Artificial Intelligence And The Power Sector A Promising Future
The world is moving towards digitisation. A lot of us across the world are working from home and attending meetings via Zoom, Teams, Slack , Yammer, and WhatsApp video calls. The pandemic has reinforced the value of digitisation in our lives and compelled the uninitiated to quickly learn the new skills for staying relevant and useful for their business. Keeping in line with this trend, a lot of verticals in the economy are moving to upcoming technologies like Data Analytics, Artificial Intelligence, Internet of Things, etc. One of these verticals is the power sector.
Artificial intelligence (AI) has the potential to cut energy waste, lower costs, and accelerate the use of clean renewable energy sources in power grids globally, along with improving the operation, maintenance, control, planning and plan execution of power systems. AI is thus closely tied to renewable, clean as well as affordable energy that is necessary for development. The power sector has a bright future with the advent of AI-managed smart grids if implemented well. In addition, AI brings the customer back in focus by connecting power generators, gird managers and end consumers to be connected and served efficiently and better. It must also be stated that AI is also employed to reduce the environmental impacts from thermal power plants, improve their performance and thus play a more efficient role in supplying power to the grid.
AI powers electrical grids that allow two-way communication between utilities and consumers. Smart grids are embedded with an information layer that allows communication between its various components so they can better respond to quick changes in energy demand or urgent situations. This information layer, created through widespread installation of smart meters and sensors, allows for data collection, storage, and analysis. Given the large volume and diverse structure of such data sets, techniques such as machine learning, Internet of Things, etc are best suited for their analysis and use. This analysis can be used for a variety of purposes, including seamless fault detection in meters, predictive maintenance needs, quality monitoring of sustainable energy, as well as renewable energy…