We see homes, businesses, and other private and public buildings depend on electric energy everywhere we look in our communities. By 2040, we can expect a 58% rise in global energy demand. As far as solutions go to address the energy supply, many have turned to renewable energy sources and adopted microgrid and smart grid technology and infrastructure.
In recent years, the development and implementation of artificial intelligence in smart grid solutions have demonstrated some pivotal changes in how we collect and use energy consumption data to our advantage. Namely, AI and automation capabilities enable the smart grid to predict energy consumption trends. How reliable are the energy supply and demand predictions that smart grids produce? Continue reading on to find out, and check out EcoStruxure Grid for more information.
Why These Predictions Are Useful
Smart grid technology fits perfectly into a landscape where many see the value of digitizing power generation and distribution systems. Using the increasingly prevalent IoT-connected devices and meters, facility managers and electricity companies can capture a wealth of information and data points across the smart grid system. Once the data points are analyzed with AI algorithms, it could reveal insights and predictions on the grid activity. This way, energy producers and consumers can anticipate higher or lower levels of energy consumption.
How Renewable Energy Affects Grid Stability
Despite industry advancements in renewable energy, there still exists a degree of unpredictability when working with solar or wind sources. In communities that have adopted the smart grid, the local utility authorities need to adjust the area’s grid to integrate the unpredictable amount of energy generated from the area’s renewable sources. Therefore, optimization issues can arise if the grid is still operating on a reactive rather than predictive basis. As efforts to improve grid stability progress in regards to harnessing renewable energy, the focus must stay on generating enough energy and controlling where the energy flows or gets distributed.
How To Make More Accurate Predictions with The Technology
The more data that operators make available to smart grid systems, the more refined the insights and predictions become. Fortunately, automated smart grid systems that use advanced AI technology to make these energy consumption forecasts can draw from several thousands of data points across a connected grid. In order to scale these predictions to formulate a more accurate forecast of the energy landscape in real-time, cloud computing is necessary to accomplish this feat.
Is The Technology Reliable?
The outlook for the continued usefulness and reliability of smart grid energy consumption predictions is quite optimistic, but still reasonably cautious. We still have human experts examining and refining the technology every day. There are still engineers and utility workers monitoring the energy grid to prevent disruptions and finding areas for improvement. However, just as these types of smart technology are implemented in other aspects of modern infrastructure optimizing operations, we can expect this to happen in electric energy and grid management. Simply put, trust in the technology builds as smart grids continue to deliver more accurate and valuable predictions.
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At Critical Systems, the people come first, from our employees to our customers. We strive to attract and develop the best talent in the business. Our goal is to deliver innovative solutions for the purpose of making every building secure, efficient, and effectively managed. Serving the Washington D.C., Northern Virginia, and Baltimore regions, SEBCSI provides innovative solutions for your commercial building or facility. Visit our website and follow us on Facebook, Twitter, Instagram, and LinkedIn today! If you’re looking for more information or interested in working with us on your next project, please contact us!