At Quantego we are always one step ahead. With QUASAR we have launched the next generation of stochastic optimization software to help energy companies make smarter decisions in the face of uncertainty. QUASAR is the only general-purpose solver for large-scale stochastic optimization and its performance is accredited by science. By uniting a set of unique and cutting-edge features, QUASAR lifts decision-making to the next level and gets you ahead of your competitors.
Learn how energy companies use QUASAR to make smarter decisions in the face of uncertainty.
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, Vienna, 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, Vienna, Austria
No time to develop a custom solution? You don’t have to! With QUASAR apps, we provide graphical user interfaces for applications like stochastic hydropower planning, gas storage valuation, and portfolio management. QUASAR apps are based on thoroughly tested, flexible models, which can be configured to meet user requirements. Let our consultants help you build a custom application from our templates.
Run QUASAR remotely either on premise or hosted by Quantego using our web-based Jupyter notebooks. QUASAR’s Python package seamlessly integrates with popular packages like Numpy, Pandas, and Matplotlib. QUASAR’s Python integration offers you the shortest path from prototype to fully operational production system.
QUASAR's MATLAB interface now offers quantitative analysts the power of stochastic optimization with QUASAR from inside their favorite workbench.
Easily integrate solutions based on QUASAR into enterprise-wide applications. The Java backend offers developers a user-friendly modeling language, flexible interfaces to model customized stochastic processes, as well as full control over the stochastic optimization solver engine.
Optimal gas storage valuation and futures trading under a high-dimensional price process. Optimization Online (2015)
Optimizing trading decisions for hydro storage systems using approximate dual dynamic programming. Operations Research (2013)
Directly deploy from Docker:
Repository with sample files:
Python references for PyQUASAR: quantego.com/docs/pyquasar
Javadocs for the QUASAR Java API:
At Quantego we are always one step ahead. Being a research-driven company, we are not only up-to-date with the latest trends in applied math, operations research, and machine learning. Our researchers themselves are renowned scientists in these fields, committed to invent the next generation of decision-making technology. They repeatedly publish their breakthroughs in top-notch peer-reviewed scientific journals. We at Quantego are working aggressively to transform these breakthroughs into professional products and services that help our clients to stay ahead.