GEMINI
The advanced analytics and predictive diagnostics solution for optimized energy production.
Hight asset efficiency, profitability and performance
Predictive analytics for wind asset monitoring
Horizon Gemini’s Predictive module utilizes AI algorithms, backed by domain expertise, to detect anomalies in CMS vibration and spectra data and in
SCADA data.
Advanced analytics for solar asset monitoring
Horizon Gemini’s advanced analytics module automatically detects
under-performance, downtime, and other issues to enhance asset performance, reliability and profitability.
- Enhanced asset lifespan and performance
- Increased dependability and efficiency
- Improved operational efficiency
- Improved cost reduction
Predictive analytics for wind asset monitoring
Identify anomalies
The neural network (AI) is “trained” with the data that was received, and “learns” what a normal operation modus is.
Anomalies can then be detected against this “normal” situation using the developed algorithms if a system or customer-defined threshold is exceeded.
Anomalies to failure module
Anomalies are fed into a FMEA Matrix (failure mode and effects analysis) developed by combining the knowledge of data scientists, wind turbine technology specialists and wind farm operations experts. “The FMEA Matrix is an automated decision tree that provides the most probable failure modes for each anomaly or anomaly group”. Failure modes represent the machinery breakdown or operational constraint which may result from the detected anomalies.
Expert-enriched AI results
Wind turbine operation experts discuss the findings and recommendations of the AI algorithms and evaluate them based on their domain knowledge.
The findings of the AI algorithms are filtered according to the experts’ evaluation on plausibility, severity and urgency. This process minimizes false positives and enriches the algorithms findings and recommendations with experts’ domain knowledge.
Feedback loops
AI algorithms, combined with technical and operational expertise, enable the identification of early failures. This prevents expensive machinery breakdowns and related production losses.
Advanced analytics for solar asset monitoring
Compare main KPIs
The algorithm calculates the actual production vs predicted and theoretical ratios, considering weather corrections and multiple loss categories, to identify the primary cause of lower production.
IPI
The Investor Performance Index compares the actual production to your original budget, allowing you to assess and follow up your ROI.
OPI
The Operational Performance Index measures the difference between actual production and theoretical production, to assess losses resulting from operational issues.
Availability
Track the availability of all devices to detect potential improvement of operational tasks.
Loss partition table
Access a comprehensive breakdown of the portfolio’s loss categories.
Site-level loss partition
View loss partition for individual sites within the portfolio.
Treemap visualization
Understand the magnitude of each loss category graphically.
Dimension of losses
Identify primary loss categories and their impact on energy production.
Site-specific analysis
Identify sites with higher losses, enabling focused analysis and actions to address site-specific challenges.
Evaluate the performance of their energy production assets and identify areas for enhancement.
Waterfall chart
View the variations in energy output from the initial budgeted amount to the final actual energy production, highlighting the various gains and losses.
Granular view
Access a detailed examination of specific sites, devices, or even event-related sub-losses.
Custom thresholds
For each category of profits or losses, thresholds can be adjusted to show when they are exceeding expected levels.
Manage and resolve findings related to asset losses.
Table
Customizable table, that allows data sorting and filtering based on specific criteria, like loss category or severity.
Kanban dashboard
Findings of daily management, enabling the execution of corresponding actions to address critical issues.
Suggestions
Based on the data collected by the watchdogs, recommendations are offered to prevent losses.
Is Gemini´s predictive analytics module the right tool for your wind portfolio?
Horizon Gemini’s Predictive module has effectively identified potential damages early, resulting in substantial cost savings for clients.
