Electricity Price Forecasting
Customer
Energy Company
Developing forecasting model to predict electricity prices and help traders make better decisions resulting in a 25% reduction in deviation compared to previous models in place
Challenge
- Client needs accurate electricity price forecasts for internal trading team
- Goal to improve price forecasting using a fixed train/valid/test reference dataset
- Need for a new probability forecast to be implemented
Solution
- Built backtesting pipeline and test multiple forecasting configurations (multivariate time series)
- Developed forecasting solution which generated probabilistic forecasts with consistent prediction intervals
Business Impact
- Unit8 model significantly improved forecasts compared to previous solutions in place
- Reduced deviation between forecasted and actual prices
- by 25% compared to previous model
Hydro-electric Plant Predictive Maintenance
Customer
Swiss Energy Company
Building a predictive maintenance model to detect abnormal measurements earlier, leading to better maintenance planning and cost reduction
Challenge
- Currently no reliable long-term anomaly detection system
- Slow-shifting anomalies are hard to detect with human surveillance as they can take months
- Goal to have a predictive maintenance system to spot these issues early and plan maintenance more effectively
Solution
- Unit8 built a predictive machine learning model for physical variables of interest (e.g., temperature or vibration)
- Define a threshold for values to be throughout the day and sends automatic alerts if a value differs significantly from model predictions
Business impact
- Engineers able to detect abnormal changes in measurements much earlier
- Maintenance can now be planned effectively
- Shorter stops in electricity production leading to lower costs due to plant shutdown