Reducing Mechanical Complexity with AI-inspired Control

Reducing Mechanical Complexity withAI-inspired Control

Niall McMahon,Trinity College Dublin

ViennaSeptember 15th, 2016

Niall McMahon, Trinity College Dublin Reducing Mechanical Complexity with AI-inspired Control

Control is (Very) Important

I In the 1980s many wind turbines werestall-regulated fixed-pitch machines.

I The rotors were usually equipped with integraloverspeed protection such as ailerons, tipbrakes, flip tips and other similar devices.

I Nowadays, most machines have variable pitchsystems (active or passive), in addition tomechanical braking systems.


Control is Expensive

Control systems add complexity and cost to windturbine systems.


Reducing Complexity Reduces Cost

I Fewer complicated components.

I Fewer mechanisms and potential failure points.

I Relative ease of manufacture and assembly.

I Reduced maintenance requirements.


How Can We Reduce Mechanical Complexity?

Eliminating mechanisms, i.e.

I Pitch systems. Fixed pitch systems are oftencoupled to induction generators, e.g. Gaia-Wind133.

I Mechanical brake systems. These are usually leftin place, with some exceptions, e.g. firstgeneration Ampair 6000.

Possible replacements for these systems includeblade-mounted control and electrodynamic braking.i.e. short-circuiting the generator.


IEC 61400-2 r3 Guidelines

Section 8: Protection and Shutdown System

The SWT shall be designed in order to keep allparameters within their design limits under alldesign load cases. This shall be achieved through anactive and/or passive protection system included inthe design. There shall be means to preventthe rotational speed design limit ηmax frombeing exceeded.


IEC 61400-2 r3 Guidelines

The protection system shall be designed to befail-safe. It shall be able to protect the SWT fromany single failure or fault in a power source or in anynon-safe-life component within the control andprotection system ... A failure of the control,power, or protection system shall not allowthe turbine to exceed the ηmax rotationalspeed or go into an unsafe state of operation.


Electrodynamic Braking Has Been Attempted

Several manufacturers have attempted to buildelectrodynamic braking-based systems that complywith the standards, e.g.

I Ampair A6000 (first generation)

I Southwest Skystream

I Evance R9000

With mixed results ...


There Have Been Failures

Taken from the Dorset Echo (c) 2010. The car in the photograph wasdamaged before the machine fell over.


Electrodynamic Braking Failures

Electrodynamic braking is hard to do right:

1. Wind turbine rotor torques can quickly exceedgenerator short-circuit torques, even at windspeeds close to rated;

2. The energy dumped into the generator duringbraking is significant and can cause rapidheating to high temperatures.


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Tor

que

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Rate of Rotation [RPM]

Peak short-circuit torque (300 STK 2M)Simple short-circuit torque curve (500 STK 2M)

Rotor torque: 2 m/s4 m/s6 m/s8 m/s

10 m/s12 m/s14 m/s16 m/s18 m/s20 m/s22 m/s


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Tor

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Increasing short-circuit resistance -->

Peak Short-Circuit Torque (300 STK 2M)Simple SC




Typical Failure

1. Wind speed increases.

2. Rotor torque exceeds generator capacity.

3. Accelerates to maximum λ (8+). Overspeed.4. Something breaks:

4.1 Transient high energy discharge into generator.4.2 Temperature increases rapidly.4.3 Magnets come off.4.4 Tower fails at base.4.5 Other bad things ...


Goal

Maintain rate of rotation below critical value whilemaintaining generator health.


System Specification

I 4 m rotor diameter.

I No gearbox.

I Synchronous permanent magnet machine.

I 4 kW nominal output with 5 kW dump load.

I Alxion 300 STK 2M type generator architecture.


Braking Strategy

Adjust speed with:

1. Dump load.

2. Short-circuit load, tuned by varying theshort-circuit resistance.

3. Emergency stop system (pin etc. ...)

Simplified model. Monitor:

1. Ω - rotor speed.

2. U - wind speed.

3. T - generator internal temperature(T2 = E

2mc + T1).


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1000 1050 1100 1150 1200

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Tor

ques

(N

m)

Rotational Speed (RPM)

Rotor Torques

2 m/s4 m/s6 m/s8 m/s

10 m/s12 m/s14 m/s16 m/s18 m/s20 m/s22 m/s24 m/s


Braking Constraints

I Do not release short-circuit if danger ofoverspeed. Release when safe. Stop ifopportunity.

I Maintain energy transfer (power) to generatorwindings/magnets within safe limits.

I Do not brake while peak braking torqueexceeded by rotor.

I Account for system response time.


Basic Control

1. Maintain operation close to nominal withload/dump load until U = 12 m/s.

2. If RPM exceeds maximum, halt system usingelectrodynamic brake. Wait until cool andre-start.

3. If U > 12 m/s, bring system to a halt. Waituntil cool and re-start.


Intelligence - Step 1: Hard Coded Rules

1. As U increases, calculate rolling averages, U .Estimate error bars about averages at differentscales, +/− ε.

2. As U + ε exceeds 12 m/s, stop machine.

3. If RPM exceeds upper critical value, stopmachine.


Intelligence - Step 1: Hard Coded Rules

4. If U or RPM exceed max. generatorshort-circuit capability:

I If it is likely that the wind will drop again very soon after,I If structural limits are note exceeded at that wind speed/RPM,I Then allow to free-wheel and wait until the wind drops.I (Uncontrolled-but-safe overspeed.)I Then take the rotor speed all the way down to zero.


Intelligence - Step 2: Machine Learning

1. Train artificial neural network to recognisepatterns in wind at that site and on generatorcapability.

2. System anticipates braking opportunities.

3. System anticipates uncontrolled-but-safeoverspeed opportunities.


Challenges

These are many and include:

1. May not be possible to do with real systems.

2. Real generator short-circuits have transienteffects, simplified away here.

3. Effective cooling may pose a problem for realgenerators.

4. Cost benefit must be at least ≈ 10% overregular systems to compensate for lost winds atthe high end.


Hardware and Software

Python running on ...

... a Raspberry Pi 3.


References

See http://www.niallmcmahon.com/vienna/ forsummary article.


Acknowledgements

With thanks to:

I Sustainable Energy Authority of Ireland.

I David Sharman and Peter Burton, formerly ofAmpair.

I Henry Rice and others at TCD.

And, in particular,

I Kurt Leonhartsberger, FH Technikum Wien andKleinwindkraft 2016 and sponsors.


Thank You

Questions?


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Reducing Mechanical Complexity with AI-inspired Control