PREDICTIVE ANALYTICS IN POWER OPTIMIZATION

The striking fact about the decades ahead is that we are beginning a perpetual global energy crisis and it will transform everything about how we live. Therefore, it’s quintessential that we optimize our power production and distribution to minimize losses and use our energy resources judiciously.


Here is how Industry 4.0 has come to the rescue


1. Optimizing Power Consumption

One of the most primary challenges faced by the energy sector is the looming exhaustion of resources used for power generation, namely the non-renewable fossil fuels. The alternative sources - nuclear energy, wind, solar energy, etc. are still either costly or dangerous. Therefore, its high time to shift the focus on efficient energy management by power producers, distributors, and consumers. On this road, smart grids are being installed to improve performance and maintenance. The smart grid is fundamentally an automated system that connects all entities in the power sector, enabling them to associate with each other in real-time. These smart grids study the historical data to analyze and identify fuel consumption patterns to detect any irregularity in the system. Also, these grids can recognize the circumstances under which the breakdown happens. During maintenance, staging equipment can be utilized to depreciate, or even diminish, downtime. Real-time waveform monitoring and additional predictive analytics methods can be used to create timely insights on equipment performance and help dodge downtime occurring due to overloading, voltage fluctuations, and damages to ancillary equipment. These measures ensure that power usage is efficient and not disturbed by any equipment inefficiency.


2. Patching the loopholes in Transmission & Distribution

Even in 2020, many countries like India, face huge T&D losses. According to a study, India still faces 20% T&D losses, albeit the fact that it faces a worrisome power deficit. However, with accelerated technological advances and the rise of IoT, it is becoming easier to track and monitor disruptions in supply. With the deployment of Predictive Analytics, data from equipment such as sensors, smart meters, and other communications devices can be studied to generate actionable insights for T&D companies. This method is called "asset analytics." It assists T&D companies in enhancing productivity based on measures such as asset health, criticality, and maintenance schedule.


3. Giving the consumers their consumption insights

The Big Data generated by meters, costs, business policies, production figures, asset operations when assessed will prove to be a sustainable solution to handle the energy requirement for the future. With the availability of reliable data and actionable insights, consumers or the ordinary people can be persuaded of the urgent necessity to replace or repair energy-inefficient devices by presenting the details on long-term cost indications using predictive analytics. This will be a significant step to raise public awareness as well as minimize power requirements.

With both the industries working together, there is hope for improvement and solution to the energy crisis.

The change we brought
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Most advanced ready to use AI modules for manufacturing data analytics
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Tvarit The Team
We’re based out of Frankfurt Germany having the perfect team composition - a German founder bringing vast know-how of machinery coupled with high-quality software expertise of the Indian founders.
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