
Interactive Example Notebook in Google Colab: Reservoir Management
Check out our interactive example notebooks in Google Colab to find out just how simple it is to solve multistage stochastic programming problems with QUASAR®!
Next Generation Stochastic Hydropower Optimization
Hydropower planning today not only faces uncertainty about natural inflows but also uncertainty about the evolution of electricity prices. Longer dry seasons, trading across multiple power markets, participation in the balancing markets and increasing complexity of contracts used for hedging production, of this turns hydropower operation into an increasingly challenging task.
Taking full advantage of QUASAR®’s advanced solver technology, Quantego has developed the most flexible and detailed stochastic optimization model for hydropower planning available today.
Quantego’s hydropower planning model consists of an integrated price and inflow model and a decision model.
The model is available as ready-to-use yet highly customizable software solution deployed through QUASAR® Cloud.
Users can import and manage input data, execute optimization runs, calculate water values and delta positions, create interactive charts and reports, as well as export result data and easily share it across the organization. QUASAR® Cloud can be obtained as subscription service or set up on-premise via AWS VPC.
The model is driven by the powerful QUASAR® stochastic programming solver that combines the latest advancements in machine learning and mathematical optimization. QUASAR®’s highly efficient algorithms can solve the most complex stochastic-dynamic programming problems with hundreds of time stages, thousands of variables and millions of possible outcomes at an unprecedented speed.
Austria’s largest power company, VERBUND, uses QUASAR® for medium-term planning of several interconnected reservoirs, hydropower stations, and run-of-the-river plants, in hourly time resolution. The model considers uncertainty of hourly spot prices as well as natural inflows over a 3-year planning horizon, which has been impossible with existing planning tools before.
The sheer size of our reservoir makes it necessary that our hydropower storage assets must be managed over the medium term, when there is still significant uncertainty about future hydrologic inflows and power prices. Our asset management therefore clearly benefits from stochastic modeling, but only with QUASAR, we are able to solve the stochastic optimization problem in hourly time steps over a three-year planning horizon.
Check out our blog with more resources, such as white papers, customer success stories and academic publications.
Check out our interactive example notebooks in Google Colab to find out just how simple it is to solve multistage stochastic programming problems with QUASAR®!
Learn how to optimize a hydropower planning in hourly time granularity under uncertainty about day-ahead electricity prices and natural inflows.
In this presentation, Dr. Elke Moser explains how Energieallianz (formerly e&t), an energy trading house in Vienna (Austria), used QUASAR to develop a custom-made solution for optimizing bids for the German-Austrian auction for balancing reserves.