Get the best from your data gathering
Hydro
Our services enhance the capabilities of hydro assets, making possible to get optimal performance, by reducing production loss and improving O&M scheduling. Our software enables plant asset managers to create more value from data gathering, through big data analytics, Machine Learning and Artificial Intelligence techniques.
EFFICIENCY IMPROVEMENT
Detection of non-optimal operations and of their impact on energy production.
FAILURE ANTICIPATION
Early detection of faults, by identifying root causes in an autonomous way to minimize downtimes.
SENSORS ANALYSIS
Analysis of sensors behavior in order to identify anomalies in the transmission of information.
KNOW-HOW EMPOWERING
Smart sharing of knowledge about components and analyses among plants’ operators.
Plants
GW
Nations
Hydro
Advanced digital condition monitoring
The true value from hydro fleets data gathering and analysis
Our software combines data gathering and big data analytics application obtaining the digitalization of sophisticated risk-based decision-making tools, to optimize near-term O&M asset management plants in order to maintain, overhaul or replacing the most critical components of the fleets. i-EM has developed, customized and trained advanced algorithms able to perform deep and multivariate analysis on plants data, in order to allow hydro O&M operators to take appropriate decisions and apply strategies to extract the best achievable value, exploiting all of the information contained in data themselves.
Data exploration
Goal:
- Monitor signals from the plant
Features:
- Visualize time trend of the signals
- Scatter plot between two signals
Data quality check
Goal
- Identify criticalities on sensors and data transfer/acquisition chain
Features:
- List of bad/good signals visible and exportable as text file
- More information available for each signal with time trend, distribution histogram and detailed quality report
Efficiency analysis
Goal:
- Monitor the working efficiency of the plant and identify not-optimal periods or GUs management
Features:
4 different kind of scatter plots:
- Efficiency VS water flow
- Efficiency VS net head
- 3D plot: efficiency VS water flow VS net head
- Efficiency VS water flow with reference to historical efficiency curves
- Filter on regular and transient data
Analytics as a Service
Goal
- Identify and predict anomalous condition on the plant, exploiting operators experience
Features
- Customized signals selection as input of the multivariate statistical model (data quality results are indicated in order to select only signals with the best quality)
- Customized definition of training and test time period
- KPI visualization, warning indication and most critical signal detection for the test period
Analytics as a Service: output
Goal
- Identify and predict anomalous condition on the plant, exploiting operators experience
Features
- Customized signals selection as input of the multivariate statistical model (data quality results are indicated in order to select only the signals with the best quality)
- Customized definition of training and test time period (real-time runs also available)
- KPI visualization, warning indication and most critical signal detection for the test period
- Comparison between measured variable and simulations from an ensemble of ML models
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