CONTROL ASPECTS OF WIND TURBINES Faizal Hafiz, Wind Energy Research Group, SET Center
Presentation Outline 2 Power in Wind Maximum Power Point Tracking Connection Topologies Active Power Control How? Grid Integration: Challenges Grid Integration: Possible Solutions Intelligent Control
Power in the wind 3 The total power that is available to a wind in watts, P w 0.5 m w v 2 0.5 ρ A v 3, where, m w ρ A v ρ density of the air (kg/m 3 ) A the exposed area (m 2 ) v the velocity (m/s) The mechanical power, P m c p P w 0.5 c p m w v 2 0.5 ρ c p A v 3 where, c p performance co efficient
Power in the wind Bet z Limit Assume, inlet wind velocity is v i and the output velocity is v o and the mass flow rate, m w, through the system is approximately ρ A v ave where,. Wind Power, P w 1 Solving for maximum value, P P 0.593
Power in the wind Cp 0.5 0.4 0.3 0.2 0.1 0-0.1 C p is a function of both λ & θ (pitch angle), C p f λ, θ where, Tip speed ratio, λ ω t R/v wind ω t turbine rotational speed -0.2 R rotor radius 0 5 10 15 Tip speed ratio v wind wind speed.
Power in the wind 6 3.5 4 x 106 3 12 m/s 14 m/s 15 m/s 2.5 11 m/s Mechanical power 2 1.5 1 0.5 9 m/s 10 m/s 13 m/s 0-0.5 6 m/s 4 m/s 7 m/s 8 m/s -1 0 0.5 1 1.5 2 2.5 3 3.5 rotational speed
Power Curve Hysteresis
8 General Structure of WECS
9 Danish Concept Fixed Speed
10 Direct in line wind turbine system
11 Doubly Fed Induction Generator (DFIG)
Active Power Control How do they do it? 12
Model of Wound Rotor Induction Machine 13 icr 3 2π θr cos br i 3 2π θr cos cosθriar Lsr ics bs i L mut,s ias leak,s L self,s L λas where, dt cs dλ Rsics vcs dt bs dλ bs Rsi bs v dt as dλ Rsias vas winding, stator for frame,equations in abc model Machine &,
Reference Frame Theory i ds Transformation matrix to convert quantity into d -q axes from abc axes is, i dr Ts 2 3 sinθ cosθ sin θ 120 cos θ 120 sin θ 120 cos θ 120 and inverse transformation is given by, i qr i qs 1 Ts sinθ sin θ 120 sin θ 120 cosθ cos θ 120 cos θ 120
Control Concept 15 Line Voltage Oriented Control Electromagnetic torque in line voltage oriented frame is given by, T e λ ds i qs λ qs i ds λ qs i ds L m L ss i dr λ qs and, λqs v ds rs i ds
MPPT Maximum Power Point Tracking T * e L m L ss * λ qs i dr * i dr L ss L m λ qs T * e Turbine characteristics and tracking characteristic Reference current calculations for tracking maximum power point.
Rotor Side Current Controller 17 Ids S*Lm Qref Iqr * x 3 x 4 Kp3 +ki3 /s Kp2 +ki2 /s Vq Vqr * Q Iqr S*Lrr Idr S*Lrr T e * L ss / L m λ s Idr * x 2 Kp2 +ki2 /s Vd Vdr * MPPT Iqs S*Lm * i dr Lss T * L e m λ qs 1 dλ v ds ds rs i ds λqs ω s dt λ qs v ds r s i ds v v * dr * qr v v ' d ' q sω sω s s L L rr rr i i qr dr sω sω s s L L m m i i qs ds
Rotor Side Converter Control 18 * i dr Lss T * L e m λ qs 1 dλ v ds ds rs i ds λqs ω s dt λ qs v ds r s i ds
Grid Integration 19
Grid Integration Concerns: LVRT, Grid Support Services, Economic Concerns Possible Solutions: Ancillary grid support services Wind Power Forecasts Intelligent Control: Nature Mimicking Algorithms
Grid Inertia Gird Inertia : Supply Demand mismatch Synchronous Generator: Inherent Response Wind Turbines Inertia? Courtesy: GE Energy Primary Frequency Support?
Intelligent Inertia Emulation Objectives, Adaptive Inertia Controller for Individual WT WF level control & Co ordination Short Term Wind Forecasting
Inertial Response: Challenge 1.2 1.1 Rotor Speed and Active Power (pu) 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 6 7 8 9 10 11 12 13 14 15 Wind Speed (m/s) wr Pe G. Lalor, A. Mullane, and M. O'Malley, "Frequency control and wind turbine technologies," Power Systems, IEEE Transactions on, vol. 20, pp. 1905 1913, 2005.
Inertial Response: Possible Solution
Inertial Response: Possible Solution WT Active Power (pu) 0.5 0.45 0.4 0.35 0.3 0.25 0.2 No Support SOP-2 PD Wind Speed : 7.0 m/s 0 10 20 30 40 50 60 70 80 Time (s) WT Rotor Speed (pu) 0.9 0.88 0.86 0.84 0.82 0.8 0.78 0.76 0.74 Wind Speed : 7.0 m/s No Support SOP2 PD 0.72 0 10 20 30 40 50 60 70 80 90 100 Time (s) 50 49.8 Wind Speed : 7.0 m/s Frequency (Hz) 49.6 49.4 49.2 49 48.8 48.6 48.4 No Support SOP-2 PD 48.2 0 5 10 15 20 25 30 35 40 45 50 Time (s)
Inertial Response: Opportunities 60 40 20 0 7 8 9 10 11 12 Wind Speed (m/s) 13 14 15 0.3 0.25 0.2 0.15 Additional Power, Psupport (pu) 0.1 0.05 Time to hit the minimum rotor speed Tsupport,max (s)
Inertia Emulation: Proposed Approach 1 50 49.8 49.6 Frequency (Hz) 49.4 49.2 49 48.8 48.6 No Support SOP-1 SOP-2 PD OSOP 48.4 Wind Speed : 7.0 m/s 48.2 0 5 10 15 20 25 30 35 40 45 50 Time (s)
Inertia Emulation: Proposed Approach 2 50 A B Frequency (Hz) 49.5 49 48.5 No Support PD AIC 0 50 100 150 200 250 Time (s)
MPPT, Desirable? 29
Effects of Aggregation 30 1 Wind tu r b in e 30 Wind turbines 150 Wind turbines 300 Wind turbines Reproduced from Wind Power in Power Systems, Wiley, Ed. Thomas Ackermann, pp. 37
Further Possibilities Future Research Effect of wakes on inertial support Active Power Control for Primary Frequency Support (PFS) Co ordination of WTs for PFS Wind Farm level Control Short Term Wind Forecasting
Nature Inspired Algorithms
Nature Inspired Algorithms Neural Computation the brain Evolutionary Computation evolution Swarm Intelligence group behavior
Swarm Intelligence Collective behaviors of (unsophisticated) agents No centralized control Collective (or distributed) problem solving Leverage the power of complex adaptive systems to solve difficult non linear stochastic problems
Swarm in Action
Research 36 Journal Publications: 1. F. Hafiz and A. Abdennour, "A team oriented approach to particle swarms," Applied Soft Computing (IF: 2.86), Elsevier, vol. 13, pp. 3776 3791, 2013. 2. F. Hafiz and A. Abdennour, Optimal use of kinetic energy for the inertial support from variable speed wind turbines, Renewable Energy (IF: 3.36), Volume 80, Pages 629 643, August 2015. 3. F. Hafiz and A. Abdennour, "A Neuro Fuzzy Adaptive Inertia Controller for Variable Speed Wind Turbines," Renewable Energy, Elsevier (IF: 3.36), Under Review 4. F. Hafiz and A. Abdennour, "Particle Swarm Algorithm variants for the Quadratic Assignment Problems A probabilistic learning approach", Expert Systems with Applications, Elsevier, (IF: 2.24), pp. 413 431, 2016 5. F. Hafiz and A. Abdennour, "Discrete team oriented particle swarms to solve the quadratic assignment problems", IEEE Transactions on System, Man and Cybernetics: Systems (IF: 2.17), Under Review Conference Proceedings: F. Hafiz and A. Abdennour," Optimal Inertial Support from the Variable Speed Wind Turbines using Particle Swarm Optimization", 9 th IFAC Symposium on Control of Power and Energy Systems (CPES), 2015 F. M. F. Hafiz, R. Roy, R. Maurya, and S. Ghoshal; "PSO Optimized Small Signal Stability Analysis of DFIG for WECS"; Current Trends in Technology, Nirma University, Ahmadabad; 286 292; Excel India Publishers; 2008.
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