Zurich, Switzerland, November 30 2022 -Terra Quantum, one of the leading quantum technology companies, and the global energy company Uniper combine expertise to explore real world use cases using hybrid quantum technologies. Their joint efforts focus on quantum powered applications in the realms of optimization, machine learning and Monte Carlo simulations (a computerized mathematical technique that allows users to quantitatively account for risk in forecasting and decision-making). The projects investigate potential benefits in LNG scheduling and forecasting, optimizing the operational processes of biomass plants through improving predictions of CO2 emissions and peaks. A further use case can enable faster and more accurate risk pricing in Uniper’s trading division.
Quantum technologies have the potential to help us find solutions to some of the world’s most complex problems. Uniper has joined forces with Terra Quantum, a leading full-stack quantum technology company, to explore applying cutting-edge technology to notoriously challenging problems in the energy landscape.
Markus Pflitsch, Founder and CEO of Terra Quantum, says: “The energy industry, like many other industries, has a wide variety of optimization, machine learning and simulation challenges which can be impacted by hybrid quantum computing today. We are delighted to be driving this vital industry forward.”
Use cases for proof of concept
LNG scheduling and forecasting
In this use case, Terra Quantum and Uniper are tackling complex optimization problems that could enable an enhancement in delivery capacity at lower costs. The hybrid quantum approach aims to build on existing approaches to find improved solutions to complex scheduling problems.
CO2 emissions prediction in biomass plants
In this application, a hybrid quantum machine learning (QML) model is being applied to Uniper’s operation platform, which already utilizes Artificial Intelligence to optimize processes within biomass plants. This platform analyzes plant data and sensor measurements to predict emissions and peaks. QML could enhance these predictions which would in turn lead to improved optimization of the biomass plant processes, to ultimately reduce emissions and peaks.
Valuation of options and complex derivates in energy trading
A third use case being considered is in using quantum enhanced Monte Carlo simulations to improve the valuation of options and complex derivatives for Uniper’s trading division. Monte Carlo simulation is one of the key methods used to understand risk and price complex derivative products in financial markets. Quantum simulation techniques have the potential to significantly enhance Monte Carlo simulation methods by enabling speed-ups.
The organizations are working together in these areas with the aim of probing real world use cases with hybrid quantum technologies, not merely academic problems.