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How Data Analytics can Revolutionize Energy Sector

By CIOReview | Thursday, March 28, 2019

Big data analysis has grown in significance over the years. Organizations have become ever reliant on data analytics solutions to gain insights into their business processes and operations. In 2008, Google applied data analytics to predict the spread of disease by analyzing millions of searches related to influenza. The analysis helped healthcare service providers in providing better care to their patients.

The energy sector also has enormous potential to benefit from data analysis methods as they have reduced the use of large coal-based power plants, and have started using microgenerators and renewable energy farms for energy generation. These latest developments in the energy industry have created the need for vast amounts of data to be accessed remotely.

Many governments are emphasizing the use of renewable energy, resulting in the steep rise of investments in the sector. According to a 2017 research by renewables policy organization REN21, it was observed that an estimated 178 GW of energy capacity for renewable energy was added that year, with solar photovoltaic proving the star performer, as its energy outputs increased by about 33 percent. This increase in renewable energy is because of increased connectivity and data collection, as these measures provide financially viable and efficient methods for companies to monitor multiple sites remotely.

There are many challenges for the renewable energy source. For example, solar and wind energies require additional support to maintain a stable energy supply as they are intermittent resources. Data analysis can come to the rescue of companies by ensuring proper operation and maintenance of many unmanned assets. Companies can use IoT technology to gather data in abundance to make optimum use of the data analytics tools.

The data collection can also help energy companies in predictive maintenance and condition monitoring. Many data analytics tools analyze data to analyze the health of equipment. Predictive analytics detect any anomaly in the functioning of equipment, allowing companies to protect their devices against any major disruptions.

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