Optimization for
Energy Storage & Trading

The world's fastest and most scalable multistage stochastic programming solver.

QUASAR® Solver

Software for storage optimization and energy trading built on QUASAR®

QUASAR® Cloud

Trusted by key players in the energy industry

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Make optimal decisions
under uncertainty

Until now, optimization under uncertainty meant sacrificing detail. Not anymore. QUASAR® easily solves stochastic programming problems with hundreds of stages, thousands of decisions variables, and millions of random outcomes.

QUASAR® empowers our clients to model decision problems and any risk factors involved as they are – and solve them at an unprecedented speed.

Success Story

Stochastic Hydropower Asset Optimization

Austria’s largest electricity company, Verbund, leverages QUASAR® to simultaneously plan their vast network of hydropower plants - in hourly time resolution over multiple years.

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Success Story

Stochastic Optimization of Energy Procurement

Extensive backtests based on several years of historical data of EEX and TTF futures indicate a substantial monetary value of using QUASAR® to model forward buying decisions for a large industrial company.

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Success Story
trading

Stochastic Portfolio Optimization

Power traders can use QUASAR® to calculate an optimal hedge plan that accounts for weekly, monthly, quarterly, and yearly futures contracts as well as the market impact of trading them.

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How can I use QUASAR®?

Whether you are an analyst, data scientist, or operations research engineer: use QUASAR® to build your own models or select a model from our repository. Then deploy everything as stand-alone web applications via QUASAR® Cloud.

What our clients say

BASF trades excess power supply on energy markets at different production sites across Europe. QUASAR/hegde provides our buyers with daily hedging targets and an outlook on the right mix between futures, forward products, and spot.
Dr. Ferdinand Kiermeier
Advanced Analytics in Global Procurement at BASF SE, Germany
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.
Dr. Andreas Eichhorn
Portfolio Management at VERBUND Trading, Austria
The business environment of energy utilities and energy traders is changing constantly, which makes dealing with uncertainty a daily challenge. To cope with this change, flexible and user-friendly tools are required. QUASAR’s Jupyter integration combines productivity, flexibility, and usability in one tool, which makes it a pleasure to prototype and analyze models for everyday’s work tasks.
Dr. Elke Moser
Research and Analysis at Energieallianz, Austria

Quantego Blog

RECENTLY POSTED
QUASAR Examples
QUASAR Jupyter

QUASAR: Stochastic Programming in Scala

The QUASAR optimization software finally makes stochastic programming available for a wider audience. Check out the example in this post to see for yourself, just how easy it is. In a previous post, we have used our Python interface. In this example, we call our Java API from Scala.

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