enhancing energy capture in wind turbines using a

ENHANCING ENERGY CAPTURE IN WIND TURBINES

USING A HYDROSTATIC TRANSMISSION AND

DYNAMIC PITCHING

Daniel Escobar-Naranjo

PI: Prof. Kim A. Stelson

Hydraulic Power Transmission Lab

Department of Mechanical Engineering

University of Minnesota

2/24

Wind statistics

• Fastest growing new energy source

• 600 GW by 2018, 6% of the global electricity demand

• 97 GW by 2019, 7% of the U.S. electricity demand

• DOE set goal of 20% of U.S. energy from wind by 2030

• Distributed wind turbines (<1 Mw) are an attractive but under recognized means to meet this goal

Source: EIA, International Energy Outlook 2019

3/24

Conventional wind turbine

• Two or three stages of planetary or parallel shaft gear train

• Three actuators: yaw motor, pitch motor & generator

• Synchronous or asynchronous generator

WES 100 Gearbox (100 kW)

Manufacturer Siemens

Number of stage 2

Weight 820 kg

Ratio 0.055

GE 2.3 MW

4/24

Conventional Wind Turbine: Reliability

• Studies show the major components contributing to low reliability and increased downtime of turbines are found to be the gearbox, generator and the drive train.

• This failure decreases the annual energy productions and increases the maintenance cost.

* http://www.reliawind.eu/

* C Ensslin, M Durstewitz, B Hahn, B Lange, K Rohrig (2005) German Wind Energy Report 2005. ISET, Kassel

5/24

Research Objectives

• Target: Community Wind (<1MW)

• Cost-effective for farms, communities, factories and rural electric cooperatives.

• It can operated in local niches, eliminating the need for costly electric power transmission upgrades.

• Commercially hydrostatic units are available in required size.

• Develop an efficient and reliable hydrostatic drive train for community wind (<1 MW) turbine.

• Design a controller to maximize the energy capture and stabilize the power grid.

6/24

55 kW~100 kW ~155 kW

Power Regenerative Test Platform

• To Investigate the performance of hydrostatic transmission

• To test the advanced control algorithm

• Capable of simulating a turbine output power of 100 kW

• Small electric motor (55kW) to compensate for losses in the components

Components

• Pump and Motor

• Transmission

• Speed down transmission (HSD)

• Speed up transmission (HST)

• Fluid Testing

• Independent hydraulic circuit for HSD and HST with temperature control

7/24

Power Regenerative Test Platform

8/24* Johnson, K. E. , Pao, L. Y. , Balas, M. J. , Fingersh, L. J. Control of variable-speed wind turbines: standard and adaptive techniques for

maximizing energy capture. IEEE Control Systems Magazine, Vol. 26(3), pp.70–81, 2006.

Turbine Control in Region2• Wind Power

– 𝑃𝑤𝑖𝑛𝑑 =1

2𝜌𝐴𝑢𝑤

3

• According to Betz Law, the maximum energy that

can be captured by the rotor is 59.3% of the kinetic

energy of the wind

• Rotor power coefficient (𝑪𝒑) is the ratio of wind

power captured by the rotor:

– 𝐶𝑝 =𝑃𝑟𝑜𝑡

𝑃𝑤𝑖𝑛𝑑

• Rotor Tip Speed Ratio

– 𝜆 =𝜔𝑟𝑅

𝑢𝑤

• Objective: Maximize power capture with constant

pitch angle 𝛽

9/24

142 4 6 8 10 12

0.3

0.4

0.5

0.2

0.1Ro

tor

po

we

r c

oe

ffic

ien

t

Tip speed ratio

maxpC

*

Acceleration Deceleration

max

3 3

*

p pC C

=

max

3 3

*

p pC C

max

3 3

*

p pC C

Optimum point

𝜏𝑎𝑒𝑟𝑜 𝜏𝑐

𝐽𝑡, 𝜔𝑟

𝐽𝑡 ሶ𝜔𝑟 = 𝜏𝑎𝑒𝑟𝑜 − 𝜏𝑐

𝑢𝑤

Turbine Control in Region2

• Torque control law - control rotor reaction torque:

𝜏𝑐 = 𝐾𝜔𝑟2

where the gain K is given by blade parameters.

𝐾 =1

2ρ𝐴𝑅3

𝐶𝑝𝑚𝑎𝑥

λ∗3

• Dynamics of the rotor

ሶω𝑟 =1

2𝐽𝑡ρ𝐴𝑅3ω𝑟

2(𝐶𝑝

λ3−

𝐶𝑝𝑚𝑎𝑥

λ∗3 )

• The beauty of the 𝒌𝝎𝟐 law: bring the turbine to optimal

point only with rotor speed and it does not require wind

speed information.

10/24

HST turbine control scheme in region

2

• F. Wang and K. A. Stelson, ‘Model predictive control for a mid-sized hydrostatic wind turbine’, 13th Scandinavian International Conference on Fluid Power, SICFP2013, June 3-5,

2013, Linköping, Sweden, 2013.

Rotor reaction torque generated by the pump

HST Turbine Control in Region2

Control Strategy

1. Use rotor speed to generate a reference pressure command

2. Track the line pressure by adjusting motor displacement through PI controller.

3. For this strategy we need rotor speed measurement to design the reference pressure and pressure measurement for

feedback control.

• Torque is proportional to the pressure. The control

pressure is:

𝑝𝑐 =𝐾𝜔𝑟

2

𝐷𝑝𝜂𝑚

Where 𝜂𝑚 is the pump’s mechanical efficiency.

• To have an accurate control, the pump’s mechanical

efficiency is estimated by previewing the pump’s

efficiency map from the historical rotor speed and line

pressure data

11/24

Hardware-in-the-Loop Wind Simulation

Regulating 𝜔𝑟 with HSD swash plate position and 𝑝𝑡 with HST swash plate position.

12/24

Step GustTurbulent

Hardware-in-the-Loop Wind SimulationTurbine Specifications

• Polaris 60 kW

• Horizontal axis variable speed turbine

• Rated speed: 10 m/sec

• Rotor diameter: 21.2 m

• Hub height: 30 m

• Rotational RPM: 58 RPM

Transient inputs

13/24

Experimental Results: Step

• Rotor controller tracks the reference rotor speed generated by the HIL.

• HST pressure is tracking the reference pressure with a small delay.

• The turbine response time depends on the inertia of the rotor.

14/24

Experimental Results: Efficiency

• The overall efficiency is computed with ISO 68 hydraulic oil.

• The maximum measured efficiency is 80%.

• The efficiency can be increased to 87-88% by using lower viscosity oil.

• Low wind regime could be improved by using Digital displacement motor or linkage motor.

15/24

Dynamic Pitching to improve Energy Capture in Wind TurbinesRESEARCH QUESTION

Can periodic varying pitch improve energy capture in wind turbines? If so, how much is the improvement andhow does it vary with operating conditions?

5. CONTROL STRATEGY

IMPLEMENTATION

4. DYNAMIC MODEL CREATION

3. WIND TUNNEL EXPERIMENTS2. CFD SIMULATIONS

1. EXPERIMENTAL DESIGN

(a) (b)

(c) (d)

6. WINDTURBINE EXPERIMENTS

16/24

CFD Simulations: Validation

Dynamic pitching simulations using ANSYS

Good correlation between published data and CFD simulations under the same conditions.

Where 𝜔𝑟𝑒𝑑 =2𝜋𝑓𝐶

2𝑉is the reduced

frequency

• f is the rate of rotation (𝑟𝑎𝑑/𝑠)• 𝐶 is the chord length (𝑚)

• 𝑉 is the wind speed (𝑚/𝑠)

17/24

Wind Tunnel Experiment: Validation• Recreate real-life conditions at SAFL Wind Tunnel

• Using a DU96-W-180 airfoil (commonly used in Wind Turbines)

• High Reynolds numbers (106)

– Higher wind speeds (25𝑚

𝑠)

– Smaller chord (~1𝑚)

𝑹𝒆 =𝒖𝒘𝑪

𝝂

18/24

From Blade Element Momentum Theory (BEMT) we know that the torque in the rotor is:

𝑑𝑇 =1

2𝜌𝐵𝑐 𝑟 𝑟𝑉𝑟𝑒𝑙

2 𝐶𝐿 sin 𝜙 − 𝐶𝐷 cos 𝜙 𝑑𝑟

Where :

• 𝜌 is density of air

• 𝐵 is number of blades

• 𝑐(𝑟) is chord at radius 𝑟

Then the power in the rotor is:

𝑃𝑟𝑜𝑡 = න𝑟ℎ𝑢𝑏

𝑅

𝜔𝑟𝑇𝑑𝑟

Where 𝜔𝑟 is the rotor speed (constant)

How do we know if we get more power?

• 𝑉𝑟𝑒𝑙 is relative velocity of the wind

• 𝜙 is incidence angle

• 𝑑𝑟 is the element size

19/24

Preliminary Results: Conditions for Improvement

• Low camber airfoil shape

– DU96-W180

– Oscillate around 𝐶

4

• “Tilted Sinusoid”

– Low average angle of attack 𝛼𝑜 = 8𝑜

– Amplitude 𝐴 = 2.8𝑜

– Frequency 𝑓 = 0.5𝐻𝑧

Up fast Down slow

20/24

Preliminary Results: CFD

Dynamic Pitching exhibits:

• Lower lift

• Lower drag

• Higher lift to drag ratio

𝑅𝑒 = 1.6 × 106

21/24

Preliminary Results: Net Power

4% Overall

improvement!

The torque required to oscillate the turbine blade in

steady state operations is:

𝜏 = 𝜏𝑎𝑒𝑟𝑜Where:

𝜏𝑎𝑒𝑟𝑜 =𝐶𝑚𝜌𝑉𝑟𝑒𝑙

2 𝑐2𝑑𝑟

2• 𝐶𝑚 is moment coefficient

From this we can calculate the power required to

oscillate the turbine blade

𝑃𝑜𝑠𝑐 = 2𝜋𝑓𝜏𝑎𝑒𝑟𝑜• 𝑓 is the frequency of oscillation of the “tilted

sinusoid”

Finally the net power captured by the turbine is:

𝑃𝑛𝑒𝑡 = 𝑃𝑟𝑜𝑡 − 𝑃𝑜𝑠𝑐

22/24

What is next?

• Explore more airfoil shapes (NACA, S8XX, DU,…)

• Explore more average angles of attack (Higher and lower)

• Explore more waveforms (odd harmonics, steeper )

• Explore more frequencies

• Explore more amplitudes

• Validate CFD simulations with wind tunnel experiments

• Plan a control strategy

• Implement in a wind turbine (Eolos, UMN Morris)

23/24

Conclusions• A unique power regenerative test platform has been developed to

demonstrate and validate the performance of a HST for wind turbine

applications.

• The pressure controller strategy was implemented to maximize the power

capture and validated the performance of the HST turbine in HIL

simulation.

• Results show that we can drive the turbine at optimal tip speed ratio to

maximize the power capture.

• Preliminary studies show a 4% overall improvement in power capture by

using dynamic pitching under specific conditions.

• Further studies have to be performed to evaluate various unstudied

scenarios and optimal operation conditions.

24/24

THANK YOU!

Kim A. Stelson Mike Gust Feng Wang

Daniel Escobar Eric Mohr Yuhao Feng John

Sampson

Biswaranjan

Mohanty

Emma Frosina

25/24

26/24

Experimental Results: Gust

• The reference rotor speed has around 1.7 sec delay from the wind input due to large rotor inertia.

• Both the measured signals effectively track their reference counterparts with a small delay.

27/24

Experimental Results: Turbulent

• Aerodynamic torque has high frequency contents.

• The large inertia of the rotor filters out the High frequencies of the turbulent wind.

• Pressure controller is effectively tracking the reference pressure signal to operate the turbine near optimal tip speed ratio.

28/24

Dynamic Modeling and Controls

• Dynamic model based on aerodynamic forces, periodic oscillation conditions, and incoming wind

• Dynamics of pitch control are faster than the standard 𝐾𝜔2 torque control

• Pitch control with hydraulic actuators

• Superposition of 2 controllers will improve the power capture

• Optimization by using optimal periodic control strategies