‘AI is the new electricity’ in a world that is reeling under myriad tech innovations. AI has the power to transform data collection, storage, and management, allowing the energy sector to catch up with today’s requirements while keeping the future needs in mind. Despite the size and enormity, the energy sector still heavily relies on manual work. This sector has a lot of catching up to do. And one way to look at this is to integrate data analytics into it. This development is also important to achieve the Sustainable Development Goal 7 (SDG7), aimed at ensuring access to affordable, reliable, sustainable, and modern energy for all by 2030.
While there is no doubt that the demand for renewable energy is only going to increase, it is more important to understand the factors that hinder the scalability of it. There are several benefits of renewable energy today, but without intelligent forecasting and scheduling of the resources, industries cannot benefit to the fullest. Especially in a country like India, the unpredictability of the weather is a challenge. And it is where the use of intelligent tech interventions like data analytics and machine learning can help make data-driven decisions to predict weather conditions, maintain the supply chain, improve productivity, increase affordability while improving shortcomings. An amalgamation of these technologies will ultimately lead to the modernization of the energy sector, which is critical for every country’s economy. Efficient data management can change the face of the industry for good and fast track developments.
– Data forecasting: Shortage of energy is a global problem. One of the primary requirements of the energy sector is predictive analytics. There is an urgent need to upgrade predictive analysis methods to cut costs, save energy, become adaptable to changing conditions, and improve end-user experience. It is where data analytics and big data can enhance the power of forecasting for better. The cost of error in the renewable energy industry is high, and forecasting can help avoid that and predict changes in demand, overloads, and possible failures as accurately as possible.
– Efficient resource management: Resource management is equally necessary for the energy sector. And with data analytics and predictive mechanisms, renewable energy suppliers will be able to make informed decisions. It helps them in preparing for demand well in advance, predicting problems at the grass-root level, dispatching their resources better and saving resources to the best possible extent. And these can translate to low energy consumption and bills for end clients.
– Intelligent storage of resources: Thanks to efficient resource management, there is a growing need to store renewable energy. In such a scenario, additional capacity and new management systems are of prime importance, and big data and analytics help efficient storage of renewable energy. They help by rightly optimizing energy storage.
– Improving safety and reliability: Data analytics and big data offer improved safety, efficiency, and reliability by helping companies understand usage patterns, identify energy leakage and the health of the devices.
– Predicting failure and prevents it: Energy can be very hazardous when handled poorly. And it is more than necessary to implement data intelligence to predict and prevent deadly disasters. For instance, AI can predict system overloads and warn of potential transformer breakdowns.
Advanced technologies like big data and analytics have had an enormous effect on every aspect of the modern world today, and the energy industry is no exception. However, the pace at which it is implemented must be fast-tracked, as it has the potential to revolutionize the sector. While AI is famously known as the technology of the century, it will be interesting to see how it makes its presence felt in the renewable energy sector, in the days to come. Implementation of data analytics and big data will be the most efficient decision stakeholders in the industry can make today to reap benefits in decades to come.
Tags:big data to address challenges Data analytics Inspira renewable energy sector