January, the European Parliament approved the EU’s Green New Deal – pushing for a climate-neutral bloc by 2050, April saw COVID-19 force oil prices below zero, and President Xi Jinping announced that China will hit net-zero by 2060 in September.

Society is becoming increasingly carbon-conscious, and with political pressures mounting, most energy majors recognise that now is the time to change. Heavyweights like BP, Shell and Total have all recently announced radical decarbonisation programmes, with BP reporting that global oil demand may have peaked in 2019. 

In a break from tradition, markets are now punishing the companies who lack sustainable investment goals. The market capitalisation of ExxonMobil, who remain staunch in their fossil-fuel commitments, was recently overtaken by NextEra’s, the world’s largest wind and solar provider. With institutional investor sentiment changing, it seems the ‘black to green’ transition may no longer be an ethical choice, but the smart economic decision.

The world’s most sustainable company is powered by data

Yet, with futures binding companies to fossil-fuels for decades to come, how can Big Oil successfully remodel their entire asset-base? Perhaps, they should ask Ørsted.

Named one of the top 20 business transformations of this decade, Ørsted has renewed their business from an oil and natural gas provider to the world’s leading supplier of offshore wind, achieving this feat in just 12 years.

Formerly known as DONG (Danish Oil and Natural Gas) Energy, in 2008 Ørsted announced a new focus on renewables, targeting 85% clean-energy supply by 2040. However, that same year, an equal proportion of their energy capacity was in fossil fuels with the company managing a small offshore wind portfolio. The change required was enormous and four years later, the outlook was bleak. Ørsted published a 37% year on year decline in EBITDA and held the record for Danish corporate net-debt at the time.

Fast-forward to 2020 and Ørsted is now the ‘most sustainable company in the world’. The transformation seems almost miraculous, having met their 2040 target 19 years in advance whilst posting record operating profits along the way.

So, what helped them achieve such rare transformational success? A clear company vision? Certainly. Excellent leadership and decision-making? Definitely. Yet, one of Ørsted’s most pivotal assets is too often unsung, data. Data helped Ørsted reduce the risks associated with a rapidly changing organisation, putting the right information in the hands of decision-makers targeting a greener corporate vision.

A data-driven value chain

The International Renewable Energy Agency (IRENA) defines digitalisation as ‘converting data into value for the power sector’, believing digitalisation is crucial for the industry’s renewables transformation. IRENA understand that good data underpins digital, so do Ørsted.

In 2012, energy generated from offshore wind was more expensive than any other renewable. Reducing operating costs whilst building out wind capacity was Ørsted’s number one priority.

World-first data to improve turbine design and layout

First, they needed to make turbines taller. A larger turbine results in greater power output, helping to reduce the number of units required and subsequent operational costs. 

Ørsted needed information on where to make structural improvements. Leading a pioneering study generating data on the performance of over 1,000 turbine foundations, they discovered previous designs were insufficient for load-bearing and limited structural size. New foundation designs are now cheaper to produce, transport and install, with modern turbines taller than the Gherkin able to power 7,100 homes.

A taller turbine may produce more energy, but only if placed in the best location. Farm layout is crucial as wind effects from neighbouring turbines deplete power output. Ørsted produced wind flow data at unprecedented resolution by introducing ground-breaking offshore radar systems. Using this data to model 3D wind improved power output and ensured future energy forecasts were as accurate as possible, helping manage supply variability.

Digital turbines reduce maintenance costs

However, managing farms of 200m tall turbines creates a new problem: maintenance. Unplanned maintenance results in temporary shutdowns. Remediation is very expensive and inspection costs only increase as turbines get larger. 

Every turbine in an Ørsted wind farm is equipped with thousands of sensors, each generating real-time data on turbine condition, stress, pitch and yaw. LiDAR data is used to monitor wind turbulence and is even made publicly available, helping to forecast future energy generation, manage variability, and further monitor asset stress. 

More recently, drones are used to scan turbine blades, generating a sea of data on blade condition and reducing operational maintenance times from two hours to 20 minutes. All this data on asset condition helps Ørsted model predictive maintenance, maximising data ROI and further reducing costs by preventing unexpected disruptions.

Giving customers the data they value

Variable renewables can create supply-and-demand gaps. Low winds reduce output and stormy conditions can result in temporary farm shut offs. Ørsted manage supply variability with timely energy meter monitoring for customers and the provision of RBR (renewable balancing reserve). 

RBR allows energy-intensive clients to monitor their usage volatility and automatically informs them of supply and demand imbalances. Customers then alter their consumption accordingly, either capitalising on cheaper energy or reducing consumption during periods of high demand. This data provides significant cost-savings to clients, whilst also helping Ørsted manage their variable energy generation.

Companies wanting to change need to understand the value of data

In six years, the price of generating offshore wind power has fallen by 63%. Ørsted have become data-driven across their entire value-chain, from design and construction, operation and maintenance, to supply. Without understanding the value of data, they would have likely become another business transformation failure.

The onus now lies with those majors advertising themselves as ‘post-petroleum’. Ørsted have shown that it is possible to go from black to green, but data must lead every step of the way.

We help organisations value their data, so they can manage it and treat it like a tangible asset. If you are interested in learning more about data valuation, get in touch.