The arrival of artificial intelligence has transformed the way various industries and sectors have been working. On the other hand, renewable energy boom is coming up as another big revolution. The economy of the energy projects is continually getting competitive by each passing day.
The energy sector, hence, is experiencing a huge shift and the supply chain is being transformed and transitioned to be efficient and effective more than ever. To support the AI and encourage its use to develop the sectors, the UN organised an AI Good Global Summit in Geneva to highlight the applications of the AI application.
Applications of AI in the Energy Sector
Artificial intelligence makes the prospect of the energy of greater speed and decreases the processing costs highly which is making it the most attractive aspect for all the major oil companies. The drilling and refinery organisations are making huge profits by using the artificial intelligence by using it to determine data regarding the fluid resistance, porosity, formation, density, shape, and size of the collection of resources underneath the surface.
Management of Supply
A variety of important data is being collected by the power grid operators to constantly monitor, analyse, and interpret the need that enables to ensure a constant supply of the energy resources as per the demand.
Robotics enabled AI has been used integrally in the field of research and testing in the energy sector and has been delivering excellent results. The robots are being capable of inspecting, repairing, maintaining, and certifying the energy resources and requirements.
Smart Energy Storage
The efficient and effective storage of the energy plays an important role in determining the demand and supply of the energy required and to be used at its optimum level. The situation is complex and hence requires a number of technologies to be combined and unlock the value of proper control and storage. Pairing AI and energy are expected to bring the necessary change and shift in the sector.
Optimising Stand-Alone Systems
To enhance the economic value of the energy systems and storage efficiency of the projects, AI opens a number of possibilities. Bringing in factors like predictive analysis, big data, machine learning, and grid edge computing, every second of data is being captured and analysed.
The continually changing business complexity has been supporting a number of emerging value streams. The aim is to achieve reduced demand charges, increased revenue, future-proofing against changing rates, and more value derivation while at the same time maximising returns and ensuring program compliance.
A report by the Brookings Institution says AI is having a bigger impact at a larger level on fossil fuels than green alternatives because it’s very well suited and meeting the demands for the activities that enable to unleash the true potential of the energy being derived from hydrocarbons. 54% of the businesses in the energy sector have been actively growing in the AI revolution and have confessed to having gained productivity by taking the step says the survey.
Challenges Of Using AI
Undoubtedly, AI has brought in a number of advancements in a number of sectors. AI revolution has been a major factor in the growth of a number of businesses and continuing with the pace but is experiencing a number of obstacles and hurdles on its way to completely make a shift into the energy sector.
- More than 54% of global energy is being consumed by the data centres and powerful industrial systems being used to reduce the energy consumption and other aspects of the energy.
- Server farms and data collection uses 3% of the global energy which is making it more difficult for the highly dependent businesses to go ahead with AI and other IoT aspects.
- Cognitive technologies like robots, machine learning, and AI have been expected to have a major impact on the employment opportunities in the energy sector in a number of forthcoming nations by 2025.
- A survey also reveals how 77% of CEOs still aren’t convinced of the power of the AI and argue the fact of vulnerability and disruption. However, 76% still fear the potential for bias and lack of transparent processes in AI adoption.
- 93% of the businesses still feel unprepared to get full-fledged into the AI revolution and fear failing to tackle the challenges put forward by accepting the AI.
Trends In The Sector
- Businesses in the sector of energy accompanying telecommunication, media, and technology itself expect AI to have a great impact on the product offerings in the upcoming years rising significantly higher.
- Platforms capable enough to accurately identify savings and efficiency for customers and organisations are increasingly being valued in the on-going scenario.
- A number of oil giants are innovatively looking forward to going ahead with further implications of AI in their businesses.
- AI is being actively used and is preferred to model the cost savings and provide recommendations for smart home investments to save energy.
- The error rate of the predictions and the demand and supply of the energy gap has majorly decreased significantly from 7% to 2.4% globally.
The oil and gas majors like Chevron, BP, Total, and Shell, have outsourced their AI applications and models from external contractors and service providers like Microsoft, Cisco, etc. Total and TATA Consultancy are on a joint venture to proceed with the same aim to achieve the most out of the AI revolution and be benefitted.
The use of AI is also enabling the emphasis of the use of the human aspects of the job tasks by the employees and rather emphasising more upon the routine tasks. A number of energy giants are focusing strongly upon the innovations and developments in the Silicon Valley based AI technology and IoT applications to the industry.
Consequently, robotics is changing the dimensions of the work for the energy workers from finding the problems towards solving them. Still on the horizon lie quantum computing, robotics, better operational intelligence and smooth running to equip the struggling businesses with better resources and capabilities to accept and induct AI into the processes.