Companies like Shell use the cloud for everything from security to searching for new resources
Clouds are becoming increasingly popular in the energy and industry sectors, due to enterprises' modernisation and digital transformation efforts. Companies are increasingly striving to increase their efficiency and improve competitiveness.
Modern clouds provide a number of benefits:
- They accelerate the development of specialised applications and systems for collecting and analysing production data.
- They provide fast and easy access to computing power and scaling virtual infrastructure.
- They monitor production processes in real time and controlling their efficiency.
- They ensure the stable and safe operation of enterprises during peak loads or unplanned equipment failure.
- They reduce IT infrastructure costs.
Let's take a closer look at some scenarios in which cloud technologies can be applied in energy and industry.
Accelerated application development
Cloud technologies reduce the time and cost of introducing new services that enable businesses to upgrade their production facilities or offer customers new product lines.
Automation and data management
HEP, Croatia's national energy company, faced the challenge of providing the computing resources needed by businesses too slowly during the digital transformation process, significantly delaying new project implementation.
Migration to the cloud has allowed HEP to significantly speed up the development and testing of the required applications by automating many routine operations.
The first project in the cloud was the development of the Coal Information System, which is used for managing data on coal reserves at the Plomin thermal power plant. The task was to provide the managing company and the thermal power plant with accurate data on coal supplies and its current stock, as well as a contract management tool.
Based on the results of the first two months in the cloud, HEP's IT department saw an acceleration of releasing new features and updates for the application by over 50 per cent. The HEP development team now has a ready-to-run environment without the hassle of purchasing and configuring hardware and software. Since implementing the cloud development process, HEP has noted increased savings and reduced risks thanks to standardised architecture and processes.
Using AR and VR technologies
One of the areas of large-scale digital transformation in the petrochemical company SIBUR was the introduction of augmented and virtual reality technologies.
This approach was intended to replace visits to industrial facilities by service experts, as well as to reduce the time and cost of carrying out the necessary work, saving up to $15,000 on each video call.
For other industrial and energy companies that wish to accelerate their digital transformation, specialists of G-Core Labs are ready to carry out a full cycle of development and testing for specialised programs and services.
Peak load management
Cloud technologies provide quick access to additional computing power during sharp increases in the amount of data generated by the enterprise.
Similar situations arise when new production lines or instrument systems are connected, where sensors record the main parameters of the equipment (for example, temperature and pressure).
Uneven load distribution is a typical issue caused by, for example, peaks and troughs in electrical power consumption. Cloud-based virtual power plants help optimise infrastructure performance. Renewable energy systems like solar and wind have one more problem - uneven power generation due to changes in weather conditions.
Tesla's virtual power plant
Tesla is implementing the world's largest virtual power plant project: 50,000 solar and storage batteries, connected to provide a sustainable power supply in South Australia.
In the same region, the company has connected the largest energy storage facility at the Hornsdale wind farm. A cloud platform ensures the optimal distribution of energy among consumers.
Telemetry systems monitor the current state of energy infrastructure elements such as batteries, inverters, and chargers. The collected data is then processed in the cloud and software models are created: digital twins used to predict energy consumption and control system peripherals. The workload between industrial applications is distributed by Kubernetes clusters, providing fault tolerance for the virtual power plant.
AI load simulation
The G-Core Labs AI Platform is suitable for simulating the peak loads of power systems. It integrates a number of data acquisition and processing tools, such as Kafka, Storm, Spark, PySpark, PostgreSQL, MS SQL, Oracle and MongoDB.
The platform uses Intel Xeon Gold 6152, 6252, 5220R CPUs and Nvidia GPUs for computing.
Employing additional computing power during peak periods and shutting down unnecessary virtual machines when the load decreases are carried out in the cloud in just a few minutes.
The pay-as-you-go model allows customers to pay only for the resources consumed, with per-minute billing.
Cloud computing lowers enterprise costs in the event of emergencies related to control and monitoring system failures, equipment failures, data loss and personnel errors. Companies can scaleup to use additional computing resources in emergency situations, create data backups and automatically recover interrupted processes.
By switching to a cloud-based backup and disaster recovery solution, the oil and gas company Ultra Petroleum has cut its IT infrastructure costs in half. Implementing the new system took less than eight hours.
In the G-Core Labs cloud, disaster recovery is provided as a service: payments are required only for the active use of virtual machines, the need for which arises when testing equipment fault tolerance or in the occurrence of immediate failures in its operation. The system is easily scalable, allowing new applications to be introduced as needed. If there's an incident, any interrupted processes are completely recovered in just a few minutes.
Big data and artificial intelligence
For modern industrial and energy companies, the ability to work with big data is a key competitive factor. This requires the implementation of applications for data analysis, including those based on artificial intelligence. Cloud infrastructure can help reduce the time it takes to develop, test and deploy these applications and ensure they run smoothly.
Oil and gas
Shell is developing a number of projects based on a cloud platform with artificial intelligence.
- Predictive maintenance: Wired and wireless sensors collect data about the current state of oil production and refining equipment, like valves and compressors. Using information about changes in temperature and pressure, the machine learning algorithms predict in advance when they need to be replaced. The company uses this solution at 23 facilities (refineries and offshore oil platforms), allowing them to avoid disruptions of their work. Shell estimates that predictive maintenance at its Pernis plant in the Netherlands has already saved the company several million dollars.
- Searching for new oil and gas fields: Machine learning algorithms reduce the time to process seismic data from the ocean shelf by 80 per cent. In land drilling, AI helps to accurately determine oil well contours and reduce wear on drilling rigs.
- Security: Shell filling stations in Thailand and Singapore are equipped with video analysis systems. Artificial intelligence detects smoking and alerts employees to take action to prevent fires and explosions. In the future, Shell plans to use similar systems to ensure safety at its other facilities, for example, to monitor the condition of underwater equipment or the availability of protective overalls for oil workers.
- Improved quality of service: Artificial Intelligence analyses data from previous orders made by Shell customers, helping to develop personalised offers and loyalty programs.
ABB is making its energy infrastructure sustainable by monitoring inverters and transformers with AI cloud digital twins. A low-cost solution based on image recognition technologies has been developed for customers who wish to ensure security in an industrial enterprise. Neural networks using the TensorFlow and Keras machine learning tools detect corrosion on electrical wiring and assess the risk of failure.
The development and testing of services based on artificial intelligence is a promising area of investment for industrial and energy companies, enabling them to upgrade production facilities and create new services. The cloud AI Platform - with integrated machine learning tools like TensorFlow, TensorRT, OpenVINO, Keras, fast.ai, PyTorch and BigDL - also helps to speed this process, with minimal IT infrastructure costs.
Internet of things
Cloud technologies ensure the functioning of industrial internet of things systems. The centralised management of smart manufacturing is carried out through the continuous collection and analysis of data on production and logistics processes in an enterprise.
Tonsjö uses a cloud to automate its metal production. Sensors connected to milling, turning, and boring machines and industrial robots monitor equipment health, speed, and efficiency in real time.
The collected information is stored and processed in the cloud, along with CRM data and financial records. The digital monitors installed at the enterprise display warnings about the risks of equipment malfunction and up-to-date statistics. Tonsjö estimates that production from its cloud-connected production lines has grown by 4 per cent.
G-Core Labs Cloud is a multifunctional data center that is available at any time from anywhere in the world and allows you to deploy unlimited virtual resources in just a few clicks, without leaving your home or office and without buying the expensive necessary equipment. With the help of G-Core Labs Cloud, any business will be able to speed up its development, testing, and launching processes several-fold, and with the minimum infrastructure costs.
Our cloud services are powered by Intel Xeon Gold 6152, 6252 and 5220 processors, have up to 1 TB of RAM and SSDs and HDDs with triple replication.
The G-Core Labs cloud is based in Luxembourg, Ashburn (USA), Amsterdam, Singapore, Moscow & Khabarovsk; Frankfurt, Sidney and São Paolo are to follow.