Bernard DrÃ©villon
prÃ©sentation
Bernard DrÃ©villon commence sa carriÃ¨re de recherche en Physique des Hautes Energies Ã lâ€™Ecole polytechnique en 1969. Il soutient sa thÃ¨se soutenue en 1973. Puis il se tourne vers la synthÃ¨se de couches minces de silicium pour applications photovoltaÃ¯ques et participe Ã la crÃ©ation du Laboratoire de Physique des Interfaces et des Couches Minces (LPICM) Ã lâ€™Ecole polytechnique en 1986. Il se spÃ©cialise dans une technique de caractÃ©risation optique originale (ellipsomÃ©trie spectroscopique) qui permet le suivi en temps rÃ©el de la croissance des couches. Lâ€™instrument sera ensuite exploitÃ©e commercialement par JobinYvon (devenue Horiba) Ã partir des annÃ©es 90. Plusieurs centaines dâ€™ellipsomÃ¨tres ont Ã©tÃ© vendus depuis dans le monde entier.
B. DrÃ©villon a dirigÃ© le LPICM de 1999 Ã 2012 et participÃ© activement Ã la crÃ©ation de lâ€™Institut PhotovoltaÃ¯que dâ€™Ile de France (IPVF, opÃ©rationnel en 2016), en collaboration avec EDF et TOTAL. B. DrÃ©villon est lâ€™auteur de plus de 250 publications dans des revues Ã comitÃ© de lecture (facteur H : 41) et dâ€™une trentaine de brevets dâ€™invention. Il a dirigÃ© plus de vingt thÃ¨ses. Il est Professeur Ã lâ€™Ã‰cole polytechnique depuis 2001, il dirige le Master Renewable Energy Science and Technology (REST) depuis 2011. Â Â
CA/DER/DEP/PHYS
PHY598  Internship for Energy Environment (STEEM) (20172018)
4 to 6month Research or industrial internship for STEEM students.
The internship can be done in a lab, a company or a startup, numerous possibilities in Paris area or elsewhere in France or abroad (contact program directors). The internship starts in March and end with a report and an oralÂ defense.
PHY652A  Physics of Solar Cell Devices (Intro to PV) (20172018)
PHY652B  Polymers for Photovoltaics (Org PV) (20172018)
Eligibility/Pre requisites
A basic knowledge in quantum mechanics is preferable, but not absolutely required.
Learning outcomes
This course will provide a comprehensive overview of the research and technology used to design polymerbased organic solar cells.
After taking this course, the student should be able to demonstrate theoretical knowledge on the following subjects:

Concept of organic semiconductors,

Exciton and charge carrier transport in polymeric and organic semiconductors,

Synthesis and application of polymers in organic photovoltaic technology,

Organic photovoltaic cell design.
Course main content
The costeffective development of flexible solar cells is one of the challenges of tomorrowâ€™s onboard photovoltaic systems. As demonstrated by the 10.7 % efficiency achieved in April 2012 by Heliatek GmbH, polymer solar cells, and organic photovoltaic technology at large, seem to offer the most promising avenue for achieving this. The role of organic materials is not limited to semiconductortype active media, so we will also discuss their use in dye sensitized solar cells and perovskitebased hybrid cells, which have shown promise for even higher power conversion efficiency during the recent years.
Organic semiconductors (16 hours)
 The carbon atom
o Frontier orbitals (HOMO and LUMO)
o Band width
o Density of states (DOS)
 Charge transport
o Bandlike transport
o Concept of polaron; Marcus model
o Multiple and trapping release model
o Hopping models
 Optical properties
o Concept of exciton
o Singlet and triplet
o Energy transfer (Dexter, FÃ¶rster)
 Metalsemiconductor interface
o Energy levels in metals and organic semiconductors
o Charge injection and extraction in organic semiconductors
o Metal semiconductor diodes
Organic photovoltaic cells (4 hours)

Principle of organic photovoltaics

Device structures; concept of Bulk Heterojunction

Role of morphology

Tandem Cells
Chemistry of polymer semiconductors (8 hours)

Conjugated polymer synthesis
o History of metal catalyzed coupling reaction
o Mechanism of the metal catalyzed Coupling Reaction
o Mechanism of the Stille coupling reaction
o Mechanism of the Suzuki coupling reaction
o GRIM polymerization, living polymerization
o Catalytic Systems, Ligand Effect, Solvent effect
o Type of monomers
o Example of Functional conjugated polymers

Materials for OPV
o Materials developmento Hole transporting materials
o Electron transporting materials, polymer and fullerene
Dyesensitized and perovskitebased cells (4 hours)

Working principle

Material design
Economic aspects of organic photovoltaics (4 hours)
 Review of the industrial groups involved
 Analysis of the industrial profitability
Examination and requirements for final grade
The evaluation of the students will consist of a final written exam.
Coordinator Instructors
Gilles HOROWITZ, Ecole polytechnique
GaÃ«l ZUCCHI
Langue du cours : Anglais
Credits ECTS : 4
PHY652C  Batteries and Energy Storage (Batt) (20172018)
PHY652D  Renewable Generation of Electricity Using the Thermal Cycle (Therm) (20172018)
PHY652E  Introduction to Power Systems (Intro to PS) (20172018)
PHY652F  Wind Power (Wind) (20172018)
Lecturer: Fawad Massouh
Eligibility/Pre requisites
Due to use of experimental facilities, the number of students is limited to 24
This course needs basic knowledge in fluid mechanics and in electricityÂ
Learning outcomesÂ

Global vision of wind power and the evolution of wind turbines

Ability to analyze wind data on a site and calculate the potential of wind energy

Understanding the operation and control of the chain of energy transfer formed by theÂ wind turbine.

Understanding the technical problems related to the connection of wind turbines toÂ power grids

Understanding of basic aerodynamic models for the rotor of wind turbines

Experience in numerical simulation of flow around wind turbines

Experience in wind tunnel experimentation undertaken to obtain wind turbineÂ performances

Experience in writing a scientific paper and its oral public presentationÂ
Course main contentÂ

General presentation of wind energy and wind turbines
Evolution and classification of wind turbines, Wind turbine components. Overview of the wind power industry in European Union and worldwide. Considerations in wind farm siting and operation

Wind characteristics and wind energy potential
Characteristics of wind. Meteorological aspects. Weibull distribution. Calculation of theoretical wind energy potential. Calculation of produced energy by a given wind turbine. General presentation of atmospheric boundary layer. Wind velocity measurements.

Aerodynamics of wind turbines
Aerodynamics of an airfoil, forces and coefficients. Operation in normal and stall mode. Rotor aerodynamics. Momentum theory, Betzâ€™ law, Blade element momentum theory, vortex theories.

Mechanical Design
Normal and extreme loads as defined by the standards, Blade design, presentation of employed materials. Mechanical behavior and test. Aeroelasticity of blades. Rotor in operation.

Electrical Power conversion in wind turbines
Fixed speed wind turbine. Variable speed wind turbine. Full power electronic converter. Double feed induction machine. Integration of wind turbines in electrical networks of transport and of distribution.

Control and Regulation of wind turbines
Power electronic converter control
Wind turbine control strategy: stall, pitch control.

Introduction to CFD and simulations of flow and wake of a wind turbine. Practice
of CAO and preparation of the numerical model. Analysis and synthesis of results.
Submission of a report.

Experimental investigation in ENSAM wind tunnel.
Tests of a wind turbine and determination of its characteristic curves: thrust, torque
and power. Analysis of results and submission of a testing report.

Initiation to scientific communication.
The student is asked to do a personal work within a small group about a researchÂ subject in the field of wind enegy. A specific bibliographic revue must be prepared. This work must be finalized as a written paper respecting a given template and also as an oral presentation.Â
Examination and requirements for final gradeÂ
Students are graded through :
 Written final exam (open book) 60%
 Numerical simulation session and report 10%
 Wind tunnel experiments and report 10%
 Written bibliographic revue and oral presentation 20%Â
Coordinator InstructorsÂ
Fawaz MASSOUH, ENSAM ParisTech
Marc RAPIN, Xavier GUILLAUD, Ivan DOBREV, Sofiane KHELLADIÂ
Langue du cours :Â Anglais
Credits ECTS :Â 4
PHY652G  Nature based solutions to substitute fossile ressources (20172018)
Naturebased solutions to substitute fossile resources and address global change
Lecturer: BenoÃ®t Gabrielle  AgroParisTech
Natural ecosystems and the services they provide are a key to address current environmental challenges, such as climate change, the preservation of air and water quality, and the transition toward a lowcarbon economy. Engineering these services via the management of ecosystems, landuse planning or the integration of plants in urban environments can Â«Â pave the way towards a more resource efficient, competitive and greener economyÂ Â» (EU Research Agenda, 2015). Naturebased solutions include for example the production of biobased alternatives to fossilebased products, the mitigation of heat waves in cities via the presence of vegetation, the enhacement of carbon storage in ecosystems or the management of watersheds to reduce flood risks.
The aim of the course is to raise the awareness of these solutions, with a particular focus on biomass production and transformation into fuels, materials and chemicals to substitute fossile resources, and to equip them with key concepts and knowhows on the design and assessment of such solutions. The course will provide students with a detailed understanding of the issues associated with the development of naturebased solutions to meet our needs for food and energy, mitigate climate change or air pollution, and methods to their sustainability along the environmental and economic dimensions.
Langue du cours :Â Anglais
Credits ECTS :Â 4
PHY652H  Project Management, Innovation and Entrepreneurship (Proj) (20172018)
PHY652I  Topical seminars (20172018)
PHY652J  Solar Resource Seminar (20172018)
PHY652K  Lecture (20172018)
PHY661E  Fluvial and Maritime Resources for Renewable Energy (Fluv) (20172018)
PHY661F  Specialization Course in Biomass and Bioenergy (Bio II) (20172018)
PHY698  Internship for Energy Environment II (STEEM2) (20172018)
MEC665  Sea State, coastal waves and morphodynamics (20172018)
Lecturers: Michel Benoit
This course is shared with ENSTA ParisTech engineerâ€™s program
The first part of this course is devoted to ocean waves theory, their linear and nonlinear dynamics, their spectral representation and their stochastic properties.
Â Â Â The second part focus on the coastal and near shore environment, where high quantities of noncohesive sediments (sands) are transported under the combined action of waves and currents. This sediment transport is crucial to both the understanding of how the morphology of the sandy coasts evolves and the accurate designing of coastal protection methods (e.g., hard structures, sand nourishments). The course presents the basic hydrodynamical processes driving the coastal and near shore sand transport and the underlying physical mechanisms controlling the evolution of sandy bodies.
1. Introduction on surface waves
Monochromatic surface waves, linear swell, wave energy and power.
2. Sea state and random waves
Deep sea random waves observation, shortterm statistics, spectral analysis: frequency and direction. Wind generation, nonlinear evolution, dispersion and dissipation.
3. Linear shallowwater waves
Shoaling, shallowwater transformation, wave breaking dissipation, wave induced currents, coastal and beach currents.
4. Nonlinear shallowwater waves
Nonlinear models of shallowwater waves, GreenNagdi equations, surf and swash zones.
5. Offshore to coastal waves
Wave current interactions, wave evolution in finite depth. Numerical models of GLM2RANS.
6. Introduction on nearshore morphodynamics
Wavedriven currents in the nearshore; geomorphology; patterns in the sand; sediment transport under breaking waves; sandy beachÂ morphodynamics on timescales: days to years.
7. Modelling of nearshore morphodynamics
Forcing template and selforganization theories; linear and nonlinear stability analysis; shoreline instabilities, 3D surf zone sandbars dynamics.
8. Practical session: Development of a simple shoreline evolution modelÂ
Oneline shoreline modelling; development and basic underlying assumptions; analytical solutions; numerical scheme; practical applications with nourishments and coastal structures.
9. Noncohesive sediment transport and observation technics
Introduction to mophodynamics, sediment property and characterization, sediment transport, overview of observation technics, multibeam echosounder, current meters.
10. Dynamics of marine sandbanks and sand dunes of the continental shelfÂ
Characteristics of banks, dunes, megaripples; modelling and time scales, sandbanks modelling linear stability analysis, dunes and megaripples modelling.Â
M. BenoitÂ (IRPHE & Ecole Centrale Marseille), B. Castelle (EPOC),Â M. YatesMichelin (SaintVenant)
Langue du cours :Â Anglais
Credits ECTS :Â 4
PHY661D  Stochastic & dynamic optimization: adaptive storage & delivery of RE (20172018)
Stochastic and dynamic optimization: adaptive storage and delivery of renewable energies
Lecturer:Â Â Â Â Michel De Lara (CermicsÃ‰cole des Ponts ParisTech) Â Â Â Â Â professional webpage
Eligibility/Prerequisites.
 Mathematical skills. Computer skills.Â
 Continuous optimization: linear programming, convexity, duality, firstorder optimality conditions. [Ber96]
 Probability calculus: probability space, probability, random variables, independence, law of large numbers. [Fel68,Bre93,Pit93]
 Software Scicoslab to be installedÂ ScicoslabÂ (else, install software Scilab)
Â Learning outcomes.Â After the course the student should be able to
 design mathematical models for energy storage and delivery of renewable energies, especially in microgrids, and formulate costminimization problems,
 use the scientific software Scicoslab and numerically solve small scale problems.
Course main content.Â The course mixes theoretical sessions, modeling exercises and computer sessions.
In introduction, we present examples of microgrid and virtual power plant management  where the question of electrical storage is put, due to the need to answer a varying demand and to incorporate intermittent and highly variable renewable energies. During the course, we will present concepts and tools to formulate such problems as stochastic dynamic optimization problems. For this purpose, the first sessions are dedicated to mathematical recalls in probability and optimization, followed by an introduction to the scientific software Scicoslab.
Then, we turn to stochastic optimization. In a deterministic optimization problem, the values of all parameters are supposed known. What happens when this is no longer the case? And when some values are revealed during the stages of decision? We present stochastic optimization, at the same time as a frame to formulate problems under uncertainty, and as methods to solve them according to the formulation. More precisely, we presentÂ twostage stochastic programmingÂ (and the resolution on scenario tree or by scenarios) andÂ multistage stochastic controlÂ (and the resolution byÂ stochastic dynamic programming). We finish with theÂ Stochastic Dual Dynamic Programming (SDDP)Â algorithm (used in commercial software in the world of the energy), which mixes dynamic programming and cutting plane algorithm. Depending on time availability, we will try to shed light on decomposition methods that lead to decentralized optimization (especially adapted to microgrid management).Â
Modeling exercises and computer sessions tackle issues like optimal economic dispatch of energy production units, storage/delivery optimization problem to buffer an intermittent and variable source of energy, dam optimal management with stochastic water inflows, battery optimal management with renewable energy inputs.
Examination and requirements for final grade.Â At the end of each computer session, the student produces a report, which receives a mark after evaluation. Miniexams, presence and participation also contribute to the final grade.
Link course.Â Â Â Â Â http://cermics.enpc.fr/~delara/TEACHING/Graduate_Degree_STEEM/
Â Â Â Â Â Â course webpage
Link Graduate Degree STEEM.Â Â Â Â Â https://portail.polytechnique.edu/graduatedegree/steem/Â
Â Â Â Â Â Graduate Degree STEEMÂ Â Â Â Â Â Â Â Â Â Â Â Â Â map of the courses rooms
Langue du cours :Â Anglais
Credits ECTS :Â 4
Program
1Â / Â Â Â Â
Introductory talks (14h0015h00)
To introduce the course, we present examples of microgrid and virtual power plant management (that can be solved using stochastic dynamic optimization):
 Work done by Francis Sourd and Ariel Waserhole (Sun'R)Â
``Renewable Energy Aggregator: How to Handle Market Risk''Â Â Â Â Â slides  Work done by FranÃ§ois Pacaud (Efficacity and CermicsÃ‰cole des Ponts ParisTech)Â
``Optimal Control of a Domestic Microgrid with Combined Heat and Power Generator''Â Â Â Â Â slides  Work done by Tristan Rigaut (Efficacity and CermicsÃ‰cole des Ponts ParisTech)Â
``Optimization for Energy Efficiency and Climate Control of a Subway Station Microgrid''Â Â Â Â Â slides
Lecture (15h0016h00)
Recalls on probability calculus: probability space, probability, random variables, law of a random variable, mathematical expectation, indicator function, independence of random variables, almostsure convergence and law of large numbers. [Fel68,Bre93,Pit93]
Exercises (16h3018h00)
Exercises on probability calculus.
2Â / Â Â Â
Lecture and exercises (14h0016h30)
Recalls and exercises on continuous optimization [Ber96]. Â Â Â Â slides
 Recalls on convexity: convex sets, convex functions, strict and strong convexity (characterization by the Hessian in the smooth case), operations preserving convexity.
 Abstract formulation of a minimization problem: criterion, constraints. Sufficient conditions for the existence of a minimum (continuity and compacity/coercivity).Â
Sufficient condition for the uniqueness of a minimum (strict convexity). Exercises with a quadratic objective function on an interval.Â  Definition of a local minimizer; necessary condition in the differentiable case. Formulation of a minimization problem under explicit equality constraints.Â
Necessary firstorder optimality conditions in the regular/affine equality constraints case; Lagrangian, duality, multipliers.Â
Sufficient firstorder optimality conditions in the convexaffine case. Exercises.Â
Exercises (17h0018h00)
We present, under the form of an exercise, an example of optimization problem under uncertainty: ``the newsvendor problem''. Â Â Â Â Â slides
3Â / Â Â Â Â
Computer session
Introduction to the scientific software Scicoslab. [CCN10] Â Â Â Â Â computer session
Computer session
4Â / Â Â Â Â
Modeling session
``Day Ahead Energy Markets''Â Â Â Â Â slides
Computer session
The newsvendor problemÂ
You will send the results of the computer projectÂ The newsvendor problemÂ
under the form of a pdf fileÂ TP1_STEEM_2017_MYNAME.pdf
Â toÂ delara@cermics.enpc.frÂ before .
 You can choose any software for the computation (but Scicoslab is recommended).
 You can choose any text editor for the report.
 You can insert computer code, but in limited amount.
 The report will display on the first page: title, given name followed by family name, date, mention ofÂ STEEM 20172018.
5Â / Â Â Â Â
Lecture
Twostage stochastic programming on a scenario tree.
Nonanticipativity constraint along scenarios: tree representation.
Computer session
Â Â Â Sizing of reserves for the balancing on an electric marketÂ
(linear and quadratic optimization on a tree)
6Â / Â Â Â Â
Lecture
Twostage stochastic programming on a comb.Â
Nonanticipativity constraint along scenarios.Â
Scenario decomposition by Lagrangian relaxation. Progressive Hedging [RW91].Â
Computer session
Â Â Â Sizing of reserves for the balancing on an electric marketÂ
(linear and quadratic optimization on a comb) You will send the results of theÂ Sizing of reserves for the balancing on an electric marketÂ computer project under the form of a pdf fileÂ TP2_STEEM_2017_MYNAME.pdf
Â toÂ delara@cermics.enpc.frÂ before .
7Â / Â Â Â Â
Exercises (14h0016h00)
Exercises on twostage stochastic programming.
Exam (16h3018h00)
Exam on twostage stochastic programming.
8Â / Â Â Â Â
Lecture and exercises
Dynamical models of storage (battery models, dam models). Dynamical sequential systems with control. Optimal control of dynamical sequential systems. Dynamic programming. Curse of dimensionality. Exercises on dynamic programming. Â Â Â Â Â slides
Dynamical sequential systems with control and noise. Optimal control of stochastic dynamical sequential systems. Stochastic dynamic programming. Curse of dimensionality. Exercises on stochastic dynamic programming. Â Â Â Â Â slides
[Bel57,Put94,Ber00,Whi82,CCCD15]
9Â / Â Â Â Â
Computer session
Code the dynamic programming algorithm.
Computer session
Â Â Â Â Dam optimal management under uncertaintyÂ You will send the results of theÂ Dam optimal management under uncertaintyÂ computer project under the form of a pdf fileÂ TP3_STEEM_2017_MYNAME.pdf
Â toÂ delara@cermics.enpc.frÂ before .
10Â / Â Â Â
Lecture (14h0016h00)
Inventory problems. Optimal storage management in the hazarddecision framework, with linear costs.Â
Stochastic optimal control with convex costs and linear dynamics.
Presentation of theÂ Stochastic Dual Dynamic Programming (SDDP)Â algorithm. Â Â Â Â Â slides
Exam (16h3018h00)
Exam on stochastic dynamic programming.
Bibliography

Bel57
 R.Â E. Bellman.Â
Dynamic Programming.Â
Princeton University Press, Princeton, N.J., 1957.  Ber96
 D.Â P. Bertsekas.Â
Constrained Optimization and Lagrange Multiplier Methods.Â
Athena Scientific, Belmont, Massachusets, 1996.  Ber00
 D.Â P. Bertsekas.Â
Dynamic Programming and Optimal Control.Â
Athena Scientific, Belmont, Massachusets, second edition, 2000.Â
Volumes 1 and 2.  Bre93
 L.Â Breiman.Â
Probability.Â
Classics in applied mathematics.Â SIAM, Philadelphia, second edition, 1993.  CCCD15
 P.Â Carpentier, J.P. Chancelier, G.Â Cohen, and M.Â De Lara.Â
Stochastic MultiStage Optimization. At the Crossroads between Discrete Time Stochastic Control and Stochastic Programming.Â
SpringerVerlag, Berlin, 2015.  CCN10
 Stephen Campbell, JeanPhilippe Chancelier, and Ramine Nikoukhah.Â
Modeling and Simulation in Scilab/Scicos with ScicosLab 4.4.Â
SpringerVerlag, New York, 2 edition, 2010.  Fel68
 W.Â Feller.Â
An Introduction to Probability Theory and its Applications, volumeÂ 1.Â
Wiley, New York, third edition, 1968.  KW12
 AlanÂ J. King and SteinÂ W. Wallace.Â
Modeling with Stochastic Programming.Â
Springer Series in Operations Research and Financial Engineering. Springer New York, 2012.  Pit93
 J.Â Pitman.Â
Probability.Â
SpringerVerlag, NewYork, 1993.  Put94
 M.Â L. Puterman.Â
Markov Decision Processes.Â
Wiley, New York, 1994.  RW91
 R.T. Rockafellar and R.Â JB. Wets.Â
Scenarios and policy aggregation in optimization under uncertainty.Â
Mathematics of operations research, 16(1):119147, 1991.  SDR09
 A.Â Shapiro, D.Â Dentcheva, and A.Â Ruszczynski.Â
Lectures on stochastic programming: modeling and theory.Â
The society for industrial and applied mathematics and the mathematical programming society, Philadelphia, USA, 2009.  Whi82
 P.Â Whittle.Â
Optimization over Time: Dynamic Programming and Stochastic Control, volume 1 and 2.Â
Langue du cours :Â Anglais
Credits ECTS :Â 4
PHY558B  PhotovoltaÃ¯cs Solar Energy (20172018)
Course outline :
 General introduction : Photovoltaic energy (PV) in the worldwide energetic context. Evolution of the PV market.
 Introduction to the physics of crystalline semiconductors : band structure, optical absorption, recombination, intrinsic and extrinsic semiconductors.
 Transport phenomena in semiconductors. The pn junction. Photovoltaic effect.
 Asymetrical devices. Metal/semiconductor contacts. Heterojunctions
 Solar cell operation. Solar cells and modules.
 Crystalline silicon (cSi) solar cells and IIIV compounds
 Amorphous and nanocrystalline semiconducors (structure, doping)
 Silicon thin film solar cells. Comparison with cSi. Silicon heterojunctions
 Cost of PV electricity. Environmental and social impact. Gridintegration challenges.
Niveau requis :
Recommended courses for Ecole polytechnique's students :
PHY430  Advanced Quantum PhysicsÂ andÂ PHY433  Statistical Physics 1
Langue du cours : English
Credits ECTS : 4