Roadmap 2024
Vision
Our open-source initiative aims to develop a cutting-edge machine learning pipelines for short-term energy load forecasting on the grid. These pipelines are designed for seamless adoption, boasting exceptional quality and harnessing built-in expert knowledge. The aim is to make OpenSTEF the industry standard for short term energy forecasting.
Fostering an active community, our project encourages collaborative efforts, fostering continuous improvement of the code base through contributions from multiple stakeholders.
Unique selling points
- Easy adoptability
- Automated pipelines make is very easy to train a model and make a forecast
- The example notebooks provide an easy way to get familiar with the model
- Simple interface
- Extendable
- Explainable
- Proven/benchmarked high forecasting quality
- Easily benchmarked by backtest
- Implemented at companies such as Alliander and RTE
- Build-in expert knowledge on energy systems
- Close connection to academic knowledge (latest scientific innovation)
- Feature engineering
- Energy splitting
- Fully open-source
- Community of experts
- Flexibility to be able to implement in any enterprise environment
- Scalability
- Data standard on how to handle forecast (standardization)
Plans community
Alliander - KTP team
- Improve forecast quality
- Dagster
- MLOPs architecture
- May influence the reference implementation
- Add maybe second reference implementation
- Larger scale implementation
- Add to description
- Improved DAZLs model (Q1)
- Update example notebooks
Firan
- Improve forecasting quality of peaks, with a very short time horizon
RTE
- Predict wind power on OpenSTEF.
- Predict every hour for 72 hours.
- 2500 windfarms.
- Implement new machine learning model
RTE-i
- Create a complete POC for demonstration purposes (Q1/Q2)
- Present a webinar on OpenSTEF (22nd of March, Q1)
Sigholm
- Deploy OpenSTEF on Sigholm cloud environment
- If requirements are met, switch to OpenSTEF as main forecasting tool.
- Demo to Sigholm customers
- Integrate with other Sigholm products.
Shell
- Implementation OpenSTEF-dbc realtime
Planned milestones
Year | Q | Milestone | Company | Kind |
2024 | 1 | Promote OpenSTEF at FOSDEM | Alliander | Outreach |
2024 | 1 | OpenSTEF workshop | Alliander | Outreach |
2024 | 1 | Present webinar on OpenSTEF | RTE-i | Outreach |
2024 | 1/2 | Complete POC for demonstration purposes | RTE-i | New |
2024 | 1/2 | Improve forecasting quality | Alliander | Improvement |
2024 | 2 | Provide benchmark of OpenSTEF on relevant usecase compared to other forecasting providers | New | |
2024 | 2 | Promote OpenSTEF at CIRED (incl. Methodology paper) | Alliander | Outreach |
2024 | 3 | LF energy summit | Outreach |
Previous roadmaps
Input Alliander:
Forecasting topics at Alliander 2022:
Scale up ‘Contingencies’; locations with active capacity management
T-prognoses customers; Including those in our load/generation forecasts
Forecasting load at non-measured secondary substations
Forecasting Reactive power (with few measurements)
Milestones related directly to OpenSTEF: (version 2022-02-21):
Year | Q | Milestone | Kind |
|---|---|---|---|
2022 | 1 | Finish OpenSTEF LFE Intake | Outreach |
2022 | 1 | Remove Openstef-dbc from Openstef | Improvement |
2022 | 2 | Forecasting API - together with SOGNO FastAPI wrapper around OpenSTEF | New |
2022 | 2/3 | Promote OpenSTEF @ LFE
| Outreach |
2022 | 3 | Backtest / Predictability Analyses | New |
2022 | 3 | Ensemble forecasts - Automated optimized combination of independent forecasts / forecasting algorithms | Improvement |
… |
Input RTE:
