Renewable energy business is continuing to grow all over the world as the entire world is looking for clean and alternative energy source to control the pollution.
IOT solutions are helping this business to improve operational excellence, efficiency, cut cost, fix issues proactively, increase productivity and profitability. The effective use of IOT is the differentiator among the competitors. Real-time analytics can make a significant difference to act quickly to identify and fix issues and improve operational excellence. The challenge in the system is the amount of data being collected from the power sources, it is huge. This challenge is common for both wind and solar energy systems where the wind turbines and solar panels are many in number and are spread across various places. As the amount of data being generated is huge from these sources, the cost of sending these data to the cloud and using big data infrastructure are increasing the overall cost of operations. And it impacts the network latency and performance.
In a large Wind energy farm, the IOT system is collecting data from sensors that includes Acceleration, Temperature and Vibration data from turbines. These data need to be collected and analyzed in real-time or near real-time for quick analysis and actionable insights for performance optimization to increase productivity and predictive maintenance to avoid downtime.
The challenge with this IOT system is transferring huge data from various locations in real-time to a central location to run queries on the data and perform analytics. This makes the cost of data transfer much higher than the benefits it is giving.
In solar energy infrastructures, the essential data that can be collected from the sensors by IOT system includes Irradiance (Solar panel tilt angle), wind factors. Ambient temperature and location. This data can be used for performing analytics, compute predictive algorithm, calculate the energy that is being generated in all the connected solar energy system, analysis of energy generation pattern, Fault/ Problem detection and Real-time visualization of the solar systems. The data need to be collected and analyzed in real-time
Like IOT system for wind energy, the challenge of transferring huge data in real-time to cloud exists in this IOT system also as the size of the data from each Solar unit is huge.
Decentralization – Edge analytics
Decentralization of data storage, processing and analytics can solve the problem of sending huge data to the centralized cloud. Ability to run queries at any given time can be achieved by Edge analytics. The data generated from the solar panels or wind turbines can be filtered at the edge and send only the meaningful data to the cloud to run queries for analytics, this will help to reduce the data transfer cost. Real-time and post-mortem analytics can also be done completely in Edge gateway or with cloud analytics whichever is the best suitable and cost effective for the specific renewable energy use case.
So, the existing challenges in IOT systems of renewable energy can be handled by implementing a decentralized IOT solution with data filtering, processing, and analytics done in Edge side of the IOT solution.