Edge Analytics 101: Key benefits and insights explained

A close-up of a smart meter that supports edge analytics

Edge analytics has found its place in the everyday vocabulary of nearly everyone doing business in the energy sector. However, despite its popularity, it is not always clear what the term is about. Essentially, it is a combination of two words: “edge” showcases the proximity to the data source at the periphery of the grid and “analytics” refers to data processing. So, let’s take a look at what edge analytics is, its benefits, and how it can drive smarter, real-time energy decisions at home.

What is edge analytics?

Edge analytics is an approach to data analysis that allows for energy data to be processed and analyzed closer to the source. By integrating advanced AI models directly into smart meters, data can be processed in real time, at the grid-edge, eliminating the delays, costs, even limitations of sending loads of raw meter data to centralized data centers or cloud-based services to get data processed. This behind-the-meter visibility unlocks new use cases, such as dynamic grid management and residential flexibility, as well as customer collaboration through behavioral recommendations and personalized energy insights.

The evolution AMI data:

As one of the first technological advancements that paved the way for the energy industry’s digital transformation, Advanced Metering Infrastructure (AMI) revolutionized energy management and monitoring. AMI 1.0, the first generation of AMI meters, initially brought a shift in the energy landscape: through an hourly/half-hourly/quarter-hourly collection of energy data and automated meter readings that made manual meter readings redundant, AMI 1.0 made the energy consumption data more accurate and reliable, reducing billing errors and unlocking new potential.

Despite opening up new avenues for the energy transition, AMI 1.0 can be quite limited and not able to correspond to the emerging demands and needs of the energy ecosystem amid the emerging electrification process. In recent years, distributed energy resources (DERs), including electric vehicles (EVs) and solar photovoltaic panels (PVs), have brought extra changes to the energy mix and the new challenges have been threatening the overall grid stability and reliability. In the North American context, with today’s energy ecosystem being dynamic, there is a dire need for the grid to become smarter and more resilient. At the same time, the rise of hyper-personalization on multiple levels has increased consumers’ expectations, making near real-time feedback a necessity.

Edge analytics is key to tackling all these emerging challenges since it allows for real-time data processing at the source. AMI 2.0 represents the next stage in the evolution of AMI data, harnessing the power of edge analytics to the fullest. By leveraging this new generation of AMI meters, advanced data analytics is performed directly at the grid-edge and in near real time. Through this inside-the-meter approach, the obstacle of limited data is overcome while the former conventional way of data processing now transforms into AMI 2.0, a robust edge-computing network. Thus, edge analytics translates into integrating advanced AI models directly into smart meters, reformulating how data is processed and utilized within the grid.

Edge analytics and its benefits:

1. Faster decision-making, less delays

   
   

   With edge analytics, there are no unnecessary delays. By processing data at the point of collection and not sending it to centralized locations, both the distance and the time that the data needs to travel is significantly reduced. Such an approach makes near real-time information easily accessible, allowing for fast and effective decision-making. An example of this involves EV charging: when consumers receive insights informing them about low electricity rates or the current charging demand, both cost savings and grid reliability are ensured.

   
   

2. Scalable, sustainable, and budget-friendly growth

   
   

   By enabling faster data processing closer to the source, edge analytics supports scalable and sustainable growth. With edge analytics, multiple devices are utilized, taking the pressure off centralized data centers or other network infrastructures. In the long run, this approach to data processing reduces expensive data transmission while making large, high-maintenance data centers less overwhelmed.

   
   

3. Privacy-first, trust-guaranteed

   
   

   Edge analytics has the power to significantly enhance security and data privacy; by processing data at the point of collection, the risk of data breaches is minimized and sensitive information remains within the limits of well-controlled and secure environments. In this case, detailed household energy data is processed locally and only relevant insights are sent to the utility. With the privacy of data being one of today’s highest priorities, trust and confidentiality is guaranteed.

   
   

4. Richer data, smarter insights

   
   

   By unlocking richer, high-resolution data, this advanced analytics approach has the power to deliver deeper and more actionable energy insights; this leads to smarter decision-making and unveils an array of grid-facing and customer-facing use cases, such as the ability to provide behind-the-meter visibility and grid monitoring. More information here.

Unlock value with NET2GRID EnergyAI®:

NET2GRID EnergyAI®, NET2GRID’s AI-powered software as a service, leverages the power of edge analytics and offers cutting-edge, real-time energy disaggregation, providing DER Intelligence. With robust APIs that are easy to integrate and while making the most of AI and deep learning models, NET2GRID offers highly accurate and actionable energy insights. A real-life example of collaboration that tests and proves the value of edge analytics is that of NET2GRID with Itron, empowering the grid of the future. With the help of AMI 2.0 technologies and, in particular, Itron Riva, utilities are empowered to engage with their customers, building trust-first customer relationships, and, at the same time, boost grid efficiency fueled by Distributed Intelligence. Discover more about NET2GRID’s edge capabilities here.