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Artificial intelligence and machine learning now integral to smart power solutions

They help to improve efficiency and profitability for utilities.

The utilities’ space is rapidly transforming today. It’s shifting from the conventional and a highly-regulated environment to a tech-driven market at a fast clip. Collating data and optimizing manpower is a constant struggle. The smarter optimization of infrastructure has increased monumentally with the outbreak of the pandemic, and also the dependency on technology. There is an urgent need to balance the supply and demand for which Artificial Intelligence (AI) and Machine Learning (ML) can come into play. Data Science, aided by AI and ML, has been leading to several positive developments in the utilities space. Digitalization can increase the profitability of utilities by significant percentages by utilizing smart meters for grids, digital productivity tools and automating back-office processes. According to a study firms can increase their profitability from 20 percent to 30 percent.

Digital measures rewire organizations to do better through a fundamental reboot of how work gets done.

Customer Service and AI

According to a Gartner report, most AI investments by utilities most often go into customer service solutions. Some 86% of the utilities studied used AI in their digital marketing, towards call center support and customer application. This is testimony to the investments in AI and ML that can deliver a high ROI by improving speed and efficiency, thus enhancing customer experience. The AI that’s customer-facing is a low-risk investment as customer enquiries are often repetitive such as billing enquiries, payments, new connections etc. AI can deliver tangible results for business on the customer service front.

Automatic Meters for Energy conservation

As manual entry and billing systems are not only time-consuming, but also susceptible to errors and are expensive too. The Automatic Meter Reading (AMR) System has made a breakthrough. The AMR enables large infrastructure set ups to collect data easily and also analyze the cost centers and the opportunities for improving the efficiencies of natural gas, electric, water sectors and more. It offers real-time billing information for budgeting. It has the advantage of being precise compared to manual entry. Additionally, it is able to store data at distribution points within the networks of the utility. This can be easily accessed over a network using devices like the mobile and handhelds. Energy consumption can be tracked to aid conservation and end energy theft.

Predictive Analytics Enable Smart grid options

By leveraging new-age technologies, utilities can benefit immensely. These technologies in the energy sector help in building smart power grids. The energy sector heavily relies on a complex infrastructure that can face multiple issues as a result of maintenance issues, weather conditions, failure of the system or equipment, demand surges and misallocation of resources. Overloading and congestion leads to a lot of energy being wasted. The grids produce a humongous data which help with risk mitigation when properly utilized. With the large volume of data that continuously pass over the grid, it can be challenging to collect and aggregate it. The operators could miss these insights which could lead to malfunction or outages. With the help of the ML algorithms, the insights can be obtained for smooth functioning of the grids. Automated data management can help maintain the data accurately. With the help of predictive analytics, the operators can predict grid failures before the customers are affected and also create greater customer satisfaction and mitigate any financial loss.

Efficient and Sustainable energy consumption

These allow for better allocation of energy for consumption as it would be based on demand and can save resources and help in load management and forecasting. AI can also deal with issues pertaining to vegetation by analyzing operational data or statistics. This can help to proactively deal with wildfires. Thus, it can become a sustainable and efficient system. To overcome issues pertaining to weather-related maintenance, automation helps receive signals and prioritize the areas that need attention to save money and cut down the downtime. To achieve this, the sector adopts ML capabilities as they need to be able to access automation fast and easily.

The construction sector is also a major beneficiary of the solutions. Building codes and architecture are often a humongous challenges that take a long time to meet. But, some solutions help the builders and developers test these applications seamlessly without any system interruptions. By integrating AI and ML in the data management platforms, the developers enable the data-science teams to spend enough time innovating and much less time on maintenance. With the rise in the computational power and accessibility to the Cloud, the deep learning algorithms are able to train faster while their cost is optimized. AI and ML are able to impact different aspects of business. AI can enhance the quality of human jobs by facilitating remote working. They can help in data collection and analysis and also provide actionable inputs. Data analytics platforms can throw light on the areas of inefficiency and help the providers keep costs down.

Though digital transformation might appear intimidating, its opportunities are much more than the cost and risk associated. Gradually, all utilities will undergo digital transformation as it has begun to take roots in the industrial sectors. This AI-led transformation will improve productivity, revenue gains, make networks more reliable and safe, accelerate customer acquisition, and facilitate entry into new areas of business. Globally, the digital utility market is growing at a CAGR of 11.7% for the period of 2019 to 2027. In 2018, the revenue generated globally for the digital utility market was 141.41 Bn and is expected to reach US$ 381.38 Bn by 2027 according to a study by As the sector evolves, the advantages of AI and ML will come into play and lead to smarter grids, efficient operations and higher customer satisfaction. The companies that are in a position to take advantage of this opportunity will be ready for the future challenges that could emerge in the market.


Views expressed above are the author’s own.