AI in power and utility industry
AI is a popular technology. Can it serve its purpose in the power and utility industry as well? Find out.

AI in power and utility industry

Everyone is talking about artificial intelligence (AI) today. In fact, it is the fastest-growing branch of the high-tech industry. 

Despite the hype, not everyone understands what AI actually means. At a broader level, AI is the capacity of machines and computers to mimic human behavior (and intelligence). Under that umbrella term are machine learning (ML) technologies and complex algorithms that help machines and computers work smarter and help solve problems faster.

In the last few months, we’ve discussed how AI can impact various industries. In this article, we will talk about the use case of AI in the power utility sector.

AI has become highly crucial in the energy industry. It has a huge potential for the future of the energy system. The common applications of AI in the power utility sector include electricity trading, smart grids, or the sector coupling of electricity, heat, and transport. 

AI has grown in popularity in this industry due to the digitalization of the energy sector and the availability of large sets of data that are proving to be invaluable. The role of AI has been predominantly to make the energy industry more efficient and secure. This it does by analyzing and evaluating the data available.

AI makes the transition to renewable energy easy

Renewable energy is becoming mainstream for obvious reasons — sustainability. Additionally, energy providers are eager to take advantage of federal or state tax credits for products such as solar power equipment. 

A successful transition from fossil fuels to renewable energy first requires analyzing crucial data points. Utility providers need to assess the output of current or planned renewables projects and combine that with the anticipated demand brought about by all the customers using renewables.

By examining the two variables, it’s possible to use AI to take a predictive approach to the metrics. Such a system can help to determine information such as when renewable energy sources get used the most, during what hours of the day, or which particular areas have exceptionally high usage.

AI for customer satisfaction and engagement

A few years ago PricewaterhouseCoopers (PWC) released a research report titled “Beyond the hype: What is the value of customer satisfaction to a regulated utility?”. The research showed that customer satisfaction is an important factor influencing the outcomes of regulatory initiatives. The study also found that a focus on customer satisfaction is a key way for utilities to protect their core business.

The energy system has undergone dramatic changes in the last few years caused due to the influx of distributed energy resources (DER). Another driver for these changes is the threat of competition from non-utility energy providers. Hence the importance of customer satisfaction has increased.

AI can provide the power utility sector with highly personalized, actionable, and timely information that they can communicate to customers in a way that drives better engagement. For example, alerts can be sent to customers about their bills when it is projected to be higher than usual. This can include actions that the customers can take to address the problem. 

Preventing power outages 

Power outages are disruptive for customers and become costly for utility companies to fix. AI and ML can be used to predict the conditions that cause power outages.

For example, utility providers can seek to identify weak points in the electric grid and proactively repair them before outages occurred. By creating an autonomous system, providers can be better prepared to handle ordinary fluctuations in power or even recover quickly from disastrous events such as storms and earthquakes.

AI for reducing waste

Waste of utility will result in profitable operations difficulty. It’s not easy to spot problems if they relate to hidden leaks. AI can be used to pinpoint areas of inefficiency. This allows providers to take timely action and keep their costs down. Providers can offer AI-powered apps that enable customers to reduce costs by helping them reduce waste. This can be done by tracking how much water and electricity are used. A simple example is using AI to find leaks in water pipes by using sound-processing capabilities to monitor for sounds that could indicate dribbles of water. 

Challenges

The biggest criticism of AI is the power consumption of AI itself. The irony of it doesn’t fail to amaze us. 

Processing large amounts of data consumes a lot of electricity. When using AI for energy system transformation, it is important to analyze how to design energy-efficient data centers and to try and keep them as climate-neutral as possible. 

One of the solutions to this problem is to increase the physical proximity of data centers and renewable energy generation plants. Another solution would be to postpone power-intensive computing operations to times when a lot of power is available. Providers can also consider utilizing more energy-efficient IT hardware or programming that requires as little computing power as possible.

Another key challenge is protecting user data. While the benefits of AI aren’t debatable, it is important to ensure the safety of user data. This requires that the AI is transparent and comprehensible. AI should be explainable. 

At Brainalyzed Insight’s AI-powered platform, we are helping power utility providers deliver better services, transition to renewable energy, avoid wastage of utility, and keep customers happy. Want to learn how you can implement AI to enhance your power utility business? Let’s talk. 

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