THE AWESENSE DIFFERENCE
NO MASSIVE CAPITAL OUTLAY
Traditional approaches to solving grid issues involved large capital investments in equipment. But it is impossible to permanently monitor everywhere, and this approach is simply too expensive.
Awesense IoT devices reveal true operating conditions on the distribution grid, sampled at strategic locations.
NO MASSIVE IT PROJECTS
Pure analytics companies have begun to look to Big Data (smart meters, consumption patterns, weather, etc.) to predict where losses and problems exist. But this approach kicks off costly, high-risk IT projects that still miss that important data from within the grid - AND these solutions are only suited to big utilities who have fully-deployed smart-meter infrastructure.
Awesense proposes a smarter approach.
Analytics + In-Grid Data + Services
Awesense uses data from IoT sensors that sample live lines on the grid (in between the substation and the consumers).
Our algorithms logically sub-divide the grid into manageable segments and use risk-based analytics to identify high risk segments of the grid.
Our team applies a proven methodology to systematically reduce losses and helps build a risk model to enhance wider enterprise risk strategies.
LOOK IN THE INVISIBLE PART OF THE GRID
From Generation to Transmission right down to Distribution substations, the grid is well-monitored. And out at the edge of the grid, at the customer level, there is also ample monitoring (often including smart meters).
But in between the Distribution substations and the customers there are thousands of miles of unmetered lines and connections where theft and errors occur. Permanently monitoring this "invisible grid" is economically impossible yet there are millions of dollars worth of non-technical losses to be recovered.
TIP LINES CAN'T FIND EVERYTHING
In-grid data eliminates the guesswork and allows utilities to find losses that would go otherwise undetected. Conventional revenue protection solutions can only find some types of losses.