3 Use Cases of How Big Data Analytics Makes the Energy Industry Smart

3 Use Cases of How Big Data Analytics Makes the Energy Industry Smart

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Reduced energy consumption, the search for new renewable energy sources, and increased energy efficiency are important Big Data goals for environmental protection and economic prosperity. Big amounts of moving data are increasingly being watched and analyzed in real-time, which aids in achieving these objectives. Many large custom software development companies and mobile app development corporations employ various methods to ensure that they have the energy resources they require today and in the future. Nontraditional energy sources such as solar farms, wind turbines, and wave energy are becoming more viable possibilities as fossil fuel prices and availability continue to be an issue.

big data analytics in the energy industry

Electric utilities opt for smart grids with the development of modern metering infrastructure and big data capabilities to gain strategic insights to support optimal energy use. FortySeven IT professionals will be showing you three real-world instances of the extent to which big data analytics helps the energy industry, based on our experience working with electric utilities. In this article, Hanna Shnaider, Head of Marketing Department at FortySeven, explains the extent to which big data analytics may benefit the electric power industry. You can find out more about her here.

Use Cases of The Way Big Data Analytics Makes the Energy Industry Smart

The following are the most common applications of big data analytics in the Energy & Utilities sector:

Fault detection and predictive maintenance

It is common knowledge that equipment failures in the energy industry can result in catastrophic power outages and large quantities of money spent on new assets, restoration work, and energy losses. A power outage can bring an entire country to a halt, as the Northeast blackout of 2013 did in the United States, affecting nearly 45 million people. Unfavorable weather is one of the leading causes of power disruptions. Nonetheless, electric and utilities custom software development firms are developing smarter infrastructure and sensors to improve predictability and avoid such outages.

Modern power outage systems by some custom software agency use real-time solutions based on live data and smart algorithms to predict and prevent catastrophes. These systems can estimate the influence of any near-real-time asset values on the network grid, as well as possible outages induced by smart meter events, regional outages, and more.

Electric power quality

The quality of electric power influences the safe operation of a power system and consumer happiness. Big data software, fortunately, goes much beyond spotting anomalies a posteriori. For example, at FortySeven47 we can help our customers set up continuous power quality monitoring to establish an “early warning system” using deep learning and pattern recognition algorithms. With this system, you may rapidly and reliably examine all data connected to power quality and detect and categorize deviations from the norm that emerge in power grids. Once the deviation has been categorized, the reason can be determined and preventative measures taken to avoid downtime and production losses.

Load Management

Energy is a capital-intensive custom company that places a high value on equipment and network infrastructure performance. Failure of these assets could result in major power distribution issues and, as a result, a loss of consumer trust. As a result, one of the primary concerns of the industry is to prevent similar events.

Big data analytics comes to the rescue when it comes to preventive equipment maintenance. Smart sensors, trackers, and data solutions are incorporated into the assets, relaying real-time data to the center. The information gathered can then be processed and analyzed to identify potential equipment maintenance concerns, allowing for proactive problem-solving. And utilities are not the only ones who benefit from this situation: when in-home displays and programmable communicating thermostats are combined, electric power users gain access to information that can encourage them to make changes in their energy consumption, advancing the era of conscious energy consumption.

Big Data and Cheaper Energy

Combining Big Data and data analytics with low-cost energy solutions, according to CitiBank, might eventually lead to free energy. Utilities can provide cheaper power by better matching energy supply and demand. But this is just the beginning. The idea behind free energy is to allow users to store surplus energy and then sell it back to the grid, basically recycling energy. Another custom software development technology to anticipate is virtual power stations. The technology connects energy storage devices and controls them from a single, digital place. Although free energy is still a long way off, one thing is certain. The price of power generation and consumption is being driven down through Big Data analytics!

Big Data Testing for the Energy Industry

A custom software issue in the deployed modern grid systems triggered the power outage of 2013, which we discussed earlier. Energy development companies must examine the issues that may develop due to poor custom software development technologies as a custom software developer implements highly complex infrastructure to offer reliable and uninterrupted electricity.

Because so much depends on real-time transmission and analysis of big data throughout the grid, it is past time for the industry to recognize the importance of big data testing as well as end-to-end testing.

A top-tier home comfort system provider sought a low-cost load generation environment like software development companies to investigate baseline reaction time on concurrent usage. They improved response time by 30%, hardware performance by 25%, and server performance and scalability by 20% using a cloud-based lead generation technique.


Many electric utilities companies have already started implementing big data analysis because of the benefits that predictive maintenance, power quality monitoring, and load control are capable of bringing to the energy software development company. The usage cases that were listed in this article are not all-inclusive.

A big data journey can take a lot of time and be fraught with dangers. But certainly, the result is always worthwhile when you have the appropriate approach set in place. Whenever you are unsure where to start or believe your existing big data solution lacks, FortySeven software professionals will be happy to assist you; let us know.


Written by

Alexander Sterling

Alexander Sterling

Alexander Sterling is a renowned financial writer with over 10 years in the finance sector. With a strong economics background, he simplifies complex financial topics for a wide audience. Alexander contributes to top financial platforms and is working on his first book to promote financial independence.

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Judith Harvey is a seasoned finance editor with over two decades of experience in the financial journalism industry. Her analytical skills and keen insight into market trends quickly made her a sought-after expert in financial reporting.