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transforming the energy industry with AI
Category: Energy & Utilities

How Cutting-Edge Technologies Like AI, ML, IoT are Transforming Energy and Utility Companies

The energy and utilities sectors are undergoing a major digital transformation shift, but an overwhelming majority of such companies fail in their initiatives. Companies need to realize that they need to be agile and nimble in adopting cutting-edge technologies in a structured manner to successfully deploy their own model of digital transformation, altering their business processes and operations in an optimized fashion.

Three ‘Ds’ are Reshaping the Energy and Utilities Sector

To avoid failure, energy and utilities companies need to rejig their business processes by adopting AI, ML, IoT and big data technologies in their digital transformation processes. This process is impacted by the business environment in which energy and utilities operate, in which the three ‘Ds’ of decarbonization, decentralization, and deregulation is turning the industry on its head. Add to it the shift of the consumers to clean energy, where mostly in developed western countries, the fossil fuel led mix of energy solutions are no longer acceptable to the consumers, consumers are asserting their preferences. All these factors contribute to the cause of digital transformation in energy and utility companies, where they adopted the above-mentioned advanced technologies for their betterment and consolidation.

As decarbonization and deregulation continuously impact the sector, a gradual shift has already started from the regulation and highly centralized working structure of the energy and utility companies to the world, where ‘prosumers’ rule the roost and are producing and consuming their own electricity. So, to grow their customer base and retain their existing customers, energy and utility companies need to completely overhaul their consumer service, making it seamless and working across various channels right from online to physical stores, and thereby using the AI and ML technologies to impact their services positively. Technologies such as these are helping energy and utility companies to make their operations sustainable by using and supplying energy from clean and renewable sources and thus majorly impacting demand and supply of electricity, make the entire supply chain valuable and transforming the energy industry with AI solutions and change the ways companies conduct their business.

Digital Transformation in Context of Machine Learning (ML)

As per the studies conducted, an overwhelming 95% of energy and utility companies fail to get any sort of returns or even partial returns from their digital transformation processes and only a minuscule 5% of companies make a cut for the better. One of the major reasons for this dismal picture can be the over-focusing on new technologies rather than concentrating on customers. Smarter utilities through machine learning are now a reality which is transforming the way utilities work and evolve with a future technology roadmap. In this regard, it becomes important that energy and utility companies make effective use of data which is generated enormously in all the business processes that are automated and changed as per the digital transformation initiatives.

Hence, the reliability of data and the quality of data have become a major concern for energy and utility companies, so that analysis paralysis is avoided and companies make major and effective decisions based on solid facts, not just assumptions. Machine learning systems are continuously improving the quality of data that energy and utility companies are getting and make sure that inaccurate data sources are identified and corrected so that high quality accurate and real time data can be used for analysis and thereby for making important decisions. This is an important facet of smart energy management, due to which functioning of utilities becomes optimized and streamlined.

Same is the case with distributed energy resources management systems, which are increasingly used to manage the complexity of the smart grid and effective methods of load distribution that make the smart grid totally self-sustaining and using energy from clean sources to feed electricity to the grid. Smarter utilities through machine learning for energy distribution models are being utilized to balance the grid and manage the smart grid where energy is produced from various sources for an effective distributed energy resources management system.

Artificial Intelligence in Energy and Utilities

Artificial intelligence in energy and utilities is transforming the ways such companies conduct their business and deal with various challenges facing them. As the consumers of energy and utility companies evolve as mentioned before in this write-up, the energy sector used to be a laggard. However, AI is changing all this and the sector is utilizing newer and transformed methods of data collection, data storage and management methods to suit the AI technologies. Smart energy management entails a lot of handling and collation of data. With the aid of AI technologies, enormous quantities of data can be stored, processed and managed with optimized solutions which is both cost and time effective. This helps energy and utility companies to become more competitive and companies can get newer insights which help them to transform their operations for the better.

As the modern world marches on the path of Industry 4.0, the global population needs more and more energy and also the businesses need a stable and reliant supply of more and more energy for them to carry out their operations. In the realm of AI forecasting, energy and utility companies use predictive analysis to eliminate obsolete processes, ensure energy conservation and adapt themselves to volatile business and operating environments and above all to provide better customer service. With the help of concepts like deep learning, it is making evident that forecasting is accurate and bang on target in the energy and utilities sector. Companies are forecasting demand changes, system overloads and outages.

Prediction of Failure and its Prevention

Energy and utility companies need to be careful they handle their transmission and distribution infrastructure as it may cause mass outages and have various unintended consequences, like deadly forest fires that engulfed California a couple of years back. AI can be used in such contexts to prevent infrastructure overload and also predict potential breakdowns. Energy and utility companies are increasingly relying on drones and lidars and digitizing their infrastructure and better visualize their capacities with the help of deep learning algorithms.

IoT in Energy Management

IoT is paramount for a digital future of energy and utility companies. The specific portion of IoT dealing with such systems is also called the internet of energy (IoE). Such type of technology is important to make the energy sector cleaner and more efficient and empowering consumers. Thus, IoT in energy management is necessary in each and every critical stage of the energy production and distribution process.

To this end, there are countless number of systems that use natural gas, nuclear, coal fuelled or steam powered turbines that produce electricity and, in the process, a huge quantity of data that is collected by various sensors that such systems are equipped with. This also helps energy and utility companies to constantly monitor the health of the entire system and predict faults or even outages with the help of IoE. The IoE acts as a pulse of the entire system in its entirety, and is constantly monitoring the various parameters of the individual and isolated and as well as connected systems and making measurements and collecting data. Due to the dynamic and real-time nature of data that is collected by the IoE, and this increases the reliability and usability of the collated data from such sources to form a better and much more reliable energy production and distribution processes.

Parting Thoughts

The energy and utility companies are in a constant pressure to provide reliable services and also look at issues like sustainability and decarbonization to move from a fossil fuel-based system to a more decentralized system. Hence, there are a lot of challenges and opportunities that energy and utility companies to create smarter utilities through machine learning and other allied technologies. Analytical models and other advanced AI based technologies, combined with IoT systems produce a nimble and agile energy and utility companies that are able to create controlled and distributed energy flows, make smart grids and avoid disruptions through manmade reasons or due to natural calamities. Thus, there is a bright future of the cutting-edge technologies that this write-up mentions to transform the energy and utility companies into self-sustaining entities that are highly responsive to the demands and preferences of their customers and also are sustainable entities, contributing to our climate response.

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