ARTIFIAL INTELLIGENCE IN THE ENGERY SECTOR: OPPORTUNITIES AND CHALLENGES

What lies in the store for AI in energy sector: Its potential applications and shortcomings

“Artificial Intelligence, Deep Learning and Machine Learning- whatever you are doing, if you don’t understand it — Learn it. Because you are otherwise going to be a dinosaur in 3 years.”

These words by American entrepreneur Marc Cuban can be a bit over-the-top but it puts a strong emphasis on how these modern technologies are gonna dominate almost every industry in the coming years. So today, we are gonna talk about one of these technologies- Artificial Intelligence (AI). in detail and about it’s growing importance in specifically, the Energy Sector.

 

So, lets begin our article with some insights on AI.

Artificial Intelligence may be defined as a technology which incorporates human intelligence in machines. It provides machines or computer programs the potential of thinking or performing certain tasks which otherwise, wouldn’t be possible without human intelligence. These tasks may include the likes of visual perception or speech recognition for instance.

 

Artificial intelligence (AI) makes it possible for machines to accomplish specific tasks by processing large amounts of information in form of data and recognizing patterns within the data. Today AI has taken a crucial place in many sectors and with increasing digitisation and increased flow of information everyday, the longer term for AI looks promising.

From retail to banking, from healthcare to manufacturing, AI is resulting in increased efficiency and security by enhancing the speed, precision and effectiveness of human efforts.

AI IN ENERGY SECTOR: AN OVERVIEW

With Artificial Intelligence expanding itself every day, energy sector has also not been left untouched by it. AI and energy sector are a perfect match to each other. AI thrives on data and the energy resources are flooded with huge chunk of data coming from power grids, wind-farm operations and even oil-companies. AI coupled with other technologies like cloud computing can process, stream, analyse and interpret this data precisely and with unimaginable speeds to make the energy sector more efficient and secure.

So, let’s begin our discussion on what future lies for AI in this ever- changing energy sector and what challenges and opportunities lie ahead to it:

Opportunities for AI in Energy Sector-:

The numerous opportunities for AI can be narrowed down to these five points-

1. AI in power grids : Smart grids
2. Intelligent Energy Storage(IES)
3. AI in power trading: AI forecasting
4. Resource Management
5. Preventing disaster

With time, power grids are becoming more and more decentralized and digital. It is leading to more number of grid participants and hence, more difficult to manage it and keep the grid in balance. This requires evaluating and analyzing a huge chunk of data. AI can help us with quick and efficient processing for this flood of data!

As power is being generated from more volatile sources like solar and wind, the requirement is that power generation must react intelligently to consumption (and vice versa). With AI, we can evaluate, analyse and control participants connected to each other via these smart grids.

With modern day emphasis on climate changes and increasing pressure to reduce CO2 emissions, we must find ways to have most of our power generated from renewable resources. The problem with renewable sources of energy are that they areunpredictable, which makes production of energy periodical and sometimes even chaotic. With renewable sources, there can be power outages or too much power generation which needs to be controlled.

Smart storage, also known as Intelligent Energy Storage(IES) can effectively handle these disrupt changes in power supply. If we combine renewable energy with AI-powered storage ,we can greatly improve energy storage management, increase business value and minimize power losses.

AI in power trading: AI forecasting

Use of AI in power trading can help improve forecasting. Improving their predictive analysis methods by the use of AI can serve many goals for energy companies: Cost Cutting, Power Saving, Being ready for changing conditions and also improving their existing 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 .The cost of error in energy industry is very high, which means that precision of highest level is required.

Ex- World’s largest electricity producer company GE Power is working on incorporating AI in its energy supply change to enhance precision and efficiency.

Resource Management

Suppliers can use AI to predict for demand in advance or check for problems to save resources wherever possible. They can therefore have optimal utilization of their resources, hence increasing efficiency.

AI can also enable users to save electricity and reduce their monthly bills. With AI enabled system, the networked devices can reduce power bills by reacting to prices on electricity market.

Preventing disaster

AI can be used to predict system overload or potential transformer breakdowns, thus giving an added layer of security to any disaster sort of mis-happening. Analyzing the available data and coupled with technologies like deep learning, AI can predict corrosion, cracks etc. which pose a threat to the system and can be a cause of future disasters.

Challenges for AI in the energy sector

By learning about so many potential applications of AI. in the energy sector, you would guess that it’s gonna be a pretty easy path for it in this industry. But turns out, that the path isn’t really without its obstacles. So, let’s take a look at the major challenges which has to be cleared before AI takes a giant domination in this industry-:

1. Lack of expertise and finances
2. Data privacy and Security
3. Data consumption by AI

Let us read about each challenge one-by-one:

Lack of expertise and finances

For a shift to AI enabled energy sector, we require a large number of employees with sufficient technical expertise on AI who could be able to lead this transition, but that’s not present. Moreover, the conservative approach of some organisations and huge risks associated with data compels many companies to not join this AI revolution.

Moreover, this implementation of technology in the energy sector would require developing, adjusting and monitoring software which requires lot of resources and finances.

Data Privacy and Security

Data privacy is one of the biggest issues of this century and AI literally thrives on data, so it is natural for data security to be a challenge for AI in the energy sector. Energy supply and entire energy system are prone to cyber-attacks and data theft. Being integral part of a country’s infrastructure, cybersecurity needs to be insured before completely handling over our data to the technology.

Data Consumption by AI itself

Data centers the huge “server farms” around the world storing users’ data, now consume 3% of global energy. Processing a lot of data requires large amount of electricity- making it a requirement to have a check on data consumption of AI itself. To make the energy sector artificially intelligent, its integral to ensure that these data centres are themselves, energy efficient.

CONCLUSION

It’s a no-brainer that the future lies in AI and furthermore, the capability of AI to revolutionize the energy sector must also not be doubted. AI can increase the efficiency, speed and security of energy consumption and generation and could lead the constant transitions in this sector to meet the changing climate needs. But it also goes without saying that even this “intelligent technology” has its own shortcomings which needs to be taken care of before we can embrace it with open hands.

 

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