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Opportunities and Challenges of Artificial Intelligence in the Energy Sector

Learn how artificial intelligence in the energy sector will become in focus in the years to come and how you can benefit on it

February 04, 2020

6 mins read

The energy sector is one of the most powerful and lucrative in the modern economy. But most energy companies don’t realize their energy production potential and don’t incorporate the latest technologies to make their operations more efficient. Currently, the energy industry is at the edge of a big transformation.

AI is the new electricity, smart-energy.com

One way in which the energy sector can catch up to today’s innovations is by using artificial intelligence (AI). What can artificial intelligence and machine learning development services give to the energy industry and how can it make it more efficient and safe?

Let’s dive right in.

Top uses of AI in the energy sector

Opportunities and Challenges of Artificial Intelligence in the Energy Sector
Source: Forbes

According to Forbes Contributor Fabian J. G. Westerheide, the CEO of AI for Humans, “Whoever controls the strongest artificial intelligences controls the world.” After all, AI is the technology of the century. Take a glance at the map above to get a sense of how AI is incorporated into the strategies of the most influential countries. Naturally, these strategies include modernization of the energy sector, as it’s critical for every country’s economy.

Data digitization

As the world shifts in the direction of personalized digitized services, the energy sector is lagging behind. AI can help transform data collection, storage, and management, allowing the energy sector to catch up with the times. Despite how powerful and profitable this sector is, it still relies heavily on manual work.

Energy companies have a lot of data to manage. With the help of AI, they can store, process, and manage data more time- and cost-efficiently. Implementing innovative technology can help the energy industry get more competitive under the conditions of an unstable economy and develop better operational methods than those currently available. Moreover, AI data management can reveal new insights that can completely change how the industry works.

AI forecasting

The world faces dramatic energy problems. Modern machines need more and more energy to be sustained, and so does the global population. One of the major tasks AI is expected to cope with in the energy sector is predictive analytics.

Energy companies badly need to improve their predictive analysis methods to cut costs, save power, get ready for changing conditions, and provide better customer service. With the help of machine learning and deep learning, it’s possible to bring forecasting to the next level in the energy industry. Energy providers need to forecast changes in demand, system overloads, and possible failures as precisely as possible. The cost of error in the energy industry is high.

GE Power, which generates 30% of the world’s electricity, is working on incorporating AI to facilitate their energy supply chain. GE plans to improve their business operations with the help of AI and machine learning (ML).

Anodot offers another example of an AI forecasting solution in the energy sector. This startup provides real-time alerts and forecasts that can help energy companies detect issues and solve them as soon as possible.

Resource management

Resource management is the next step after AI forecasting for the energy sector. With smart AI-powered predictive mechanisms, energy suppliers will be able to dispatch their resources better, prepare for demand in advance, predict any problems, and save resources whenever possible. For end clients, power-saving with AI will result in lower utility bills and customized services.

In November 2019, Baker Hughes, C3.ai, and Microsoft announced an alliance to make it easier for customers to adopt scalable AI solutions run on Microsoft Azure. Thanks to it, the energy sector can improve its efficiency and increase safety while reducing the environmental impact of the oil and gas industries.

Energy storage facilitation

Efficient energy storage is a tough issue. As the amount of power to be stored continues to grow, additional capacity and new management systems are needed. Artificial Intelligence can help industry actors to optimize their energy storage.

Storing renewable energy is quite problematic, as the production of this energy is periodical and sometimes even chaotic. Uniting renewable energy with AI-powered storage can greatly facilitate energy storage management, increasing business value and minimizing power losses.

Let’s consider Stem, a startup that helps companies make their energy strategies smarter. Stem works with over 80 of the top solar energy developers in the US, helping them increase project value by as much as 90% by adding storage capacity.

Failure prediction and prevention

Energy is a powerful resource that can be very dangerous when handled poorly. For instance, faulty transmission lines were found guilty of causing deadly wildfires in California in 2018. Artificial intelligence has the potential to assist in predicting and preventing such disasters. For example, AI can predict system overloads and warn operators of potential transformer breakdowns.

The startup VIA has developed a blockchain-powered solution called Trusted Analytics Chain that helps companies gather and analyze their data to predict system behavior. PreNav is a startup that’s helping energy businesses digitize their infrastructure with the help of drones, lidar, and deep learning. Such a solution can help enterprises better visualize their capacities. PreNav’s deep learning algorithms can be used for identifying damages and threats particular to the energy industry, such as corrosion, bad insulation, cracks, and missing rivets.

Key challenges of AI in the energy sector

Lack of theoretical background

One reason for the slow adoption of AI in the energy sector is a lack of necessary knowledge about AI technology among decision-makers. Many companies simply don’t have a sufficient technical background to understand how their business can benefit from AI adoption. Conservative stakeholders prefer to stick with time-proven methods and tools rather than risk trying something new.

As more industries like education, finance, healthcare, and transportation embrace the potential of AI, decision-makers in the energy world are turning their attention to this technology as well.

Lack of practical expertise

AI is still a new technology, and professionals who have mastered it are few. There are a lot of experts with in-depth theoretical knowledge of the subject. Yet it’s immensely hard to find professionals able to build robust AI-powered software that has real practical value. What’s more, the energy sector is highly conservative in its ways.

Even though energy companies collect and manage data, digitizing it with innovative tech solutions is problematic. There are associated risks of data loss, poor customization, system failure, and unauthorized access. Since the cost of error is high in the energy industry, many companies are reluctant to risk trying new approaches they have no experience with.

Outdated infrastructure

Outdated infrastructure is the largest stumbling block to the modernization of the energy sector. Currently, utility companies find themselves buried in a pile of data they collect, having no idea how to cope with it. While the industry has more data than most, that data is often distributed, disorganized, scattered across different formats, and stored only locally. While having huge profits, the industry also suffers great losses due to the vulnerabilities of outdated systems.

Financial pressure

Implementing innovative smart technology in the energy sector could be the best thing to do, but it’s certainly not the cheapest. Searching for an experienced software services provider, developing and customizing software, adjusting, managing and monitoring it takes a lot of time and resources.

Before businesses in the energy sector can reap the benefits of incorporating AI, machine learning, and deep learning into their strategies, they have to be willing to allocate an impressive budget and accept with the risks of changing their outdated systems.

Final thoughts

Advanced technology is penetrating every part of the modern economy, and the energy industry is no exception. Artificial intelligence has what it takes to revolutionize this sector across the globe. Soon enough, AI is expected to go from being a handy technology to being the most efficient decision-maker the energy industry has ever had. It’s predicted to cut the amount of manual work, reduce risks, and improve data and asset management. But before the bright future can come and AI can revolutionize the energy sector, a lot of challenges need to be dealt with.


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