Georgia Institute of Technology | Milwaukee School of Engineering | North Carolina A&T State University | Purdue University

University of Illinois, Urbana-Champaign | University of Minnesota | Vanderbilt University

Project 1J.1: Hydraulic Transmissions

for Wind Energy

Researchers: Biswaranjan Mohanty,

Feng Wang, Brad Bohlmann,

Mike Gust

PI: Professor Kim A. Stelson

Center for Compact and Efficient Fluid Power

Department of Mechanical Engineering

University of Minnesota

FPIRC, Chicago, October 14-16, 2015

2

Outline

1. Introduction

2. Research topics

Hydrostatic turbine control

Short-term energy storage

Hydro-mechanical transmission

3. Power regenerative wind turbine test platform

4. Conclusions

3

• Fastest growing clean and green energy sources

• 370 GW by 2014, 5% of the global electricity demand

• Denmark has goal of 50% wind by 2020

• 67.87 GW till June 2015, 5.13% of the U.S. electricity demand

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

Introduction

4

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

• Three actuators: Yaw motor, Pitch motor & Generator

• Synchronous or asynchronous generator

Turbine Components

5

Components reliability

WindStats Data

- 5,000 turbines from Denmark, 24,000 from Germany & 1,200 from Sweden

Electrical system has highest failure rate

Gear Box has longest downtime per failure

Drive train repairs are more expensive due to the crane costs.

6

Hydrostatic transmission (HST):

Simple system structure

Continuous variable transmission ratio

No need of power converter

All power transmitted through a fluid

link; hence less stiff

Improves reliability and reduce cost

Conventional gearbox turbine

Rotor

GeneratorPower

converter

fixed ratio gearbox

Grid

Rotor

Hydrostatic transmission

Generator Grid

Pump

Motor

Hydrostatic wind turbine

Potential of HST wind turbine

Performance Objective

Maximize captured power

Minimize loads

Reduce downtime

Reduce maintenance cost

7

HST wind turbines

Core technology: Digital displacement technology by Artemis

Mitsubishi 7MW Sea Angel offshore turbine

1. ChapDrive (Norway)

2. Windera Power System (Florida)

3. WindSmart (Canada)

4. Mitsubishi Heavy Industry

93.5% peak efficiency from shaft-to-shaft, and

also very efficient in part load too

Aachen University IFAS 1 MW

HST wind power test stand

8

Midsize HST turbine in CCEFP

Mid-size turbines can be designed as

locally distributed type, eliminating the

costly electric power transmission and

improving energy use efficiency.

CCEFP target: midsize wind (100 kW-1 MW):

Community wind - cost-effective way for

farms, communities or factories

Relatively easy permitting process

Few midsize turbines in the market today

Commercially available hydrostatic units

Community wind

9

Turbine Control

Wind speed

Turbine power

Rated speed Cut-out speed

Region 1 Region 2 Region 3

Rated power

Cut-in speed

Region 4

Four control regions:

Region 1: Standby mode

Region 2: Control to maximize power

Region 3: Control to rated power

Region 4: Turbine shut down

Rotor power coefficient (Cp) is the fraction of wind

power captured by the rotor:

Rotor tip speed ratio:

𝐶𝑃 =𝑃𝑟𝑃𝑤

= 𝐶𝑃(λ, β)

λ =ω𝑟𝑅

𝑢

𝑃𝑤 =1

2ρ𝐴𝑢3

According to Betz Law, the maximum energy that can be captured by the rotor is 59.3% of the

kinetic energy of the wind

* 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.

10

Torque control law - control rotor reaction

torque:

where the gain K is given by blade parameters.

Region 2 Control (Existing)

• Objective: Maximize power captured

• Strategy: Constant pitch angle β and use τ𝑔 to operate turbine at optimum point

τ𝑔 = τ𝑐 = 𝐾ω𝑟2

𝐾 =1

2ρ𝐴𝑅3

𝐶𝑝𝑚𝑎𝑥

λ∗3

Dynamics of the rotor

ω𝑟 =1

2𝐽ρ𝐴𝑅3ω𝑟

2(𝐶𝑝

λ3−

𝐶𝑝𝑚𝑎𝑥

λ∗3 ) u

142 4 6 8 10 12

0.3

0.4

0.5

0.2

0.1R

oto

rp

ow

er c

oeffic

ien

t

Tip speed ratio

pC

maxpC

*

Acceleration Deceleration

max

3 3

*

p pC C

max

3 3

*

p pC C

max

3 3

*

p pC C

Optimum point

The beauty of the kω2 law: bring the turbine to

optimal point only with rotor speed and it does not

require wind speed information.

11

HST turbine control in region 2

Control strategy

1. Use rotor speed to generate rotor reaction torque (pump torque) command (kω2 law)

2. Convert pump torque command to line pressure command

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

Rotor

Hydrostatic transmission

Generator

Kω2 law

Torque/

pressure

conversion

torque

cmd

pressure

cmd PI

controller

Pressure

sensor

+-

motor

disp. cmd

p

c c

p

pD

HST turbine control scheme in region 2

where ηp is the pump mechanical

efficiency.

• 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

The relationship between the

pump torque command and the

line pressure command:

To give accurate control, the pump

mechanical efficiency is estimated by

previewing the pump efficiency

map from the historical rotor speed

and line pressure data.

12

Dynamic simulation model

Main features of the simulation model:

1. Physical equation based components model;

2. Use bond graph method to determine the causality;

3. Use FAST code to generate rotor efficiency map;

4. Use pump/motor efficiency map to determine the HST losses;

5. Use distributed line model to simulate line dynamics and losses.

6. Take the charge pump power into consideration.Hydrostatic wind turbine

Wind profile

Valve manifold

Radial piston pump

Low pressure pipeline

High pressure pipeline

Generator

Controller

Charge pump

Bent/axial piston motor

Aerodynamic rotor

rotor speed

pump output flow

pump torque

pump outlet pressure

motor inlet pressure

motor input flow

motor torque

motor speed

total motor

displacement fraction

pump input flow motor output flow

charge flow

total input flow to low pressure line

motor outlet pressure

pump inlet pressure

pitch angle

13

Short-term energy storage

To increase the energy capture of an HST wind turbine, a short-term energy storage

system using a hydraulic accumulator is proposed.

Energy storage regime

Captures excess energy when the wind speed is above rated (region 3)

Release stored energy when the wind speed is below rated (region 2).

𝑃𝑤𝑖𝑛𝑑 =1

2𝜌𝐴𝑢3

Wind turbulence: Gaussian distribution

10 minutes turbulent wind profile

* R. Dutta, F. Wang, B. Bohlmann and K. A. Stelson, “Analysis of short-term energy storage for mid-size hydrostatic wind turbine,” in Proc. ASME

Dynamic Systems and Control Conference, Fort Lauderdale, FL, USA, 2012, selected as top 20 outstanding finalist papers.

- mean wind speed

Store

Release

Wind speed

Turbine

power

Rated speed Cut-out speed

Region 1 Region 2 Region 3

Rated

power

Cut-in speed

14

PPo

o Fixed

pump

M1 M2

Generator

pD

Accumulator

Displacement

control

Rotor

M1 – Variable motor

M2 – Variable pump/motor

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

0 20 40 60 80 100 120

% in

cre

ase

Accumulator Volume (liter)

% increase in AEP

Sensitivity study: accumulator size on

annual energy production (AEP) in a 50 kW

turbine:

• 40 liter accumulator increases AEP by 3.4%

• 60 liter accumulator increases AEP by 4.1%

Short-term energy storage

Generator power with and without storage

A cost analysis is required to determine

whether the AEP increase will offset the

cost increase of implementing the system.

* R. Dutta, F. Wang*, B. Bohlmann, K. Stelson, ‘Analysis of short-term energy storage for mid-size hydrostatic wind turbine’, ASME Transaction,

Journal of Dynamic Systems, Measurement, and Control, 136(1), 2013.

Energy storage configuration

15

p

p

pT

dT

Rotor

px

QR1

C1

S1

R2

C2

S2

r

rTmT

m

g

gT

Hydro-mechanical

transmission

mD

pD

T

v

Generator

Hydro-mechanical wind turbine

Hydro-mechanical wind turbine (PGS+HST)

R- ring gear

C- carrier

S- sun gear

Hydraulic powerMechanical power

A hydro-mechanical transmission combines the

advantages of high efficiency of a gearbox and

variable function of an HST.

* F. Wang, B. Trietch and K. A. Stelson, ‘Mid-sized wind turbine with hydro-mechanical transmission demonstrates improved energy production’,

Proc. 8th International Conference on Fluid Power Transmission and Control (ICFP 2013), Hangzhou, China, 2013.

4 5 6 7 8 9 10 110

0.2

0.4

0.6

0.8

1

Wind speed (m/s)

Dri

vetr

ain

eff

icie

ncy

Simulated (HMT)

Simulated (HST)

4 5 6 7 8 9 10 110

2

4

6

x 104

Wind speed (m/s)

Gen

era

tor

po

wer

(W)

Simulated (HMT)

Simulated (HST)

HMT vs HST (real-world components data)

16

A. Power Regenerative Test Platform

M

VFD

Hydrostatic Transmission

(HST)Hydrostatic Drive

(HSD)

Virtual rotor Turbine output

Variable

Frequency

Drive

Virtual wind

simulated by

hydrostatic

drive

Real HST under test

To Investigate the performance of hydrostatic transmission

To test the advanced control algorithm

1. Capable of simulating a turbine output power of 105 kW

2. Small electric motor (55kW) to compensate for losses in the components (assuming overall

efficiencies of the pump and motor are 90% each)

55 kW

105 kW160 kW

17

Electric

power input

Virtual rotor

Turbine

output

180 cc Bosch

variable pump

135 cc Linde

variable motor

2512 cc Hagglunds

motors (act as pump)2512 cc

Hagglunds motors

A. Power Regenerative Test Platform

18

A. Power Regenerative Test Platform (Status)

VFD

Electric MotorPump(HSD)

Motor(HST)

Pump(HST) Rotor Motor(HSD)

Charge

Circuit(HST)

Cooler

Torque

Sensor

19

A. Wind turbine rotor simulation

Aerodynamic torque is a function of pitch angle,

rotor speed and wind speed

To simulate real dynamics of the rotor of a

turbine, the effect of the large blade inertia will

be virtually simulated and the modified torque is

applied on the rotor of the test platform

τ𝑑 = τ𝑟 − (𝐽𝑟 − 𝐽𝑠) ω𝑟

Design a controller to track desired torque

using HSD circuit

To generate aero dynamic torque for 105 kW

turbine by modifying the blade dynamics of the

FAST code

20

Conclusions

The proposed HST turbine control strategy based on torque control law is applicable to

the real world HST turbine.

Short-term energy storage with hydraulic accumulator can improve the turbine energy

production. A cost analysis is required to determine whether the energy increase will offset

the cost increase of implementing such system.

A hydro-mechanical transmission combines the advantages of high efficiency of a

gearbox and variable function of an HST, resulting a high turbine energy production. The

cost and reliability analysis is still required.

The power regeneration wind turbine test platform enables simulating the real word HST

turbine behaviors in the lab, providing a powerful tool to investigate research topics.

New improvements could come from advanced turbine control strategies, more efficient

hydraulic transmissions and new hydraulic fluids.

21

Feng Wang

University of Minnesota

Kim A. Stelson

University of Minnesota

Mike Gust

University of Minnesota

Thank you!

Ching-Sung Wang

National Taiwan University

Biswaranjan Mohanty

University of Minnesota

Brad Bohlmann

University of Minnesota