Control strategies applied to Wave Energy Converters1 𝑇 𝜇𝑓 𝑇 𝑡𝑣(𝑡)d𝑡 𝑇 0 Some reminders on hydrodynamic control •In principle, reactive control, even in

Control strategies applied to Wave Energy Converters

Paolino Tona

IFP Energies nouvelles

09/09/2019

Stockholm

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 764014

IFP Energies nouvelles at a glance

09/09/2019

One of the only French public research bodies to self-fund

over 50% of its budget

€128.3M budget allocation (2017)

€152M own resources (2017)

50% of budget devoted to NETs

1,622 1,119 R&I engineers and technicians employees

2 facilities:

Rueil and Solaize

IFP Energies nouvelles (IFPEN) is a French public-sector research and training center active in the fields of energy, transport and the environment


IFPEN strategic priorities and core skills

09/09/2019

SUSTAINABLE MOBILITY

Developing effective, environmentally-

friendly solutions for the transport sector

RESPONSIBLE

OIL AND GAS

Proposing technologies that meet

the demand for energy and chemical products

while improving energy efficiency and

reducing the environmental impact

NEW ENERGIES

Producing fuels, chemical intermediates

and energy from renewable

sources


Offshore wind and ocean energies

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Estimation, prediction and control for WECs

Simulation and design tools for fixed and floating foundations

• A project dedicated to WEC control was started in 2013, focusing on • point-absorbers

• model predictive control (MPC) solutions

building on IFPEN expertise in • design and simulation of floating structures

• design and implementation of control strategies (for the automotive and process industries, namely)

Estimation and control for wind turbines


Control of Wave Energy Converters @IFPEN

• Motivation • Control as a key factor to optimize energy production of WECs

• Guiding principles • Reduce the gap between theory and practice, maintaining a good balance

between academic rigor and industrial relevance • 15 publications (4 in journals) + 8 patent applications (7 granted so far)

• Propose an approach as generic as possible, with modular solutions allowing to • Develop control systems of different complexity (i.e. adaptive PI control vs. MPC)

• Adapt them to different machines

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• Milestones and key events • Development of a nonlinear MPC algorithm taking into account

PTO efficiency for reactive-control capable point absorbers (2014)

• Validation of a complete nonlinear MPC system able to run in real-time (2015)

• Start-up of the H2020 UPWAVE project with Wavestar (2016)

• Start-up of the ADEME S3 project with SBM Offshore (2017)

• Participation to the WEC Control Competition (1st place for the simulation phase in 2019, experimental phase under evaluation)


Some reminders on hydrodynamic control

• In many WECs, the PTO is actively controlled in order to apply forces that change the dynamic response of the primary converter to the forces exerted by the waves

• Such active control may be used to improve the harvesting and/or to reduce the forces exerted on the components of the WEC • According to conventional hydrodynamic control theory, maximum recovery

takes place when captor speed oscillates in phase with wave excitation force

• The most significant gains (at least for narrow-banded WECs) are obtained when it is possible to operate the PTO not only as a generator but also as a motor, making it possible to implement "reactive" control

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𝑃𝑒(𝑡) =1

𝑇 𝜇𝑓𝑃𝑇𝑂 𝑡 𝑣(𝑡)d𝑡

𝑇

0

Some reminders on hydrodynamic control

• In principle, reactive control, even in its simplest forms, allows to better adapt WEC natural response band to the current sea state

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𝑣 𝑡

1. 2. 1. P or damping control

𝑓𝑃𝑇𝑂(𝑡) = 𝐵𝑃𝑇𝑂𝑣(𝑡)

2. PI or damping-spring control

𝑓𝑃𝑇𝑂 𝑡 = 𝐵𝑃𝑇𝑂𝑣 𝑡 + 𝐾𝑃𝑇𝑂 𝑣 𝜏 𝑑𝜏𝑡

0

• However, control tuning in a real-life setting requires some care • For instance, gains tuned to maximize mean mechanical power

may even lead to negative net electricity production, as the effect of PTO efficiency 𝜇 is neglected

𝑃𝑎(𝑡) =1

𝑇 𝑓𝑃𝑇𝑂 𝑡 𝑣(𝑡)d𝑡

𝑇

0


On the potential of advanced control: WECCCOMP case study

09/09/2019

• Energy-maximizing control for a small-scale Wavestar device, as in WECCCOMP

• 𝑃𝑒,𝑘: mean electric power for each sea-state k as a function of PTO efficiency 𝜇 (normalized w.r.t. the ideal case 𝜇=1)

• 𝑃𝑒,𝑘

∗, 𝑃𝑒,𝑘

+: upper and lower bounds on

optimal solution computed offline using a spectral approach

• 𝑃𝑒,𝐵𝑝𝑡𝑜: mean electric power obtained with

damping control

• 𝑃𝑒,𝑚𝑖𝑠𝑚: mean electric power obtained assuming 𝜇=1 when 𝜇≠1

Normalized mean electric power 𝑃𝑒,𝑘


On the potential of advanced control: RM3 case study

• Energy-maximizing control for the RM3 device modeled in WEC-Sim

• 𝑃𝑒,𝑘: nomalized mean electric power for each sea-state k as a function of PTO

efficiency 𝜇 𝑃𝑒,𝑘

∗, 𝑃𝑒,𝑘

+: upper and lower

bounds on the optimal solution

• 𝑃𝑒,𝐵𝑝𝑡𝑜: mean electric power obtained with

damping control

• 𝑃𝑒,𝑚𝑖𝑠𝑚: mean electric power obtained assuming 𝜇=1 when 𝜇≠1

• Only position constraints considered

• See [10] for more details

Normalized mean electric power 𝑃𝑒,𝑘

• Interesting potential for the types of WEC studied in SeaTitan (provided that PTO behavior is correctly taken into account)


Is advanced control for WECs mature?

• So far, implementation of hydrodynamic control as reported by WEC manufacturers seems to be limited to very simple strategies

09/09/2019

WEC Type DoF Response band Reactive Control Law Sea Trials

Oyster Flap 1 Large No Coulomb Yes

WaveRoller Flap 1 Large No P Yes

Pelamis Attenuator 2 Narrow Yes MIMO (PI ?) Yes

Wavestar Point absorber 1 Narrow Yes PI Yes

ISWEC Rotating mass 2 Narrow Yes PI Yes

CETO Submerged point absorber 1 Narrow No P Yes

CorPower C3 Point absorber 1 Large No P (I by design) In progress

WaveSwing Submerged point absorber 1 Large Yes Velocity tracking In progress

• Indeed, of the numerous advanced control strategies presented in the literature: • None has undergone sea trials

• Few have been tested in realistic conditions

[As to 2018]


Factors slowing the deployment of advanced WEC control

• Lack of standardization

• Low priority given to control development in the rush to sea installation

• PTO limitations in early prototypes

• Difficulties in performing small-scale tests including PTOs

• Difficulties in developing accurate wave-to-wire simulators for rapid control prototyping

• Limitations of classic hydrodynamic control framework, which assumes • Linearity of WEC dynamics

• Ideal PTOs, in terms of (infinitely fast) dynamics and (100%) efficiency

• Absence of constraints, both on PTO forces and captor motion

• Accessibility of non-measurable quantities (such as wave excitation force)

• Underestimation of the impact of computational constraints when implementing advanced control strategies in real-time

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Model Predictive Control (MPC)

• MPC principle 1. Predict system state over a short

future horizon

2. Compute the optimal control sequence maximizing (or minimizing) an objective function over the horizon

3. Apply only the first step of computed control sequence during one period

4. Start over at the next sample time (receding horizon)

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• Like a chess player • MPC « looks ahead » to

find the winning strategy

• applies one move at time

• changes strategy depending on the reaction

• MPC is an appealing strategy for WECs as it can be used to maximize an energy-related criterion which takes into consideration the future (predicted) behavior of the system, while complying with its physical constraints (PTO forces, motion)


MPC for WECs

• MPC is actually a generic name for a family of control strategies, differing in • Nominal WEC model (linear / nonlinear)

• Discretization method (of the energy-related criterion) and objective function

• Optimization algorithm

which also includes recent MPC-like algorithms based on spectral and pseudo-spectral approaches

• Even when the WEC model is linear, translating realistic WEC control objectives into an MPC framework easily results in non-convex optimization problems, which are computationally complex and difficult to solve in real-time

• Moreover, most MPC algorithms rely on the computation of predictions of the future action of waves on the device, which is not straightforward in a realistic setting

• In this context, experimental tests on a device (or at least hardware-in-the-loop tests with hard real-time constraints) become essential to assess the performance of any MPC and MPC-like strategy

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MPC @ IFPEN

A. Online estimation of the (non measurable) wave excitation force • Only accessible WEC measurements (position, velocity, PTO force) are used

• Same calibration for large ranges of sea-states

• Non-linear terms (such as viscous forces) can be taken into account

B. Short-term prediction of wave excitation force • Only present and past wave excitation moment estimates are used

• Automatic “adaptation” to the current sea-state (same calibration for multiple sea-states)

C. Energy-maximizing MPC, taking into account (non linear) PTO efficiency

• Discretization of 𝑃𝑒(𝑡) =1

𝑇 𝜇𝑃𝑇𝑂𝑓𝑃𝑇𝑂 𝑡 𝑣(𝑡)d𝑡𝑇

0 with 𝜇𝑃𝑇𝑂 =

𝜇 if 𝑓𝑃𝑇𝑂 𝑡 𝑣(𝑡) ≥ 0

1 𝜇 if 𝑓𝑃𝑇𝑂 𝑡 𝑣 𝑡 < 0

• Offline optimization procedure used to choose the parameters of an equivalent convex control problem to be solved on line

A B C

• Typical sampling periods (at full scale) A. 10-50 ms

B. 100-500 ms

C. 100-500 ms


Some lessons learned during MPC development and validation

• IFPEN MPC control system has undergone two experimental test campaigns, on a small scale model of a Wavestar-like device, with different setups

• Tests at this scale can be challenging for MPC as • Friction is more significant than at full scale

• Time scale is smaller, so are algorithm sampling periods

Wavestar-like device in wave tank, Aalborg University, June 2019

• A preliminary analysis of the results of June 2019 tests for WECCCOMP, shows that, despite a badly tuned PTO force control • Wave excitation force can be accurately estimated, except for extreme positions where

peaks and troughs are underestimated or overestimated (but still well captured)

• For a given sea state, the same levels of mean electric power obtained in simulation using the nominal design model (up to 20% more than PI control ), can be observed in the experimental tests, and this, across different realizations of the sea state • However, the offline optimal control solution shows that there should be ~15% more to gain

• MPC is able to run in real-time in a rapid control prototyping framework where any computation longer than 1ms leads to a CPU overload (and thus to a crash)


Sample test results (WECCCOMP SS6)

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10 15 20 25 30 35 40

Time [s]

-15

-10

-5

0

5

10

15

[ N m

]

Estimated (blue) vs measured (red) wave excitation moment

10 15 20 25 30 35 40

Time [s]

-15

-10

-5

0

5

10

15

[ N m

]

PTO torque demand (red) vs applied PTO torque (blue)

10 15 20 25 30 35 40

Time [s]

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

[ r a

d ]

Float position

10 15 20 25 30 35 40

Time [s]

-1

-0.5

0

0.5

1

[ r a

d / s

]

Float velocity (KF estimation)


Conclusions and perspectives

• Among the advanced control strategies proposed so far, MPC has probably the best potential to improve the electricity production from WECs, in particular the narrow-banded ones

• With IFPEN approach, this potential has been proven experimentally at lab scale on a mildly nonlinear fixed-reference point absorber, in the presence of relatively strong constraints on computational time

• Simulation findings show that the approach could be profitably extended to other 1-DoF WECs, but in these different contexts, feasibility, robustness and attainable performance must be studied in more depth and confirmed by experimental testing

Hopefully in the framework of collaborations with WEC manufacturers which are crucial to make progress in this field

For its capacity to realize high and fast force demands, accurately and continuously, in generator and motor mode, direct-drive PTO is the best ally for MPC, in what can be a winning technology combination

09/09/2019


Acknowledgements

Many thanks to Aleix Arenas and the workshop organizers for this invitation and…

All the best with the SeaTitan project!

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www.ifpenergiesnouvelles.com

@IFPENinnovation

Find IFPEN on:

For further information, please write to: [email protected]


WEC control references

a. Korde, U. A. and Ringwood, J. V., Hydrodynamic Control of Wave Energy Devices, Cambridge University Press, 2016

b. Falnes, J., A review of wave-energy extraction, Marine Structures, 20(4):185{201}, 2007

c. Ringwood, J., Control Optimisation and Parametric Design, in Numerical Modelling of Wave Energy Converters, M. Folley, Ed., Academic Press, pp. 229 – 251 , 2016

d. Faedo, N. Olaya, S. and Ringwood, J.V. Optimal control, MPC and MPC-like algorithms for wave energy systems: An overview, IFAC Journal of Systems and Control, Vol.1, pp: 37-56, 2017

e. Wave Energy Scotland (WES), Control Requirements for Wave Energy Converters Landscaping Study, Technical report ref. WES_LS04_ER_Controls, WES, July 2016.

f. Ringwood, J. V., Ferri, F., Ruehl, K., Yu, Y.-H., Coe, R., Bacelli, G., Weber, J. and Kramer, M. M., A competition for WEC control systems, in 12th European Wave and Tidal Energy Conference, 2017

09/09/2019


IFPEN references

1. Nguyen, H.-N. and Tona, Wave excitation force estimation for wave energy converters of the point absorber type, IEEE Transactions on Control Systems Technology, DOI: 10.1109/TCST.2017.2747508 , 2017

2. Nguyen, H.-N and Tona, P., Continuously Adaptive PI-Control of Wave Energy Converters under Irregular Sea-State Conditions, In Proceedings of the European Wave and Tidal Energy Conference (EWTEC) 2017

3. Nguyen, H.-N. and Tona, P., An efficiency-aware continuous adaptive proportional-integral velocity-feedback control for wave energy converters, Renewable Energies, Volume 146, February 2020

4. Nguyen, H.-N and Tona, P., Robust Adaptive PI Control of Wave Energy Converters with Uncertain PTO Systems, 57th IEEE Conference on Decision and Control (submitted), Miami, USA, 2018

5. Nguyen, H.-N., Tona, P., and Sabiron, G., Dominant wave frequency and amplitude estimation for adaptive control of wave energy converters, in MTS/IEEE OCEANS 2017 Conference, Aberdeen, U.K., 1978

6. Tona, P., Nguyen, H.-N., Sabiron, G., and Creff, Y., 2015. An efficiency-aware model predictive control strategy for a heaving buoy wave energy converter. Proc. EWTEC2015, Nantes, FR

7. Nguyen, H.-N., Sabiron, G., Tona, P., M. Kramer, Vidal Sánchez, E., 2016. Experimental validation of a nonlinear Model Predictive Control strategy for a wave energy converter prototype. Proc. OMAE 2016, Busan, KR, 2016

8. Nguyen, H.-N. and Tona, P., Short-term wave force prediction for wave energy converter control, Control Engineering Practice, vol. 75, pp. 26–37, 2018

9. Tona, P., Sabiron, G., Nguyen, H.-N., An Energy-maximising MPC Solution to the WEC Control Competition. Proc. OMAE 2019, Glasgow, UK

10. Mérigaud, A. and Tona, P., Spectral control of wave energy converters with non-ideal power take-off systems, IEEE Transactions on Sustainable Energy (submitted), 2020

09/09/2019

Documents

Control strategies applied to Wave Energy Converters1 𝑇 𝜇𝑓 𝑇 𝑡𝑣(𝑡)d𝑡 𝑇 0 Some reminders on hydrodynamic control •In principle, reactive control, even in