- Email: [email protected]
Structural integrity of a Doubly Fed Induction Generator (DFIG) of a wind power system (WPS)
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Structural Integrity Procedia 00 (2018) 000–000 Available online www.sciencedirect.com Available online at at www.sciencedirect.com
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Structural Integrity Procedia 00 (2018) 000–000
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Procedia Structural (2018) 221–228 Structural IntegrityIntegrity Procedia900 (2016) 000–000
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IGF Workshop “Fracture and Structural Integrity” IGF Workshop “Fracture and Structural Integrity”
Structural Structural integrity integrity of of aa Doubly Doubly Fed Fed Induction Induction Generator Generator a wind system (WPS) XV Portuguese(DFIG) Conference of on Fracture, PCFpower 2016, 10-12 February 2016, Paço de Arcos, Portugal (DFIG) of a wind power system (WPS) Mohammed Ezzahi , Mohamed Khafallah , Fatima Majidbblade of an Thermo-mechanical modeling of a high pressure turbine a,* a Mohammed Ezzahi , Mohamed Khafallah , Fatima Majid Laboratoire Energie et Systèmes Electriques (LESE), Université Hassan II de Casablanca, Ecole Nationale Supérieure d’Electricité et de airplane gas turbine engine Laboratoire Energie et Systèmes Electriques Université Hassan II de Casablanca, Ecole Nationale Supérieure d’Electricité et de Mécanique(LESE), (ENSEM), Km 7 Route El-Jadida, Casablanca, Maroc a,*
a
b
a a
Mécanique (ENSEM), et Km 7 Route El-Jadida, Casablanca, Maroc Laboratoire de contrôle et de caractérisation des matériaux des structures, Université Hassan II, Ecole Nationale Supérieure d’Electricité et b b c Laboratoire de contrôle et de caractérisation des (ENSEM), matériaux a,etKm7, des structures, Université Hassan II,MAROC Ecole Nationale Supérieure d’Electricité et de Mécanique Route El-Jadida, Casablanca, de Mécanique (ENSEM), , Km7, Route El-Jadida, Casablanca, MAROC a Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal b IDMEC, Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Abstract Portugal Abstract c CeFEMA, Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Improving the electricity production and enhancing the overall and the quality of the electrical grid are obligatory Portugal b
P. Brandão , V. Infante , A.M. Deus *
Improving the electricity production and enhancing the overall and the quality the electrical grid power are obligatory to reach nowadays clients requirements regarding the quality of energy. Thus, the of integration of green such us to reach nowadays requirements the quality energy. Thus, theface, integration of green power suchthe us solar, Wind Power clients Systems (WPS) andregarding biomass has changedofthe energy world and contributed to satisfy solar, Wind Power Systems and biomass has changed the objectives energy world face,this and contributed to satisfy the Abstract international needs of energy.(WPS) The renewable energies are strategic to lead energetic revolution. In this international of energy. renewable energiesGenerator are strategic objectives to is lead energetic revolution. Incase this work, we areneeds interested in the The Doubly Fed Induction (DFIG), which thethis most used machine in the their operation, in modern aircraftFed engine components are subjected to increasingly demanding operating conditions, work, wepower are interested themachine Doubly Induction Generator which is the most theother case ofDuring wind systems. This has many advantages such(DFIG), us efforts control over theused WPSmachine shaft andinthe especially the high pressure turbine (HPT) blades. Such conditions cause these parts to undergo different types time-dependent of wind power systems. This machine has many advantages such usreactive efforts control over the WPS shaftofand the other mechanical noise and the control of the the active and the It uses a back-to-back degradation,parts, one ofless which is creep. A model using finite element method (FEM)powers. was developed, in order to be ableinverter to predict mechanical parts, less noise and the control of the active and the reactive powers. It uses a back-to-back inverter between the rotor and the grid. The used inverter design can be optimized to reduce the power electronics components the creep behaviour of HPT blades. Flight data records (FDR) for a specific aircraft, provided by a commercial aviation between thethen rotor and to theinto grid. inverter design canThe bethree optimized to reduce the power electronics components losses and insert it theThe gridused through transformer. power control is related toInboth thetoDFIG company, were used obtain thermal and mechanical data for different flight cycles. order createand the the 3D way model losses andforthen insert into theapaper, grid transformer. The power is related both DFIGwe and the way FEM itanalysis, HPTthrough blade was the scanned, and integrity itscontrol chemical composition andthe material properties were itsneeded inverter is the controlled. In this we willscrap proceed structural analysis ofto a WPS. Indeed, proceeded data that was gathered was into the FEM model different run, firstDFIG, withwe acalled simplified its inverter The isofcontrolled. Ininthis wefed will proceed the structural integrity analysis ofwere a WPS. Indeed, proceeded a obtained. modeling the DFIG thepaper, rotating (d-q) frame. Then, weand applied thesimulations vector control of the field3D rectangular block shape, ininorder better establish the model, and with the 3D mesh obtained from the blade scrap. The aoriented modeling of theby DFIG the to rotating (d-q) frame. Then, wethen applied thereal vector control of the DFIG, called control, approximating the machine model as naturally decoupled current-field machine according tofield the overall expected behaviour in terms of displacement was observed, in particular at the trailing edge of the blade. Therefore such oriented control, by approximating the machine model asby naturally decoupled current-field machine according to the a Park transformation. results have been confirmed simulation thedata. Matlab\simulink framework. model can be useful inAll thethe goal of predicting turbine blade life, given a set of in FDR Park transformation. All the results have been confirmed by simulation in the Matlab\simulink framework. ©© 2018 The Authors. Published byby Elsevier B.V. 2016 The Authors. Published Elsevier B.V. © 2018 Published by Elsevier B.V. B.V. © 2018The TheAuthors. Authors. Published by Elsevier Peer-review under responsibility of the Gruppo Italiano Frattura (IGF) Peer-review under responsibility the Scientific Committee PCF ExCo. 2016. Peer-review under responsibility of the of Gruppo Italiano Frattura (IGF) of ExCo. Peer-review under responsibility of the Gruppo Italiano Frattura (IGF) ExCo. Keywords: Wind System; DFIG; Structural Field oriented Keywords: HighPower Pressure Turbine Blade; Creep;integrity; Finite Element Method;control. 3D Model; Simulation. Keywords: Wind Power System; DFIG; Structural integrity; Field oriented control. * Corresponding author. Tel.: +212 663 49 90 78; E-mail address: [email protected] * Corresponding author. Tel.: +212 663 49 90 78; E-mail address: [email protected]
2452-3216 © 2018 The Authors. Published by Elsevier B.V. 2452-3216 © 2018 Authors. Published Elsevier B.V. Frattura (IGF) ExCo. Peer-review underThe responsibility of theby Gruppo Italiano Peer-review underauthor. responsibility the Gruppo Italiano Frattura (IGF) ExCo. * Corresponding Tel.: +351of 218419991. E-mail address: [email protected]
2452-3216 © 2016 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the Scientific Committee of PCF 2016. 2452-3216 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Gruppo Italiano Frattura (IGF) ExCo. 10.1016/j.prostr.2018.06.042
Mohammed Ezzahi et al. / Procedia Structural Integrity 9 (2018) 221–228 Author name / Structural Integrity Procedia 00 (2018) 000–000
222 2
1. Nomenclature Ls Lr Ls Lr Ms Mr M Vds Vqs Vdr Vqr
ds . qs . dr qr .
ids iqs idr idr Ps Qs Pr Qr Pt Tem
Stator cyclic inductances Rotor cyclic inductances, Proper inductances of stator Proper inductances of rotor Mutual inductances between a stator and a rotor phases Mutual inductances between a rotor and a stator phases The maximum mutual inductance The voltage of the stator along the PARK axis ‘d’ The voltage of the stator along the PARK axis ‘q’ The voltage of the rotor along the PARK axis ‘d’ The voltage of the rotor along the PARK axis ‘q’ The magnetic field of the stator along the PARK axis ‘d’ The magnetic field of the stator along the PARK axis ‘q’ The magnetic field of the rotor along the PARK axis ‘d’ The magnetic field of the rotor along the PARK axis ‘q’ The current of the stator along the PARK axis ‘d’ The current of the stator along the PARK axis ‘q’ The current of the rotor along the PARK axis ‘d’ The current of the rotor along the PARK axis ‘q’ The active power of the stator The reactive power of the stator The active power of the rotor The reactive power of the rotor Total power of the DFIG machine Electromagnetic torque.
2. Introduction Wind energy conversion using Doubly Fed Induction Generator (DFIG) is one of the most important types of renewable energy generations.. For that, DFIG machine is considered as the most used machine in the wind power systems to guarantee the maximum stability and efficiency. Then, the structure of DFIG and the position of its inverters, rotor and grid sides, leads to the active and reactive power control Mesbahi (2013) et Burton (2001) and the grid coupling optimization by power electronic losses reduction Kling (2002) et Khil (2006). Thus, the fast development of power electronics and microelectronics has opened new issues of investigation for induction motor with vector control strategies Kadjoudj (2007) et Ba-Razzouk (1997). Furthermore, the control of DFIG is more complicated because it can operate at different ranges of speed. In fact, many strategies have been developed to control these machines by controlling their parameters such as power, current, current or torque. The most important target of such control strategies is to provide a fast dynamic response under transient conditions and robust characteristics against parameters’ fluctuation. Indeed, a Direct Power Control (DPC) method for DFIG drive to control the active and reactive powers directly without the need of the frame transformation and the current controller used in a FOC drive has been presented in the literature Jon (2009). So, both the simulation and the experimental results demonstrated the validity of the DPC algorithm with a fixed switching frequency. Moreover, a model of a 850 KW DFIG machine Belmokhtar (2011) has been tested and simulated by using a vector control. Then, the active and the reactive power to enhance the overall operation of the wind turbine system and its control has been modeled in the same work. Besides, Since1985, the direct torque control (DTC) was widely used for induction motor drives with fast dynamics.to produce very fast torque and flux control and robust performances of the generator taking into consideration the torque and the flux estimation accuracy and the drive parameters and perturbations Sorchini (2006), Vasudevan (2005) et Takahashi (1986) . In this paper, we are focusing over study over the Field-oriented control, which has been used and
Mohammed Ezzahi et al. / Procedia Structural Integrity 9 (2018) 221–228 Author name / Structural Integrity Procedia 00 (2018) 000–000
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presented as a strategy for induction motor speed’s adjustment feeding by variable frequency converter Blaschke (1972). This strategy, which is a classical one, still have more interest by developing new control algorithms and by using the Sensorless WPS. Making the control of the active and the reactive powers easy and reliable. So, the FOC models still giving good performances compared to the other methods of control. From a point of view of structural integrity, the mastering of the controls of DFIG machines and the use of Sensorless commands give rise to an enhanced running of the wind power system and optimize their maintenance. 3. Structural integrity of Wind Power systems (WPS): In order to assess the structural integrity of WPS, we have to deal with both the mechanical and the electrical parts. The figure 1 shows the different parts of a WPS:
Fig. 1. WPS elements
The failure of the electrical parts is one of the most important in wind power system. Thus, we need to optimize the controls of the DFIG machine and adopt a Sensorless control strategy of the DFIG machine in order to guarantee a less maintenance operation and run the WPs for a long time, figure 2. Steady‐state model
Slip calculation Torque Open loop estimators
Sensorless systems
Transitional model
MRAS
Flow induced emf Artificial Intelligence Complete order Conventional Reduced Order
Observers HF Injection Appearance of the machine
Kalman
Harmonics notches
Fig. 2. The differents DFIG sensorless systems
Extended Kalman
Mohammed Ezzahi et al. / Procedia Structural Integrity 9 (2018) 221–228 Author name / Structural Integrity Procedia 00 (2018) 000–000
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4. Modeling of the Doubly Fed Induction Generator (DFIG) in the (d-q) frame: In this paper, we will proceed to modeling the DFIG in the rotating (d-q) frame Salloum (2007). Therefore, the equations in the (d-q) frame of PARK transformation are given by many equations expressing the current and the magnetic field. For the stator, we find the equations blow:
Vds Rs .ids
ds. sqs. t
(1)
Vqs Rs .ids
qs. sds. t
(2)
ds Ls .ids M .idr
(3)
qs Ls .iqs M .iqr
(4)
For the rotor side, we find the equations below:
Vdr Rr .idr
dr . rqr . t
(5)
Vqr Rr .idr
qr . rdr . t
(6)
dr Lr .idr M .ids
(7)
qr Lr .iqr M .iqs
(8)
The stator and the rotor parameters are expressed according to each other:
r s p.
(9)
Ls lr M s
(10)
Lr l s M r
(11)
From all the equation above, we express the active and the reactive powers:
Ps Vds .ids Vqs .iqs
(12)
Qs Vqs .ids Vd s .iqs
(13)
Pr Vdr .idr Vqr .iqr
(14)
Qr Vqr .idr Vdr .iqr
(15)
5. Field Oriented Control (FOC) Field oriented control (FOC) or vector control is commonly used in DFIG controls due to its ability of controlling the motor speed more efficiently, and due to its lower cost of building. FOC controls separately the active and the
Mohammed Ezzahi et al. / Procedia Structural Integrity 9 (2018) 221–228 Author name / Structural Integrity Procedia 00 (2018) 000–000
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reactive power of the generator. Indeed, there are FOC based on current oriented control and the one based on the stator flux oriented control. The second one is widely used in the DFIG control designs in which the q-axis current component is used for active power control and the d-axis component is used for reactive power control Wei Qiao(2008) et Yongchang Zhang (2011. While for the first one, we are reversing the axis purpose Shuhui Li (2009), the d-axis component is used for active power control and the q-axis current component is used for reactive power control. In this paper, we apply the vector control of the DFIG called field oriented control by approximating the machine model as naturally decoupled current-field machine. However, employing an appropriate choice of reference frame upon which control of the field-oriented quantities allows an independent control of the electromagnetic torque known as FOC. The controlled back-to-back converter of a DFIG is typically connected through slip rings to the rotor windings, and independent torque control is usually achieved through control of the rotor current. The model of the FOC can be developed for the DFIG by taking into consideration that the rotor field is oriented according the d axis, fixe rotor field and neglecting the stator resistance. We obtain in rotating (d-q) frame, the total transmitted power as mentioned by the figure 3:
Pt Ps Pr g 1.Vs . Qt Qs Qr
M iqr Ls
Vs .s M g 1.Vs . idr Vqs .iqs Ls Ls
DFIG
Fig. 3. DFIG control scheme
The representation of the vector control is given in the Figure 4.
Fig. 4. Rotor flux orientation
The electromagnetic torque of the DFIG based on the fluxes and stator currents is given by:
(16)
(17)
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Mohammed et al. / Procedia Structural Integrity 9 (2018) 221–228 Author name / Ezzahi Structural Integrity Procedia 00 (2018) 000–000
Tem ds .iqs _ qs .ids p.
M s .iqr Ls
(18)
From the equation (18) above, we notice that we have a coupling between currents and fluxes. In order to make the FOC control of the machine possible we adopt the assumptions: We consider the current and frequency as constants; We use the rotating d-q frame; We consider that the rotor flux is oriented according to the d axis (dr=r and qr=0); We neglect the stator resistance (Vds=0 and Vqs=s.s); Considering commonly used DFIG machines of medium and high powers. 6. Experimental and simulation results As a result of the simulation in Matlab\simulink for both the DFIG modelling through the field oriented control, we obtain in the sub-synchronous mode (slip <0):
Fig. 5. Rotor magnetic field evolution in sub-synchronous mode
Fig. 6. Measured and simulated speed in sub-synchronous mode In the hyper-synchronous mode (slip >0), we obtain:
Fig. 7. Rotor magnetic field evolution in hyper-synchronous mode
Mohammed Ezzahi et al. / Procedia Structural Integrity 9 (2018) 221–228 Author name / Structural Integrity Procedia 00 (2018) 000–000
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Fig. 8. Measured and simulated speed in hyper-synchronous mode By using the sensorless systems and specially the extended Kalaman filter (EKF) we were able to estimate exactly the speed, the magnetic field, the position and the torque by adopting a decoupled modeling of the magnetic field and the torque as shown above. Thes estimations allowed us to ensure a complete integrity of the wind power system by reducing the maintenance concerns related to the sensors.
Fig. 9. (a) Estimated (simulated) and measured speed, (b) estimated rotor magnetic field, (c) estimated position and (d) estimated torque.
7. Conclusion Standard field oriented control (FOC) schemes used to command wind turbine-driven DFIGs uses regulators with cascaded current and power loops, which require the use of an incremental encoder or Sensorless WPS. Although stator-side active and reactive powers can be independently governed by adopting those control schemes, the system transient performance degrades as the actual values of the DFIG resistances and inductances deviate from those based on which the control system tuning was carried out during the early stage of installation. In addition, the optimum
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power curve tracking achievable proportional-integral -based control schemes shows a considerable need for improvement. Even if feedforward decoupling control terms are traditionally incorporated to enhance the closed-loop DFIG dynamic response, they are extremely dependent on DFIG parameters. Indeed, we showed the simulated values of rotor flux and speed have been modelled with a big accuracy. All obtained results are essential to maximise profits and maintain life cycle costs of wind power systems. They can contribute to reduce the complexity of WPS that arises for several reasons, including rapid technology development, complex supply chains and constrained infrastructure, remote locations and, more generally, lack of detailed failure data. They can also help to establish asset management to effectively manage corporate assets for a maximum added value, profitability and returns while safeguarding personnel, the community and the environment. References Ba-Razzouk, A., Cheriti, A., Olivier, G., Sicard, P. 1997. Field-oriented Control of Induction Motors using Neural-network Decouplers, IEEE Transaction on Power Electronics, 12(4), 752 – 763. Belmokhtar, K., Doumbia, M. L., and Agbossou, K. 2011. Modelling and Power Control of Wind Turbine Driving DFIG connected to the Utility Grid. In Proc. of the International Conference on Renewable energies and Power Quality, ICREPQ, 1-6. Blaschke, F. 1972. The Principle of Field Orientation as Applied to the New Transvector Closed Loop Control Systems for Rotating Machines, Siemens Review, 39(5), 217 – 220. Burton, T., Sharpe, D., Jenkins, N. and Bossanyi, E. 2001. Wind Energy Handboo. John Wiley&Sons, Ltd. Jou, S. T., Lee, S. B., Park, Y. B., and Lee, K. B. 2009. Direct power control of a DFIG in wind turbines to improve dynamic responses. Journal of power electronics, 9(5), 781-790. Kadjoudj, M., Golea, N., Benbouzid M.E. 2007. Fuzzy Rule-based Model Reference Adaptive Control for PMSM Drives, Serbian Journal of Electrical Engineering, 4(1), 13 – 22. Khil, S. K. E. 2006. Commande vectorielle d’une machine asynchrone doublement alimentée (MADA): Optimisation des pertes dans les convertisseurs: reconfiguration de la commande, theses.fr. Kling W. L. and. Slootweg, J. G, 2002. Wind Turbines as Power Plants. Proceeding of the IEEE/Cigré workshop, Oslo, Norway. Li, S., Challoo R. and Nemmers, M. J. 2009. Comparative Study of DFIG Power Control Using Stator-Voltage and Stator-Flux Oriented Frames, IEEE Power & Energy Society General Meeting, 1-8. Mesbahi, A. 2013. Contribution aux techniques d’estimation et d’observation appliquées aux machines asynchrones et synchrones, PhD thesis, ENSEM. Qiao, W., Zhou, W., Aller, J. M. and Harley, R.G. 2008. Wind Speed Estimation Based Sensorless Output Maximization Control for a Wind Turbine Driving a DFIG”, IEEE Transactions on Power Electronics, 23(3), 1156-1169. Salloum, G. 2007. Machine asynchrone à double alimentation. Institut national polytechnique de Toulouse, PhD thesis. Sorchini, Z., Krein, P. 2006. Formal Derivation of Direct Torque Control for Induction Machines, IEEE Transactions on Power Electronics, 21(5), 1428 – 1436. Takahashi, I., Noguchi, T. 1986. A New Quick-response and High Efficiency Control Strategy of an Induction Machine, IEEE Transaction on Industry Application, 22(5), 820 – 827. Vasudevan, M., Arumugam, R., Paramasivam, S., 2005. High-performance Adaptive Intelligent Direct Torque Control Schemes for Induction Motor Drives, Serbian Journal of Electrical Engineering, 2(1), 93 – 116. Zhang, Y., Li, Z., Hu, J., Xu, W. and Zhu, J. 2011. A Cascaded Brushless Doubly Fed Induction Generator for Wind Energy Applications Based on Direct Power Control, 2011 International Conference on Electrical Machines and Systems, 1-6.
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Structural Integrity Procedia 00 (2018) 000–000 Available online www.sciencedirect.com Available online at at www.sciencedirect.com
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Structural Integrity Procedia 00 (2018) 000–000
ScienceDirect ScienceDirect
Procedia Structural (2018) 221–228 Structural IntegrityIntegrity Procedia900 (2016) 000–000
www.elsevier.com/locate/procedia
IGF Workshop “Fracture and Structural Integrity” IGF Workshop “Fracture and Structural Integrity”
Structural Structural integrity integrity of of aa Doubly Doubly Fed Fed Induction Induction Generator Generator a wind system (WPS) XV Portuguese(DFIG) Conference of on Fracture, PCFpower 2016, 10-12 February 2016, Paço de Arcos, Portugal (DFIG) of a wind power system (WPS) Mohammed Ezzahi , Mohamed Khafallah , Fatima Majidbblade of an Thermo-mechanical modeling of a high pressure turbine a,* a Mohammed Ezzahi , Mohamed Khafallah , Fatima Majid Laboratoire Energie et Systèmes Electriques (LESE), Université Hassan II de Casablanca, Ecole Nationale Supérieure d’Electricité et de airplane gas turbine engine Laboratoire Energie et Systèmes Electriques Université Hassan II de Casablanca, Ecole Nationale Supérieure d’Electricité et de Mécanique(LESE), (ENSEM), Km 7 Route El-Jadida, Casablanca, Maroc a,*
a
b
a a
Mécanique (ENSEM), et Km 7 Route El-Jadida, Casablanca, Maroc Laboratoire de contrôle et de caractérisation des matériaux des structures, Université Hassan II, Ecole Nationale Supérieure d’Electricité et b b c Laboratoire de contrôle et de caractérisation des (ENSEM), matériaux a,etKm7, des structures, Université Hassan II,MAROC Ecole Nationale Supérieure d’Electricité et de Mécanique Route El-Jadida, Casablanca, de Mécanique (ENSEM), , Km7, Route El-Jadida, Casablanca, MAROC a Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal b IDMEC, Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Abstract Portugal Abstract c CeFEMA, Department of Mechanical Engineering, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Improving the electricity production and enhancing the overall and the quality of the electrical grid are obligatory Portugal b
P. Brandão , V. Infante , A.M. Deus *
Improving the electricity production and enhancing the overall and the quality the electrical grid power are obligatory to reach nowadays clients requirements regarding the quality of energy. Thus, the of integration of green such us to reach nowadays requirements the quality energy. Thus, theface, integration of green power suchthe us solar, Wind Power clients Systems (WPS) andregarding biomass has changedofthe energy world and contributed to satisfy solar, Wind Power Systems and biomass has changed the objectives energy world face,this and contributed to satisfy the Abstract international needs of energy.(WPS) The renewable energies are strategic to lead energetic revolution. In this international of energy. renewable energiesGenerator are strategic objectives to is lead energetic revolution. Incase this work, we areneeds interested in the The Doubly Fed Induction (DFIG), which thethis most used machine in the their operation, in modern aircraftFed engine components are subjected to increasingly demanding operating conditions, work, wepower are interested themachine Doubly Induction Generator which is the most theother case ofDuring wind systems. This has many advantages such(DFIG), us efforts control over theused WPSmachine shaft andinthe especially the high pressure turbine (HPT) blades. Such conditions cause these parts to undergo different types time-dependent of wind power systems. This machine has many advantages such usreactive efforts control over the WPS shaftofand the other mechanical noise and the control of the the active and the It uses a back-to-back degradation,parts, one ofless which is creep. A model using finite element method (FEM)powers. was developed, in order to be ableinverter to predict mechanical parts, less noise and the control of the active and the reactive powers. It uses a back-to-back inverter between the rotor and the grid. The used inverter design can be optimized to reduce the power electronics components the creep behaviour of HPT blades. Flight data records (FDR) for a specific aircraft, provided by a commercial aviation between thethen rotor and to theinto grid. inverter design canThe bethree optimized to reduce the power electronics components losses and insert it theThe gridused through transformer. power control is related toInboth thetoDFIG company, were used obtain thermal and mechanical data for different flight cycles. order createand the the 3D way model losses andforthen insert into theapaper, grid transformer. The power is related both DFIGwe and the way FEM itanalysis, HPTthrough blade was the scanned, and integrity itscontrol chemical composition andthe material properties were itsneeded inverter is the controlled. In this we willscrap proceed structural analysis ofto a WPS. Indeed, proceeded data that was gathered was into the FEM model different run, firstDFIG, withwe acalled simplified its inverter The isofcontrolled. Ininthis wefed will proceed the structural integrity analysis ofwere a WPS. Indeed, proceeded a obtained. modeling the DFIG thepaper, rotating (d-q) frame. Then, weand applied thesimulations vector control of the field3D rectangular block shape, ininorder better establish the model, and with the 3D mesh obtained from the blade scrap. The aoriented modeling of theby DFIG the to rotating (d-q) frame. Then, wethen applied thereal vector control of the DFIG, called control, approximating the machine model as naturally decoupled current-field machine according tofield the overall expected behaviour in terms of displacement was observed, in particular at the trailing edge of the blade. Therefore such oriented control, by approximating the machine model asby naturally decoupled current-field machine according to the a Park transformation. results have been confirmed simulation thedata. Matlab\simulink framework. model can be useful inAll thethe goal of predicting turbine blade life, given a set of in FDR Park transformation. All the results have been confirmed by simulation in the Matlab\simulink framework. ©© 2018 The Authors. Published byby Elsevier B.V. 2016 The Authors. Published Elsevier B.V. © 2018 Published by Elsevier B.V. B.V. © 2018The TheAuthors. Authors. Published by Elsevier Peer-review under responsibility of the Gruppo Italiano Frattura (IGF) Peer-review under responsibility the Scientific Committee PCF ExCo. 2016. Peer-review under responsibility of the of Gruppo Italiano Frattura (IGF) of ExCo. Peer-review under responsibility of the Gruppo Italiano Frattura (IGF) ExCo. Keywords: Wind System; DFIG; Structural Field oriented Keywords: HighPower Pressure Turbine Blade; Creep;integrity; Finite Element Method;control. 3D Model; Simulation. Keywords: Wind Power System; DFIG; Structural integrity; Field oriented control. * Corresponding author. Tel.: +212 663 49 90 78; E-mail address: [email protected] * Corresponding author. Tel.: +212 663 49 90 78; E-mail address: [email protected]
2452-3216 © 2018 The Authors. Published by Elsevier B.V. 2452-3216 © 2018 Authors. Published Elsevier B.V. Frattura (IGF) ExCo. Peer-review underThe responsibility of theby Gruppo Italiano Peer-review underauthor. responsibility the Gruppo Italiano Frattura (IGF) ExCo. * Corresponding Tel.: +351of 218419991. E-mail address: [email protected]
2452-3216 © 2016 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the Scientific Committee of PCF 2016. 2452-3216 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Gruppo Italiano Frattura (IGF) ExCo. 10.1016/j.prostr.2018.06.042
Mohammed Ezzahi et al. / Procedia Structural Integrity 9 (2018) 221–228 Author name / Structural Integrity Procedia 00 (2018) 000–000
222 2
1. Nomenclature Ls Lr Ls Lr Ms Mr M Vds Vqs Vdr Vqr
ds . qs . dr qr .
ids iqs idr idr Ps Qs Pr Qr Pt Tem
Stator cyclic inductances Rotor cyclic inductances, Proper inductances of stator Proper inductances of rotor Mutual inductances between a stator and a rotor phases Mutual inductances between a rotor and a stator phases The maximum mutual inductance The voltage of the stator along the PARK axis ‘d’ The voltage of the stator along the PARK axis ‘q’ The voltage of the rotor along the PARK axis ‘d’ The voltage of the rotor along the PARK axis ‘q’ The magnetic field of the stator along the PARK axis ‘d’ The magnetic field of the stator along the PARK axis ‘q’ The magnetic field of the rotor along the PARK axis ‘d’ The magnetic field of the rotor along the PARK axis ‘q’ The current of the stator along the PARK axis ‘d’ The current of the stator along the PARK axis ‘q’ The current of the rotor along the PARK axis ‘d’ The current of the rotor along the PARK axis ‘q’ The active power of the stator The reactive power of the stator The active power of the rotor The reactive power of the rotor Total power of the DFIG machine Electromagnetic torque.
2. Introduction Wind energy conversion using Doubly Fed Induction Generator (DFIG) is one of the most important types of renewable energy generations.. For that, DFIG machine is considered as the most used machine in the wind power systems to guarantee the maximum stability and efficiency. Then, the structure of DFIG and the position of its inverters, rotor and grid sides, leads to the active and reactive power control Mesbahi (2013) et Burton (2001) and the grid coupling optimization by power electronic losses reduction Kling (2002) et Khil (2006). Thus, the fast development of power electronics and microelectronics has opened new issues of investigation for induction motor with vector control strategies Kadjoudj (2007) et Ba-Razzouk (1997). Furthermore, the control of DFIG is more complicated because it can operate at different ranges of speed. In fact, many strategies have been developed to control these machines by controlling their parameters such as power, current, current or torque. The most important target of such control strategies is to provide a fast dynamic response under transient conditions and robust characteristics against parameters’ fluctuation. Indeed, a Direct Power Control (DPC) method for DFIG drive to control the active and reactive powers directly without the need of the frame transformation and the current controller used in a FOC drive has been presented in the literature Jon (2009). So, both the simulation and the experimental results demonstrated the validity of the DPC algorithm with a fixed switching frequency. Moreover, a model of a 850 KW DFIG machine Belmokhtar (2011) has been tested and simulated by using a vector control. Then, the active and the reactive power to enhance the overall operation of the wind turbine system and its control has been modeled in the same work. Besides, Since1985, the direct torque control (DTC) was widely used for induction motor drives with fast dynamics.to produce very fast torque and flux control and robust performances of the generator taking into consideration the torque and the flux estimation accuracy and the drive parameters and perturbations Sorchini (2006), Vasudevan (2005) et Takahashi (1986) . In this paper, we are focusing over study over the Field-oriented control, which has been used and
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presented as a strategy for induction motor speed’s adjustment feeding by variable frequency converter Blaschke (1972). This strategy, which is a classical one, still have more interest by developing new control algorithms and by using the Sensorless WPS. Making the control of the active and the reactive powers easy and reliable. So, the FOC models still giving good performances compared to the other methods of control. From a point of view of structural integrity, the mastering of the controls of DFIG machines and the use of Sensorless commands give rise to an enhanced running of the wind power system and optimize their maintenance. 3. Structural integrity of Wind Power systems (WPS): In order to assess the structural integrity of WPS, we have to deal with both the mechanical and the electrical parts. The figure 1 shows the different parts of a WPS:
Fig. 1. WPS elements
The failure of the electrical parts is one of the most important in wind power system. Thus, we need to optimize the controls of the DFIG machine and adopt a Sensorless control strategy of the DFIG machine in order to guarantee a less maintenance operation and run the WPs for a long time, figure 2. Steady‐state model
Slip calculation Torque Open loop estimators
Sensorless systems
Transitional model
MRAS
Flow induced emf Artificial Intelligence Complete order Conventional Reduced Order
Observers HF Injection Appearance of the machine
Kalman
Harmonics notches
Fig. 2. The differents DFIG sensorless systems
Extended Kalman
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4. Modeling of the Doubly Fed Induction Generator (DFIG) in the (d-q) frame: In this paper, we will proceed to modeling the DFIG in the rotating (d-q) frame Salloum (2007). Therefore, the equations in the (d-q) frame of PARK transformation are given by many equations expressing the current and the magnetic field. For the stator, we find the equations blow:
Vds Rs .ids
ds. sqs. t
(1)
Vqs Rs .ids
qs. sds. t
(2)
ds Ls .ids M .idr
(3)
qs Ls .iqs M .iqr
(4)
For the rotor side, we find the equations below:
Vdr Rr .idr
dr . rqr . t
(5)
Vqr Rr .idr
qr . rdr . t
(6)
dr Lr .idr M .ids
(7)
qr Lr .iqr M .iqs
(8)
The stator and the rotor parameters are expressed according to each other:
r s p.
(9)
Ls lr M s
(10)
Lr l s M r
(11)
From all the equation above, we express the active and the reactive powers:
Ps Vds .ids Vqs .iqs
(12)
Qs Vqs .ids Vd s .iqs
(13)
Pr Vdr .idr Vqr .iqr
(14)
Qr Vqr .idr Vdr .iqr
(15)
5. Field Oriented Control (FOC) Field oriented control (FOC) or vector control is commonly used in DFIG controls due to its ability of controlling the motor speed more efficiently, and due to its lower cost of building. FOC controls separately the active and the
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reactive power of the generator. Indeed, there are FOC based on current oriented control and the one based on the stator flux oriented control. The second one is widely used in the DFIG control designs in which the q-axis current component is used for active power control and the d-axis component is used for reactive power control Wei Qiao(2008) et Yongchang Zhang (2011. While for the first one, we are reversing the axis purpose Shuhui Li (2009), the d-axis component is used for active power control and the q-axis current component is used for reactive power control. In this paper, we apply the vector control of the DFIG called field oriented control by approximating the machine model as naturally decoupled current-field machine. However, employing an appropriate choice of reference frame upon which control of the field-oriented quantities allows an independent control of the electromagnetic torque known as FOC. The controlled back-to-back converter of a DFIG is typically connected through slip rings to the rotor windings, and independent torque control is usually achieved through control of the rotor current. The model of the FOC can be developed for the DFIG by taking into consideration that the rotor field is oriented according the d axis, fixe rotor field and neglecting the stator resistance. We obtain in rotating (d-q) frame, the total transmitted power as mentioned by the figure 3:
Pt Ps Pr g 1.Vs . Qt Qs Qr
M iqr Ls
Vs .s M g 1.Vs . idr Vqs .iqs Ls Ls
DFIG
Fig. 3. DFIG control scheme
The representation of the vector control is given in the Figure 4.
Fig. 4. Rotor flux orientation
The electromagnetic torque of the DFIG based on the fluxes and stator currents is given by:
(16)
(17)
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Tem ds .iqs _ qs .ids p.
M s .iqr Ls
(18)
From the equation (18) above, we notice that we have a coupling between currents and fluxes. In order to make the FOC control of the machine possible we adopt the assumptions: We consider the current and frequency as constants; We use the rotating d-q frame; We consider that the rotor flux is oriented according to the d axis (dr=r and qr=0); We neglect the stator resistance (Vds=0 and Vqs=s.s); Considering commonly used DFIG machines of medium and high powers. 6. Experimental and simulation results As a result of the simulation in Matlab\simulink for both the DFIG modelling through the field oriented control, we obtain in the sub-synchronous mode (slip <0):
Fig. 5. Rotor magnetic field evolution in sub-synchronous mode
Fig. 6. Measured and simulated speed in sub-synchronous mode In the hyper-synchronous mode (slip >0), we obtain:
Fig. 7. Rotor magnetic field evolution in hyper-synchronous mode
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Fig. 8. Measured and simulated speed in hyper-synchronous mode By using the sensorless systems and specially the extended Kalaman filter (EKF) we were able to estimate exactly the speed, the magnetic field, the position and the torque by adopting a decoupled modeling of the magnetic field and the torque as shown above. Thes estimations allowed us to ensure a complete integrity of the wind power system by reducing the maintenance concerns related to the sensors.
Fig. 9. (a) Estimated (simulated) and measured speed, (b) estimated rotor magnetic field, (c) estimated position and (d) estimated torque.
7. Conclusion Standard field oriented control (FOC) schemes used to command wind turbine-driven DFIGs uses regulators with cascaded current and power loops, which require the use of an incremental encoder or Sensorless WPS. Although stator-side active and reactive powers can be independently governed by adopting those control schemes, the system transient performance degrades as the actual values of the DFIG resistances and inductances deviate from those based on which the control system tuning was carried out during the early stage of installation. In addition, the optimum
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power curve tracking achievable proportional-integral -based control schemes shows a considerable need for improvement. Even if feedforward decoupling control terms are traditionally incorporated to enhance the closed-loop DFIG dynamic response, they are extremely dependent on DFIG parameters. Indeed, we showed the simulated values of rotor flux and speed have been modelled with a big accuracy. All obtained results are essential to maximise profits and maintain life cycle costs of wind power systems. They can contribute to reduce the complexity of WPS that arises for several reasons, including rapid technology development, complex supply chains and constrained infrastructure, remote locations and, more generally, lack of detailed failure data. They can also help to establish asset management to effectively manage corporate assets for a maximum added value, profitability and returns while safeguarding personnel, the community and the environment. References Ba-Razzouk, A., Cheriti, A., Olivier, G., Sicard, P. 1997. Field-oriented Control of Induction Motors using Neural-network Decouplers, IEEE Transaction on Power Electronics, 12(4), 752 – 763. Belmokhtar, K., Doumbia, M. L., and Agbossou, K. 2011. Modelling and Power Control of Wind Turbine Driving DFIG connected to the Utility Grid. In Proc. of the International Conference on Renewable energies and Power Quality, ICREPQ, 1-6. Blaschke, F. 1972. The Principle of Field Orientation as Applied to the New Transvector Closed Loop Control Systems for Rotating Machines, Siemens Review, 39(5), 217 – 220. Burton, T., Sharpe, D., Jenkins, N. and Bossanyi, E. 2001. Wind Energy Handboo. John Wiley&Sons, Ltd. Jou, S. T., Lee, S. B., Park, Y. B., and Lee, K. B. 2009. Direct power control of a DFIG in wind turbines to improve dynamic responses. Journal of power electronics, 9(5), 781-790. Kadjoudj, M., Golea, N., Benbouzid M.E. 2007. Fuzzy Rule-based Model Reference Adaptive Control for PMSM Drives, Serbian Journal of Electrical Engineering, 4(1), 13 – 22. Khil, S. K. E. 2006. Commande vectorielle d’une machine asynchrone doublement alimentée (MADA): Optimisation des pertes dans les convertisseurs: reconfiguration de la commande, theses.fr. Kling W. L. and. Slootweg, J. G, 2002. Wind Turbines as Power Plants. Proceeding of the IEEE/Cigré workshop, Oslo, Norway. Li, S., Challoo R. and Nemmers, M. J. 2009. Comparative Study of DFIG Power Control Using Stator-Voltage and Stator-Flux Oriented Frames, IEEE Power & Energy Society General Meeting, 1-8. Mesbahi, A. 2013. Contribution aux techniques d’estimation et d’observation appliquées aux machines asynchrones et synchrones, PhD thesis, ENSEM. Qiao, W., Zhou, W., Aller, J. M. and Harley, R.G. 2008. Wind Speed Estimation Based Sensorless Output Maximization Control for a Wind Turbine Driving a DFIG”, IEEE Transactions on Power Electronics, 23(3), 1156-1169. Salloum, G. 2007. Machine asynchrone à double alimentation. Institut national polytechnique de Toulouse, PhD thesis. Sorchini, Z., Krein, P. 2006. Formal Derivation of Direct Torque Control for Induction Machines, IEEE Transactions on Power Electronics, 21(5), 1428 – 1436. Takahashi, I., Noguchi, T. 1986. A New Quick-response and High Efficiency Control Strategy of an Induction Machine, IEEE Transaction on Industry Application, 22(5), 820 – 827. Vasudevan, M., Arumugam, R., Paramasivam, S., 2005. High-performance Adaptive Intelligent Direct Torque Control Schemes for Induction Motor Drives, Serbian Journal of Electrical Engineering, 2(1), 93 – 116. Zhang, Y., Li, Z., Hu, J., Xu, W. and Zhu, J. 2011. A Cascaded Brushless Doubly Fed Induction Generator for Wind Energy Applications Based on Direct Power Control, 2011 International Conference on Electrical Machines and Systems, 1-6.