How Robotics Impacts the Renewable Energy Sector?
manufacturingtechnologyinsights

How Robotics Impacts the Renewable Energy Sector?

By Manufacturing Technology Insights | Tuesday, February 26, 2019

With today’s energy crisis at hand, it’s important to look forward to ulterior forms of renewable and eco-friendly energy. AI, with the help of the internet of things (IoT), can reduce utility bills in smart homes or can help to save cost by foreseeing industrial level problems. A new trend in renewable energy involves combining solar and storage, which delivers cost savings to both solar provider and user. Setting up a solar project can be costly, given the volatility of subsidies for investing in renewable energy.

The renewable energy industry is an extremely data-rich environment. The benefits of applying artificial intelligence in this industry are only as farfetched as a mind can stretch. There exist remote inspection robots that troubleshoot and help with maintenance, robot crawlers which can get close to a structure’s surface that makes use of ultrasonic or microwave transmitters, which penetrates structures to identify faults in materials. Autonomous robots used in supply chain optimization can be used to build entire solar and wind farms—transporting parts of a wind turbine and solar array from factories by self-driving vehicles, and finally assembled by drones and sets of robots. This reduces the time invested in planning and analysis which could take a group of human hours.

Few Renewable  Energy Solution Providers (AditazzFirst Solar, Helios Energy )

The utility industry has the potential to embrace artificial intelligence. Machine learning could be used to forecast demand and supply in real time, and optimize economic load dispatch. With AI, power suppliers optimize generation efficiency with real-time adjustments across their assets. Predictive maintenance can be strengthened with drones for asset inspections, thus replacing manual inspection. The drones are trained using deep learning algorithms to predict failures and identify defects without interrupting the operations automatically. Demand management can be made smarter and automated with machine learning. Energy theft is a significant issue to be noticed in some developing countries, where theft accounts for up to 40 percent of the electricity distributed. AI can be used to detect the payment history and usage pattern to signal any aberrant behavior.

The combination of renewable energy and AI seems to be a perfect bond of emerging technology. Until producing cheap and limitless nuclear power is feasible, conserving resources and making renewable energy affordable is the only option.

Check outTop Renewable Energy Solution Providers

Weekly Brief

New Editions