Eneco

Transcript

1. Accelerating the energy transition using data science Big Data Expo 12-09-2023 Judith te Selle | Eneco Energy Trade Titus Kervezee | Eneco Energy Trade
2. To reach climate goals we need (a lot) more renewable power • Eneco is investing heavily to increase renewable power production • Renewable sources of energy are intermittent and uncertain • Electricity needs to be consumed at the same time as it is produced • We need flexibility to make sure supply and demand match each other
3. “Power system flexibility is the cornerstone of electricity security in modern power systems.” IEA, World Energy Outlook 2020
5. How does this work in practice? 5
6. Virtual Power Plant Micro-service platform that operates between the market and the assets Data science plays a crucial role in enabling propositions on the platform: forecasting, optimization, trading algorithms Today’s use case: curtailment of B2B rooftop solar installations
8. Increased solar production leads to imbalance & negative wholesale prices Total production of electricity exceeds demand: • grid stability is at risk • prices on the market become negative Excess solar should be curtailed in case of overproduction Number of negative wholesale prices (cumulative) Win-win-win for the customer, the grid stability and Eneco
9. We cannot just curtail the solar panels 9 When curtailing we need to know what would have happened if we did not curtail • VPP needs to monitor what would happen if we stop curtailing • Realtime prediction, frequency as high as possible • Compensation for customer of missed production • Monthly batch prediction, 15-minute frequency Machine learning to estimate the what-if production ?
10. Solar power forecasting 10 Features: • Solar irradiation • Temperature • Row shading • Cloud cover • Relative humidity • Hour-of-the-day • And so on
11. We need a local solar power nowcast 11 X Y Solar irradiation Temperature Production Measured at customer site Sensors KNMI Weather stations
12. Clear correlation for customers in the proximity of a weather station
13. XGBoost outperformed other models (MAE 10.60 kW)
14. Accelerating the energy transition using data science 14 • Using publicly available data sources resulted in being able to offer this proposition to B2B customers • Currently two customers are connected • This proposition helps us providing flexibility to the grid