The Internet of Things (IoT) is being promoted in the energy sector as though it is something new. In tandem with digital transformation, the utility industry, power producers, and oil & gas players are being inundated with messaging that they need to digitally transform now.
But the reality is that these trends have been going in the energy sector for decades. A move from analog to digital controls began back in the nineties, for example. Similarly, supervisory control and data acquisition (SCADA) is a well-established technology that is used in equipment such as wind turbines and other industrial equipment to obtain real-time data, make decisions, and command and control energy generation, transmission and distribution. SCADA may not be as trendy a term as IoT, but they are at least cousins, if not brothers.
IoT Drives Better Energy Outcomes
Rick Veague, chief technology officer for North America at IFS, believes there are three key areas where IoT drives business value energy companies through better outcomes:
Digital twins of physical assets
“IoT sensors give businesses immediate visibility into how an asset is performing and delivering on its intended outcome by continuous, real-time updates on the operating state of an asset,” Veague said.
“This operational awareness can then be compared to expected outcomes, to predict when the asset should be serviced to maintain its intended outcome. This allows businesses to proactively reduce unplanned downtime, reduce cost, and improve the overall performance of the asset, and ultimately the customer.
5 IoT Energy Examples
The IoT has taken off as a concept in the energy sector. More utilities and energy/hydrocarbon producers are investing in the technology. This manifests in a number of different ways:
1. Digital Twins
A digital twin is a virtual representation of a physical asset such as a turbine or a compressor. In essence, the digital twin exactly mirrors in the virtual world what happens in the real world. They can be used to simulate changes to determine their impact on areas such as performance, fuel consumption, maintenance, and so on.
Take on-shore and off-shore oil and gas, for example. Here, a digital twin, equipped with real-time data from IoT sensors and on-rig asset management data, provides an on-shore head office with real-time, end-to-end visibility of each individual rig’s condition and performance across the process, Veague noted.
“Companies have started to build models that will provide answers to ‘what if’ or ‘what will’ questions,” said Ravindra Puranik, oil and gas analyst at GlobalData.
“By replicating an asset or a portion of it in the virtual world, companies can run simulation tests on real-world problems and visualize the results in 3D. This is helping project engineers to improve their understanding of the asset, thereby enabling them to optimize its performance as per the market requirements. Thus, digital twins are gradually becoming integral to oil and gas operations.”
2. BP APEX
BP began the APEX IoT project back in 2017. Its North Sea operations fill around 200,000 barrels a day, involving thousands of miles of wellbores and risers as well as a complex web of pipelines and processing infrastructure. The IoT helped BP engineers to create a simulation and surveillance system that recreates every element of a real-world plant within its APEX system.
“APEX is a production optimization tool that makes use of integrated asset models,” said BP’s North Sea petroleum engineer Giuseppe Tizzano. “It is also a formidable surveillance tool that can be used in the field to spot issues before they have major effects on production.”
With APEX, production engineers can run simulations that used to take hours in just a few minutes, making optimization continuous. Gulf of Mexico petroleum engineer Carlos Stewart said: “Engineering time has been the biggest payback — a system optimization could take 24-30 hours. In APEX, it takes 20 minutes. APEX delivered 30,000 barrels of additional oil and gas production a day when it was rolled out.”
3. Streamlining Maintenance
IFS IoT solutions enable companies to utilize the agility and speed of application development using APIs and low code. This means organizations can quickly develop applications that integrate real-time data from IoT devices, analyze it, and provide relevant and actionable business insights. The processing of IoT data is combined with machine learning (ML) models powered by artificial intelligence (AI) to transform streams of raw sensor data into actionable observations. These observations are applied directly to the maintenance operations, triggering the appropriate workflows to enable the necessary actions to achieve peak operational efficiency.
Veague said utilities use such systems to increase efficiency of maintenance. This includes issuing equipment alerts before actions are required and greatly reducing the costly requirement for manual inspections.
4. Wind Power
One of Asia’s largest independent power producers (IPP) in the renewable energy industry is using Uptake Radar to increase its annual energy production AEP and improve the reliability of its wind turbine fleet. Using IoT and analytics, the producer has identified an increase of 1% of energy production across the fleet. This represents $4,300 in value per turbine per year.
5. Refinery Of The Future
Texmark of Texas produces renewable fuels, mining chemicals, alcohols, and aromatic solvents. The company worked with PTC, CB Technologies, and Hewlett Packard Enterprise on industrial IoT solutions to create smart, connected centrifugal pumps that enabled them to perform real-time data analysis and predict when the pump would fail.
“Management saw less time spent taking care of pumps that didn’t require attention, and operators saw less risk to employees,” said Linda Salinas, VP of operations at Texmark.
From that beginning, the company decided to build the Refinery of the Future. Leveraging ThingWorx, PTC’s end-to-end Industrial IoT platform, and its Vuforia Enterprise Augmented Reality (AR) Suite, it is using the IoT to connect plant workers to information via augmented reality headsets, and to boost its predictive maintenance capabilities.