Energy Fault Detector - Autoencoder-based Fault Detection for the Future Energy System
Energy Fault Detector is an open-source Python package designed for the automated detection of anomalies in operational data from renewable energy systems as well as power grids. It uses autoencoder-based normal behaviour models to identify irregularities in operational data. In addition to the classic anomaly detection, the package includes the unique “ARCANA” approach for root cause analysis and thus allows interpretable early fault detection. In addition to the pure ML models, the package also contains a range of preprocessing methods, which are particularly useful for analyzing systems in the energy sector. A holistic EnergyFaultDetector framework is provided for easy use of all these methods, which can be adapted to the respective use case via a single configuration file.
The software is particularly valuable in the context of the future energy system, optimizing the monitoring and enabling predictive maintenance of renewable energy assets.
Installation
To install the energy-fault-detector package, run:
pip install energy-fault-detector
Contents
- The Energy Fault Detector package
ConfigFaultDetectorquick_fault_detector()- energy_fault_detector.anomaly_scores
- energy_fault_detector.autoencoders
- energy_fault_detector.config
- energy_fault_detector.core
- energy_fault_detector.data_preprocessing
- energy_fault_detector.data_splitting
- energy_fault_detector.evaluation
- energy_fault_detector.quick_fault_detection
- energy_fault_detector.root_cause_analysis
- energy_fault_detector.threshold_selectors
- energy_fault_detector.utils
- energy_fault_detector.fault_detector
- energy_fault_detector.main
- energy_fault_detector.registration
- Usage examples
- Logging Configuration