The energy ecosystem is in the midst of a transformation, driven by advances in technology acceleration, rising use of renewable and distributed energy sources, and the consumption typology. To satisfy the demand amid the intermittent surge in generation sources and volatile energy demands, energy grids have been put under immense strain; and in Europe alone, 60bn euros are spent on maintaining it.
Nonetheless, current energy grid infrastructure is not efficient - grid operators are not aware of the real-time state of the grid, unable to pinpoint stress locations, and cannot properly take maintenance measures. Predictive and preventative maintenance methods need to be put in place in order to properly address this rising volatile energy, and new ways of monitoring the grid
Sensewaves tackles this issue with the first product built on their modular machine learning streaming analytics platform – Adaptix. Adaptix grid conducts dynamic grid analytics, brings transparency to the grid by transforming raw time-series data into actionable insights, and predicts future situations to avoid outages. The solution leverages only data coming from smart meters, thus avoiding the need to deploy additional infrastructure across the grid. Its data analytics captures, analyses and interpret critical data constantly adapting to ever-changing environments and predicting multiple scenarios with related likelihood. Predictions are fully justified by past events on which the analysis is based so to leverage on human operators’ expertise.