• Print
  • Decrease text size
  • Reset text size
  • Larger text size
20/03/2018

Digital Innovation in Energy: Getting the Fundamentals Right

The accelerated pace of digital innovation over the past half-decade has brought on a multitude of new technology. From Robotics, Artificial Intelligence, and Augmented Reality to Predictive Data Analytics, Blockchain, and Digital Twins, technological capabilities are getting more and more sophisticated at an increased rate. Digital innovation in the Information Technology world has led to frequent disruptions in the Energy world, pushing organizations further and further out of routine practices and structures. In such a dynamic business environment, it is easy for an organization to misinterpret digital innovation and implement new technology ineffectively. In order to avoid the pitfalls of misinterpreting digital innovation, an organization must first get the fundamentals right.     

So how can a business navigate through disruptive innovation in the market while remaining competitive?

Digital and Technological Innovations in the Energy Industry

Digital Oilfields are analyzing enormous sets of quantitative and qualitative data produced from an off-shore oil rig. Renewables, distributed generation, and smart grids are redefining the way we procure and transmit power. Blockchain technology with smart contracts are changing the way we think of energy trading back offices. Digital innovation has led to increased knowledge, insight, and capabilities for firms in the energy industry. The latest advancements have allowed successful organizations to align technology with the strategic and commercial objective of the business.

The table below highlights some of the innovative technologies that have impacted the energy industry over the past few years.

 

Oil and Gas

Utilities

Renewables

Upstream

  • Digital Twin technology has enabled precise digital asset simulation by incorporating real time data from sensors resulting in greater insights for asset management, worker safety, and predictive analysis.
  • 4-D seismic imaging adds a time lapse to 3-D imaging, resulting in an enhanced view of reservoirs and leading to a greater recovery rate.
  • Robotics automate the repetitive task of connecting drill pipes through ocean water and rock leading to improved efficiency and safety.
  • Big Data has enabled firms to capture unstructured data from oilfields such as rock formation data surrounding a wellbore or spectral data from thermography systems.
  • Digital Power Plants for Steam is a suite of technologies developed by GE that reduces CO2 emissions and improves the performance and efficiency of coal-fired steam power plants. According to GE, Digital Power Plant software interprets data from ~10,000 sensors to improve power plant performance and increases efficiency up to 1.5%, allows for 5% less unplanned downtime and 3% lower CO2 emissions.
  • Augmented Reality is used in smart glasses to enhance worker safety in power plants by overlaying digital instructions, identifying/amplifying hazard, connecting field workers with remote experts, etc..   
  • Machine learning, combined with predictive data analytics, has increased the accuracy of wind production forecasts by using new algorithms and pattern recognition techniques.    
  • 3D Printing of Solar Panels has led to a decreased manufacturing cost of solar panels. With 3D printing becoming more advanced and efficient, we could see a higher adoption rate for solar panels in the near future.    

Midstream

  • Blockchain technology has the ability to significantly cut costs and improve reliability in energy trading – BP and Shell are leading a consortium that will develop a blockchain based digital platform by end-2018.
  • Virtual Reality simulations of plants allow plant operators to replicate key processes and procedures in processing plants leading to robust training and improved worker safety.  
  • Industrial Internet of Things (IIoT) sensors attached to pipelines allows for the collection, measurement, and analysis of real-time data. Data from the IIoT sensors can be used to optimize logistics as well as provide critical information relative to pressure cycles, imbalances, corrosion, and pipeline conditions.
  • Virtual Power Plants aggregate distributed energy resources for the purposes of energy trading on wholesale power markets leading to greater market participation and liquidity.
  • Smart Grids facilitate the digital communication between the utility and the end user, resulting in high reliability, availability, and efficiency in the transmission of power.
  • Artificial Intelligence embedded into the smart grids leads to autonomous, self-healing, and optimal grid networks (neural grid).
  • Weather & Climate robots continuously collect, organize, analyze, and filter short-term weather data and complete historical climatic time series leading to valuable insight for forecasting and hedging.
  • Blockchain-based Transactive Energy – transactive energy is a power platform where market-based exchanges are used to optimize generation, distribution, and consumption of power. Blockchain technology further enhances and secures the communication between exchanges and producers/ distributors /users.  
  • Distributed Generation has enabled more efficient distribution of renewable power. Since the electricity is generated near the point of consumption instead of a centralized location (traditional power plant), there are fewer power losses during transmission, lower costs due to decreased congestion, etc.. 
  • Distribution Automation (DA) equipment and software seamlessly integrates intermittent renewables into the power grid by automatically switching between the various sources.   
  • Two way power flows coming from excess generation in a distributed grid results in greater efficiency and participation.

Downstream

  • Data analytics on the retail level has led to digital-enabled marketing and distribution where digital fuel pumps can capture consumer habits and optimize retail prices.
  • Geospatial analytics has led to more efficient distribution networks via route optimization.  
  • Mobile payment for fuel at service station has led to lower prices – a US gas station cut gas prices by 10 cents/gal for customers who pay via app-enabled direct debit.

 

  • Smart Meters allows for the daily monitoring and recording of electric energy consumptions. Smart meter technology has led to an enormous volume of data which has been used to price power, forecast consumption,  segment the market, etc. at the retail level. The comprehensive processing of meter data in a singular data hub has simplified billing.
  • Advanced data analytics, combined with automation, allows for a customer to visualize personal load curves, factors affecting consumption, simulate invoices, etc.
  • Connected homes have transformed how customers view and use energy.
  • Advancements in lithium ion and rechargeable lithium sulfur batteries has led to innovation in energy storage. BP reports that battery technology is advancing and is expected to increase energy capacity ‘threefold by 2025’.  
  • Autonomous, driverless vehicles have increased efficiencies in logistics and improved worker safety.
  • Electric vehicles and corresponding charging stations increases demand of power in remote locations impacting the economics of power transmission and the grid.

 

The table shows a multitude of digital and technological innovations that are transforming the energy landscape and changing the way firms operate. However, the items above only represent a fraction of the innovations that are currently in the market. If you also consider the innovations that are still being developed or made accessible for enterprise, you can get a sense of just how rapidly the industry is evolving.

Organizations within the industry typically fall into three camps when faced with digital innovation:

In order to avoid being in the third camp where businesses lose value after implementing new digital technology, you need to ensure your organization has the appropriate fundamentals in place.

Getting the Fundamentals Right

Building an organization with strong fundamentals is paramount when faced with frequent digital innovation. Strong fundamentals allows an organization to navigate through disruptive innovation and onboard new technology effectively. An organization has a strong foundation when its strategy, people, processes, technology, and culture are identified, defined and aligned. For purposes of this document we will review the technology aspect of the foundation – the IT fundamentals.   

Investing in fundamental IT capabilities allows for a firm to make precise and prudent decisions in a disruptive market. Robust capabilities in data governance, automation, IT risk management, and network infrastructure provides an organization with a foundation that enables the successful implementation of digital innovation.

Data Governance

Having strong IT fundamentals starts with the successful use and management of data. The current business environment demands we record, analyze, and leverage every piece of relevant data we discover. In previous years, access to capital and resources was the key differentiator in the energy industry. Now, the main driver of competitive differentiation is access to information. The firm who can gather and exploit the correct data in order to produce asymmetrical market information or discover cost-saving tactics will have a significant advantage in the market. Since data is critical to core business operations, it is necessary for an organization to invest in data governance as a fundamental IT pillar. Having a robust data governance program ensures that an organization

  • Retains quality data that can be easily accessed, shared, and stored when digital innovation disrupts the market
  • Has the correct data and the corresponding algorithms in the right places for impactful analysis and action

For example, you can’t automate power plant maintenance without the right data and a model which can analyze the data and produce something actionable as an output. The right data means the power plant has the correct array of sensors to collect the relevant data. A good model would house an algorithm that interprets the data and creates an analysis of what maintenance is needed. Useful data would then be available to power automated action by delivering a report or work order. A data governance program facilitates clean data as well as useful data for reporting and automation.                 

Running new and innovative technologies or processes with unreliable or incorrect data is highly inefficient and a poor allocation of resources. Using historical smart meter data to forecast retail consumption for the next year is a practical application of the smart meter technology. However, if the firm employs sub-par data practices with very little governance in place than the smart meter technology is useless because the integrity of the data is questioned. There have been brilliant innovations regarding business intelligence over the past few years that have relevant and practical application in the energy industry. Advancements in AI combined with advanced data analytics has disrupted the market with innovations such as augmented reality and digital twins. It is imperative to invest in data governance now to prepare for when the next wave of disruptive innovations impact the industry.  

Automation

Technology-enabled automation is another capability that is fundamental to an organization's foundation. Automation is essential because it is where most of your IT-based ROI comes from. The overall IT function has fundamentally shifted from a cost center to a strategic revenue contributor largely due to the automation of business processes. This is because automation directly leads to

  • Cost savings – Automation replaces manual labor, eliminates redundancies, and reduces the number of steps in a process while increasing operational speed, accuracy and reliability
  • Value add - Automation of processes enables an organization to focus on its core business by automating non-core operations such as maintenance, invoice processing, payroll, etc. The automation of trivial, repetitive tasks allows people to focus on delivering value to the customer.

Let’s take the above power plant maintenance example where IoT sensors were collecting data for a maintenance report. Though having the sensors collect data that is run though a model for a useful maintenance report is a good use of automation, the process can be further automated for greater efficiency. An automated analysis that shows a need to fix something can automatically create a script of what components needs which type of maintenance and then kick off a work order into the SAP/Oracle/propriety IT system. Even further automation can enable drone use for simple maintenance, superseding all human involvement for optimal results. Automation logic can also be used in this scenario to kick certain maintenance into a queue for human review if something critical is at risk or if the cost is over a predetermined threshold.

Automation also has a lot of indirect benefits. Machine to machine interaction stemming from automation leads to the capture of data that wasn’t previously recorded. This leads to greater business intelligence and insight, which increases the accuracy of predictive models and enables better decision making. Automation also lays the groundwork for more advanced technologies. Artificial Intelligence is more easily enabled when automation provides a foundation. While automation largely includes software that follows rules-based programming language, AI is designed to simulate natural intelligence. A robust AI-enabled IT operating model is designed to seek out patterns, learn from experience, and make situational-based decisions based on enormous volumes of data. However, in order to achieve to this level of business insight, a firm must first invest in the IT fundamentals.   

IT Risk Management

Data integration and process automation means a lot more sensitive data is exposed throughout the enterprise. Having the right controls and protocols around your data and processes is essential for security. The energy industry needs to be ready for sophisticated cyber-attacks which means careful planning and heavy investment around important assets. An organization will not be able to take advantage of any digital innovation if the business is constantly under attack. You can read more on the different types of cyber-attacks and how to prepare for them by clicking here.    

Network Architecture

The final IT fundamental discussed is the design and structure of your network architecture. Investing in innovative technology could potentially be a waste if your network architecture is not designed to leverage these technologies. A common theme amongst innovative technology today is that the technology is largely decentralized. Edge Computing brings computational power to the edges of the network and unlocks the power and potential of decentralized tech such as Blockchain, Artificial Intelligence, and Internet of Things.            

Edge Computing is a type of IT architecture in which data is collected, processed and analyzed along the peripheries of the network. It is an alternative topology to how current networks are structured in most enterprises. In a typical enterprise network, data computation and analysis is housed within the center of the network. Data is collected throughout numerous endpoints and is routed to a central cloud server for analysis. Edge Computing turns everything inside out. Processing power is redirected to the edges of the network next to the resource-poor devices that need it the most.

Centralized cloud computing is not conducive to recent digital innovation of decentralized technology. The user experience from these technologies is degraded due to the number of systems that are required to run effectively in order for the technology to be optimal. For example, in order for a forecasting team to map out real-time demand data coming from a smart fuel pump, the local internet connection, internet service provider, IT backbone, and central data server need to be functional, effective, and aligned. If one component of the IT chain fails, the data coming from the fuel pump is compromised and the IoT-enabled device is rendered useless. If each component has 99% availability, and there are 10 different IT components in the centralized system, there is only a 90% probability the system will be functional at any given time. This is, of course, unacceptable as a 10% failure rate is too high for any sustainable operation. The more we push business activity to the edges of the network in a central cloud configuration the more we start seeing operational issues such as higher network failure rates, data volume and velocity limitations, and latency.

Redesigning network infrastructure to fit the current business environment is important since it allows for the optimal function of decentralized technology. Edge Computing enables your organization to take advantage of the next big digital innovation by structuring your network in a way that facilitates technological advancements no matter where they occur.     

Consulting 4.0

Sia Partners is consistently on the cutting edge of where business meets technology. Our capabilities in the energy industry include data science labs where we house propriety models and algorithms which can be used to unlock powerful insight into your organization. We have created several cutting edge consulting bots which can be used for automation, AI, business intelligence, and advanced data analytics. From weather and climate to optimizing power rates and visualizing load curves, we have a variety of bots that can optimize your organization. You can view our current bots by clicking here.  

Disruption is inevitable in the energy industry due to the frequency of digital innovation. Getting the fundamentals right is critical when navigating through a disruptive market. For further information on how Sia Partners can help, please contact us.

 

Sources

  1. http://www.sciencedirect.com/science/article/pii/S2352864817301335
  2. http://www.datacenterknowledge.com/industry-perspectives/rise-edge-computing
  3. https://www.cisco.com/c/en/us/products/collateral/switches/nexus-5000-series-switches/white_paper_c11-690561.html
  4. https://www.businessnewsdaily.com/5791-virtualization-vs-cloud-computing.htmlSource 5
  5. https://www.horsesforsources.com/RPAglobal2000_031118
  6. https://www.fastcompany.com/40540343/we-need-breakthrough-business-models-not-breakthrough-technology
  7. https://www.ge.com/digital/blog/big-data-oil-and-gas
  8. http://www.archeio.com/the-value-of-unstructured-data-in-the-petroleum-industry/
  9. https://www.businesswire.com/news/home/20160613006585/en/GE-Introduces-Digital-Power-Plant-Steam-Enhance
  10. https://hbr.org/2004/06/capitalizing-on-capabilities
  11. https://computhink.com/the-importance-of-business-process-automation-and-workflow/
  12. http://www.thestrategicciojournal.com/2017/09/15/welcome-no-longer-cost-center/
  13. https://oilprice.com/Energy/Energy-General/The-Next-Big-Digital-Disruption-In-Energy.html
  14. https://www.cnbc.com/2017/11/14/continuous-disruption-is-new-normal-for-oil-and-gas-industry-baker-hughes-ceo-lorenzo-simonelli-says.html
  15. https://www.epmag.com/oil-gas-companies-keep-digital-tech-radar-add-value-1666261#p=full
  16. https://www.reuters.com/article/us-energy-blockchain/bp-shell-lead-plan-for-blockchain-based-platform-for-energy-trading-idUSKBN1D612I
  17. http://www.oliverwyman.com/content/dam/oliver-wyman/v2/publications/2017/may/Gas_Station_Digital_Future.pdf
  18. https://www.epmag.com/learning-leverage-artificial-intelligence-oil-gas-1677511
  19. https://www.navigant.com/-/media/www/site/insights/energy/2018/energy-cl...
0 comment
Post a comment

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.
Image CAPTCHA
Enter the characters shown in the image.
Back to Top