AI Solutions
for Energy & Utilities

AI, quantum techniques and other Big Compute^TM are primed to unlock new chemical discoveries and efficiencies in energy production, accelerating our transition to a sustainable future. According to McKinsey, quantum technology could unlock $100-300B in added value by 2035 for the chemicals sector alone.

Featured Use Case

Optimizing the Placement of Renewable Energy Sources with Generative AI

Challenge

Approach

Renewable energy sources, especially wind and solar energy, rely heavily on environmental conditions to function effectively. For example, if the sky is too cloudy or if the wind isn’t strong enough, solar panels and wind turbines won’t produce electricity. Energy planners need to strike a balance between installing energy sources in areas with high energy generation potential and close proximity to energy storage facilities and existing energy grids, while also minimizing the impact on the environment and local communities — a complex optimization problem.

Use Cases

Applications for Energy and Utilities

Chemistry and Materials

Energy Production

Energy Distribution and Consumption

Chemistry and Materials

Energy Production

Energy Distribution and Consumption

Key Challenges

Inability to simulate large molecules on classical computers
Minimizing waste and downtime in chemical manufacturing
Developing materials that enable more efficient energy production

Zapata Solutions

Chemical and Materials Simulation

Deploy quantum chemical simulations to discover new alloys, catalysts, carbon capture solvents, battery materials, solar cell materials and other industrial chemicals.

Chemical Process Flow Optimization

Optimize the manufacturing process for chemicals and materials using Generator-Enhanced Optimization (GEO).

Nuclear Reaction Simulation

Design more efficient nuclear reactors by leveraging quantum computers to more accurately simulate nuclear reactions.

Key Challenges

Reducing downtime for wind turbines and solar panels
Minimizing operational costs
Maximizing production rates for oil and gas wells

Zapata Solutions

Energy Production Site Optimization

Optimize the location of solar panels, wind turbines, mines and other energy production sites to maximize output and minimize costs using GEO.

Well Drilling Optimization

Optimize oil and gas well drilling routes to maximize production rates while minimizing costs using quantum or quantum-inspired techniques.

Fluid Flow Simulation

Apply quantum-accelerated stochastic simulations of Reynolds-Averaged Navier-Stokes (RANS) systems to more accurately model fluid flow dynamics.

Key Challenges

Timing infrastructure maintenance
Maintaining reliable and resilient power supply
Reducing emissions
Minimizing distribution costs
High computational power needs

Zapata Solutions

Pipeline Predictive Maintenance

Leverage quantum-enhanced machine learning to predict the optimal times to service pipelines and other energy infrastructure.

Distribution and Delivery Optimization

Apply quantum and quantum-inspired techniques to optimize delivery routes and pipeline network layouts to reduce fuel costs, carbon emissions, and delivery times.

Grid Optimization

Optimize the design of energy grids to maximize reliability, resilience and efficiency while minimizing costs using GEO.

Battery Usage Optimization

Optimize the scheduling of high-power computing tasks to mitigate battery exhaustion using quantum or quantum-inspired techniques, for example on edge electronics.

Use Case Timeline (est.)

Featured Case Study

bp

The variational quantum eigensolver (VQE) is a key algorithm for molecular simulation invented by Zapata founders. Over the last few years, we’ve worked with bp to explore how soon VQE can make an impact for quantum chemistry use cases, running tens of thousands of hours of computing on our software platform, Orquestra®.

Using Orquestra, we benchmarked VQE on various quantum hardware backends, and advanced proprietary techniques to make VQE more viable in the near-term. While a working enterprise-scale VQE solution is likely still years away, we discovered other use cases that could go into production much sooner. We have expanded beyond chemistry to include use cases in finance, cybersecurity, and logistics, and are accelerating BP’s Quantum Center of Expertise team using Orquestra.

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Orquestra^® Benefits for Energy and Utilities

Orchestration Across Environments

Leverage the heterogenous compute resources best suited for your tasks, without getting locked into any one hardware platform. Deploy across hybrid backends at enterprise scale.

Data Management & Velocity

Store, retrieve, and analyze large datasets. Streamline data management from ingestion to export to accelerate data velocity.

Open Framework

Keep what works now. Integrate existing and future solutions with a framework optimized for extensibility, interoperability, and innovation.

Workflow Development and Deployment

One unified platform to go from research to development to deployment with extensible, scalable, modular workflows.

AI Solutionsfor Energy & Utilities

Optimizing the Placement of Renewable Energy Sources with Generative AI

Challenge

Approach

Applications for Energy and Utilities

Use Case Timeline (est.)

bp

Orquestra® Benefits for Energy and Utilities

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AI Solutions
for Energy & Utilities

Orquestra^® Benefits for Energy and Utilities