Datamanagement is one thing, but data analysis is a science on its own. Our team of quants help energy companies and large scale users deduce essential insights from their energy data to improve their forecasts and decrease their imbalance costs.
Energy knowledge beats model complexity
While the technical performance of your data management software and the logic in your data management processes should be in order – crucial conditions for correct analysis – it is the energy intelligence that adds quality to quantitative analysis.
Our knowledge of the energy market and its business processes allows us to organize data such that great results can be achieved through simple regression models. The low computational effort required for these models makes them particularly suited for fast-paced processes like intraday trading.
From quant art to business process
We recognize that even the most accurate models are of little value when they cannot be successfully automated. Energy21 combines quantitative skills with vast experience in automating processes.
We use our EBASE data management software to schedule runs of our own regression models, or of models from external tools such as Matlab and R. This way the most recent data is always available for business decisions.
Half-day quant sessions: live energy data deduction
We organize quant sessions in which our team gets to work with your data and deducts valuable insights when it comes to:
Demand, (Renewable) Supply and Price Forecasting
Big data analytics (PowerBI, visualization, machine learning)
Energy companies or industrial and commercial energy users benefit from working together with our quants during the sessions. Also, we deliver a report summarizing the results of the analysis plus recommendations to implement improvements in business processes. Together, this helps improving forecasts and decrease imbalance costs.
For more information, contact Alex Trijselaar (Head of Quants) via +31 6 3167 3035 or email@example.com
Comments are closed.