GREEN ENERGY WIND INTERFACE-SCHEMES

1
GREEN ENERGY WIND INTERFACE-SCHEMES

• Prof. Dr. A.M. Sharaf, P.Eng.
• ECE-UNB, Canada
• http/www.ece.unb.ca

2
Outline

• Introduction
• Motivations
• Sample Study System Modelling
• Novel FACTS-based Schemes
• Controller Tuning
• Digital Simulation
• Conclusions and Recommendations

3
Introduction

• Wind is a renewable energy source

Load
kinetic Energy
Mechanical Energy
Electrical Energy
4
Introduction

• Wind is also a clean energy source

carbon dioxide
sulfur dioxide
particulates
5
Introduction

• Wind energy is a promising energy and becomes
  increasingly popular.
• The cost of wind-generated electric power has
  dropped substantially.
• By 2005, the worldwide capacity had been
  increased to 58,982 megawatts
• World Wind Energy Association expects 120,000 MW
  to be installed globally by 2010.

6
Introduction
Total installed wind power capacity (data from
World Wind Energy Association)

7
Introduction

• Wind Energy Conversion System (WECS)
• Stand alone
• Electric Grid Connected WECS
• Distributed/Dispersed Renewable Wind Energy
• Located close to where the power is needed
• Low reliability

8
Motivations

• Energy crisis
• Shortage of conventional fuel based energy
• escalating prices
• Environmental Issues
• Greenhouse gas emission
• Acid rain
• Water pollution

9
Motivations

• Large wind farm emerging (in the range of several
  megawatts)
• Many new interface requirements regarding the
  full integration of large dispersed wind power
  into the power grid

10
Motivations

• Challenges for the gird integration of the
  dispersed wind energy
• Highly variable wind power injected into the grid
• Increased penetration of wind energy
• Electrically weak distribution networks
• - Radial structure
• - Large R/X ratio distribution line
• Heavy reactive power burden brought by the
  induction generator

11
System Description
L.L.1
L.L.2
N.L.L
T3
T2
T1
L.L.3
Infinite Bus
WECS
I.M.
12
System Description-WECS
Uncontrolled Rectifier
PWM Inverter
I.G.
Lf
To Grid
Cf
DC Link Interface
Wind Turbine
Cself
13
System Description-wind turbine

• Wind turbine model based on the steady-state
  power characteristics of the turbine
• S -- the area swept by the rotor blades (m2)
• v -- the wind velocity (m/s)
• ?--air density (kg/v3)

14
System Description
tip speed ratio ? is the quotient between the
tangential speed of the rotor blade tips and the
undisturbed wind velocity
C10.5176, C2116, C30.4, C45, C521 and
C60.0068
15
System Description Wind speed

• The dynamic wind speed model consists of four
  basic components
• Mean wind speed-14 m/s
• Wind speed ramp with a slope of 5.6
• Wind gust
• Ag the amplitude of the gust
• Tsg the starting time of the gust
• Teg the end time of the gust
• Dg Teg - Tsg
• Turbulence components a random Gaussian series

16
System Description Wind speed
The eventual wind speed applied to the wind
turbine is the summation of all four key
components.
17
MPFC Scheme

• Complementary PWM pulses to ensure dynamic
  topology change between switched capacitor and
  tuned arm power filter
• Two IGBT solid state switches control the
  operation of the MPFC via a six-pulse diode
  bridge

18
Tri-loop Error Driven Controller
Modulation Index
Voltage Stabilization loop
Current Harmonic Tracking Loop
Current Dynamic Error Tracking loop
19
DVR Scheme
If S1 is high and S2 is low, both the series and
shunt capacitors are connected into the circuit,
while the resistor and inductor will be fully
shorted

• A combination of series capacitor and shunt
  capacitor compensation
• Flexible structure modulated by a Tri-loop Error
  Driven Controller

If S1 is low and S2 is high, the series capacitor
will be removed from the system, the resistor and
inductor will be connected to the shunt
capacitors as a tuned arm filter
20
HPFC Scheme

• Use of a 6-pulse VSC based APF to have faster
  controllability and enhanced dynamic performance
• Combination of tuned passive power filter and
  active power filter to reduce cost

Coupling capacitor
Coupling transformer
PWM converter
Passive Filter tuned near 3rd harmonic frequency
DC Capacitor to provide the energizing voltage
21
Novel Decoupled Multi-loop Error Driven Controller
22
Novel Decoupled Multi-loop Error Driven Controller

• Using decoupled direct and quadrature (dq)
  voltage components
• Using Phase Locked Loop (PLL) to get the
  synchronizing signal the phase angle of the VSC
  output voltage
• Using Proportional plus Integral (PI) controller
  to regulate any tracked errors
• Using Pulse Width Modulation with variable
  modulation index

23
Novel Decoupled Multi-loop Error Driven Controller

• Outer voltage regulator tri-loop dynamic error
  driven controller
• The voltage stabilization loop
• The current dynamic error tracking loop
• The dynamic power tracking loop
• Inner voltage regulator control the DC capacitor
  charging and discharging voltage to ensure a near
  constant DC capacitor voltage

24
Controller Tuning

• Parametric optimization guided Trial-and-error
  method based on successive digital simulations
• Minimize the objective function-Jo
• Find optimal kp, ki and individual loop
  weightings (?) to yield a near minimum Jo under
  different set-selections of the controller
  parameters

25
(No Transcript)
26
Digital Simulation

• Validation is done by using digital simulation
  under a sequence of excursions
• Load switching
• At t 0.2 second, the induction motor was
  removed from bus 5 for a duration of 0.1 seconds
• At t 0.4 second, linear load was removed from
  bus 4 for a duration of 0.1 seconds
• At t 0.5 second, the AC distribution system
  recovered to its initial state.
• Wind gusting changes modeled by dynamic wind
  speed model

27
Digital Simulation

• Digital Simulation Environment
• MATLAB /Simulink/Sim-Power
• Using the discrete simulation mode with a sample
  time of 0.1 milliseconds
• The digital simulations were carried out without
  and with the novel FACTS-based devices located at
  Bus 5 for 0.8 seconds

28
System Dynamic Responses at Bus 2 without and
with MPFC
29
System Dynamic Responses at Bus 3 without and
with MPFC
30
System Dynamic Responses at Bus 5 without and
with MPFC
31
The frequency variation at the WECS interface
without and with MPFC
32
System Dynamic Responses at Bus 2 without and
with DVR
33
System Dynamic Responses at Bus 3 without and
with DVR
34
System Dynamic Responses at Bus 5 without and
with DVR
35
The frequency variation at the WECS interface
without and with DVR
36
System Dynamic Responses at Bus 2 without and
with HPFC
37
System Dynamic Responses at Bus 3 without and
with HPFC
38
System Dynamic Responses at Bus 5 without and
with HPFC
39
The frequency variation at the WECS interface
without and with HPFC
40
Comparison of Voltage THD with Different
Compensation Scheme
Bus number Without compensator With MPFC With DVR With HPFC
1 28.39 4.90 11.9 4.99
2 32.70 4.60 12.2 4.88
3 35.95 4.29 12.6 4.69
4 35.75 3.51 12.2 4.51
5 35.77 3.32 13.1 3.90
6 36.04 3.57 8.57 4.57
41
Comparison of Steady-state Bus Voltage with
Different Compensation Scheme
Bus number Without compensator With MPFC With DVR With HPFC
1 0.97 1.02 1.01 1.05
2 0.95 1.00 1.03 1.05
3 0.94 1.00 1.02 1.05
4 0.89 0.99 1.02 1.05
5 0.86 0.99 1.02 1.06
6 0.83 0.96 1.03 1.05
42
Conclusions

• Three FACTS-based schemes, namely the MPFC, the
  DVR, and the HPFC, have been proposed and
  validated for voltage stabilization, power factor
  correction and power quality improvement in the
  distribution network with dispersed wind energy
  integrated.

43
Recommendation

• The MPFC is preferred for low to medium size wind
  energy integration schemes (from 600 to 5000 kW).
  
• The DVR is good for the AC sub-transmission and
  distribution systems with large X/R ratio
• The HPFC is suitable for the high wind-energy
  penetration level (100 MW or above).

44
Recommendation

• The schemes validated in this research need to be
  fully tested in the distribution network with
  real dispersed wind energy systems.
• This research can be extended to the grid
  integration of other dispersed renewable energy.
• Other Artificial Intelligence based control
  strategies can be investigated in future work.

45
Conclusions

• Developed a unified sample system model using the
  MATLAB/Simulink
• Developed a simple dynamic wind speed model,
  which is suitable to simulate the stochastic and
  temporal wind variations in the MATLAB/Simulink
• Validated the effectiveness of the proposed
  schemes by digital simulations
• Determined the near optimum parameters of the
  proposed compensators with dynamic multi-loop
  error-driven controllers

46
Publications

• 1 A. M. Sharaf and Weihua Wang, A Low-cost
  Voltage Stabilization and Power Quality
  Enhancement Scheme for a Small Renewable Wind
  Energy Scheme, 2006 IEEE International Symposium
  on Industrial Electronics, 2006, p.1949-53,
  Montreal, Canada
• 2 A. M. Sharaf and Weihua Wang, A Novel
  Voltage Stabilization Scheme for Standalone Wind
  Energy Using A Dynamic Sliding Mode Controller,
  Proceeding- the 2nd International Green Energy
  Conference, 2006, Vol. 2, p.205-301, Oshawa,
  Canada
• 3 A. M. Sharaf, Weihua Wang, and I. H. Altas,
  Novel STATCOM Controller for Reactive Power
  Compensation in Distribution Networks with
  Dispersed Renewable Wind Energy, 2007 Canadian
  Conference on Electrical and Computer
  Engineering, Vancouver, Canada, April, 2007
• 4 A. M. Sharaf, Weihua Wang, and I. H. Altas,
  A Novel Modulated Power Filter Compensator for
  Renewable Dispersed Wind Energy Interface, the
  International Conference on Clean Electrical
  Power, 2007, Capri, Italy, May, 2007
• 5 A. M. Sharaf, Weihua Wang, and I. H. Altas,
  A Novel Modulated Power Filter Compensator for
  Distribution Networks with Distributed Wind
  Energy (Accepted by International Journal of
  Emerging Electric Power System)

47
THANK YOU
48
?