ORGANIZED BY

JUNE 20TH

2019

French industrial quantum use cases

Stéphane TANGUYCIO & CTO

EDF Labs, France

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Oser le futur et innover au présent

Quantum computing @ EDF Labs

Stéphane Tanguy

EDF Labs CIO & CTO

STRATEGICPRIORITIES4in line with the EDF Group's CAP 2030 project

MAJOR DISRUPTIVE FORCES3

ELECTRIC Transition

CLIMATE Change

DIGITAL & SOCIAL Transition

EDF LABS IN BRIEF

Generation (Nuclear, Renewable, Hydraulic,

Thermal, Environment)

Network / Smarties (smart-grids, smart-cities)

Energy Management

COMPUTING ALL OVER THE GRID !! PHYSICAL SIMULATION AND DATA ANALYSIS

Nuclear : a particular domain

• TOP 100 HPC machines - 700 Million CPU hours per year

• Unique simulation code portfolio covering major domains of

Physics

• >500 Engineers/year either developing code or delivering HPC

based studies

• Total of 120 PHD students

Computing assets & resources to deliver

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MAIN USE CASES FOR QUANTUM COMPUTING @ EDF

MATERIAL AGEING

MODELLING

SAFETY PROBABILISTIC

STUDY

Modelling ageing phenomena's with quantum

physic laws

Stake : foresee material ageing patterns to

gain operational margin.

Contribute to regulatory studies for ASN IRSN

Decision support tool for real time risk analysis

Recalculate risk based on operation current

state and maintenance operation

Avoid roll back in case uninttended events

COMBINATORIAL

OPTIMIZATION FOR ENERGY

MANAGEMENT

Smart charging : optimizing VEs charging for

the grid operator/charging operator/user

Decentralized energy systems, exploiting

large data volume

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EDF APPROACH TO QUANTUM COMPUTING

3. Experimenting & feed back loop

QAOA on ATOS QLM, Pasqal (Quantum annealing start up)

1. Exploring

What does it mean for EDF ?

Where to start ?

Main uses cases ?

Our quantum journey

PHDs(LORIA, LIPN..)

H2020 Pasquans

Project

2. Building our eco system

Academics,Industrial & Quantum

machine providers

Teratec, CIGREF

..

Courtesy of Institut d’Optique

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QUANTUM ALGORITHM FOR OPTIMAL BATTERY OPERATION

Every battery model has a

capacity, a power range and

a lifetime (charge cycles).

When a battery is used,

either to deliver capacity or

frequency response, it ages.

Before investing, the financial

scenarios are investigated

using forecasted prices.

To integrate higher volume of renewables, EDF plans to install large

batteries on national scale power grids. But optimising the

investment and the life time operation of these storage systems is a

problem whose complexity exceeds the capabilities of classical

computing.

This ‘hands-on’ experiment is

being developed in the EDF

Energy R&D UK Centre.

Formulation in a Knapsack

problem (NP complex)

Adaptation of a recent

quantum algorithm (QAOA)

Implementation on Quantum

Simulator

.

.

.

Scope of work

| 8Calcul quantique | 03/2018

#1

FORMULATION

An in-depth review of

Quantum Approximate

Optimization Algorithm.

Working with business

experts to reformulate the

problem in a standard

form: Knapsack.

#2

DEVELOPMENT

A new formulation of

QAOA for Knapsack on

Universal Quantum Gates.

A novel quantum circuit

architecture and

subroutines.

#3

IMPLEMENTATION

AN implementation into the

IBM QisKit package.

Experiments with a

simulator and evaluation of

behaviour and sensitivity.

QUANTUM ALGORITHM FOR OPTIMAL BATTERY OPERATION (2)

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CONCLUSION

▪ Agnostic position in relation to Qubit technology

▪ We are focused on ramping up our R&D capability to

develop/use quantum algorithms

▪ We won’t go alone .. Leveraging multiple partnerships

in particular the rich quantum ecosystem of Plateau de

Saclay

▪ We welcome initiatives to boost academic training &

research capabilities and develop cross domain labs

▪ Realist but positive about the future of quantum

computing.. Beware of overhyping !!

▪ Opportunity for Europe to regain some of it’s digital

sovereignty