Cloud computing has become an essential tool for the energy industry, enabling companies to become more agile, resilient, competitive and sustainable. The energy industry is well-positioned to take advantage of cloud computing, as it can help companies run upstream, midstream and downstream value chain elements more efficiently, with higher margins.
Cloud computing can help dismantle the structural and technological limitations that have created barriers to connectivity, scalability and effective data management in the energy industry. It provides seamless and instant connectivity and computing power that is scalable and comes at a lower cost.
Energy companies can use cloud computing to harness the power of data to enjoy a clear competitive advantage. Cloud platforms enable near real-time connectivity between what have traditionally been siloed functional areas. This connectivity makes it possible for companies to build and leverage advanced analytics to analyse, explore and establish causal relationships between various functions.
Cloud Computing can transform the energy industry in many ways such as
Enhancing agility and resilience: Cloud computing can help energy companies become more agile and resilient by providing seamless and instant connectivity and computing power that is scalable and comes at a lower cost. It can help dismantle the structural and technological limitations that have created barriers to connectivity, scalability, and effective data management in the energy industry.
Boosting competitiveness: Cloud computing can help energy companies run upstream, midstream, and downstream value chain elements more efficiently, with higher margins. It provides near real-time connectivity between traditionally siloed functional areas, making it possible for companies to build and leverage advanced analytics to analyse, explore, and establish causal relationships between various functions.
Enabling sustainability: Cloud computing can help energy companies embrace sustainability by enabling predictive maintenance. Predictive maintenance is a proactive maintenance strategy that uses data analysis tools to monitor equipment performance and predict when maintenance is required. This approach can reduce downtime, extend equipment life, and improve safety.
Transforming every element of the energy value chain: Cloud computing can transform every element of the energy value chain by driving cost savings and profitability in virtually countless ways. It provides seamless connectivity, scalability, analytics, and automation that can drive cost savings and profitability in virtually countless ways.
Artificial Intelligence transforming the Energy Industry
Artificial Intelligence (AI) is becoming increasingly important in the energy industry and has great potential for the future design of the energy system. AI can help make the energy industry more efficient and secure by analysing and evaluating the data volumes. AI is already proving its value to the energy transition in multiple domains, driving measurable improvements in renewable energy forecasting, grid operations and optimisation, coordination of distributed energy assets and demand-side management, and materials innovation and discovery
According to a report by the World Economic Forum, digital technologies – AI in particular – can become an essential enabler for the energy transition. These powerful technologies can be adopted more quickly at larger scales than new hardware solutions, and can become an essential enabler for the energy transition. The report defines the actions needed to unlock AI’s potential in this domain
AI can help industry actors optimise their energy storage. Storing renewable energy is quite problematic, as the production of this energy is periodical and sometimes even chaotic. AI can help predict when renewable energy will be produced and consumed, allowing for better management of storage
Here are some ways in which AI can transform the energy industry:
Renewable energy forecasting: AI can help predict the amount of renewable energy that will be produced and consumed, allowing for better management of storage. This can help optimise the use of renewable energy sources, reduce carbon emissions, improve efficiency, and reduce costs in the energy industry.
Grid operations and optimisation: AI can help optimise grid operations by predicting demand and supply patterns, identifying faults, and improving maintenance schedules.
Coordination of distributed energy assets and demand-side management: AI can help manage distributed energy resources such as solar panels, wind turbines, and batteries. It can also help manage demand-side management by predicting demand patterns and adjusting supply accordingly.
Materials innovation and discovery: AI can help discover new materials that are more efficient and cost-effective for use in the energy industry.
Electricity trading: AI can help optimise electricity trading by predicting market trends and identifying profitable opportunities.
IoT transforming the Energy Industry
The Internet of Things (IoT) has been transforming the energy industry by enabling better control over energy consumption, reducing pollution and waste, and increasing profits. IoT is being used in the energy industry to transform energy generation, transmission, distribution, and consumption
Here are some ways in which IoT can transform the energy industry
Remote Asset Monitoring/Management: Connected sensors are being used to measure wear, tear, vibration, temperature, and other parameters to determine the overall health of assets from turbines to transmission lines.
Trends in the data obtained from sensors could be used to estimate the “time to failure” of key infrastructures and plan maintenance, reducing downtime due to unscheduled maintenance and help avoid the economic consequences of such downtimes. Adopting IoT in power generations could also help identify safety issues like gas leakages before they cause harm to workers and equipment.
Process Optimisation: IoT provides real-time information about the overall state of the entire generation station. Real-time data is being used to fine-tune the operations of plants, increasing energy conversion from fuels and reducing the costs of maintenance.
Integration and Automation: IoT devices have been able to create intelligent networks (also called Smart Grids) through the collection, transmission, and use of large quantities of data. In this way, it integrates in an intelligent manner all of the assets connected to the network, optimising operation and increasing the flexibility of the systems.
