A New Power Conversion System for Megawatt PMSG ... - IEEE Xplore

IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS, VOL. 2, NO. 1, MARCH 2014

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A New Power Conversion System for Megawatt PMSG Wind Turbines Using Four-Level Converters and a Simple Control Scheme Based on Two-Step Model Predictive Strategy—Part I: Modeling and Theoretical Analysis Venkata Yaramasu, Student Member, IEEE, Bin Wu, Fellow, IEEE, Marco Rivera, Member, IEEE, and Jose Rodriguez, Fellow, IEEE

Abstract— A new power conversion system is explored in this paper aiming wind turbines rated at the megawatt level. The proposed configuration consists of a medium-voltage, permanent magnet synchronous generator connected to a low-cost threephase diode bridge rectifier, a dc–dc four-level boost converter as the intermediate stage, and a four-level diode-clamped inverter on the grid-side. The dc-link capacitor voltages are balanced by the boost converter, and thus the control complexity for the grid-tied inverter is greatly simplified. To control the boost converter and grid-tied inverter, a simple method based on a two-step model predictive strategy is presented. In the first part of this paper, the continuous- and discrete-time modeling of the proposed power conversion system is analyzed. The control objectives such as maximum power point tracking, dc-link capacitor voltages balancing, regulation of net dc-bus voltage, reactive power generation, lower switching frequency operation, and common-mode voltage minimization are considered in the design of controller. Index Terms— AC–dc power conversion, boost converter, common-mode voltage (CMV), current control, dc–ac power conversion, dc–dc power conversion, dc-link capacitor voltages balancing, digital control, direct-driven, four-level boost, gridconnected, maximum power point tracking, medium voltage Manuscript received June 3, 2013; revised October 25, 2013; accepted November 25, 2013. Date of publication December 12, 2013; date of current version January 29, 2014. This work was supported in part by the Natural Sciences and Engineering Research Council of Canada through Wind Energy Strategic Network Project 3.1, in part by the Fondecyt Initiation into Research under Grant 11121492, in part by CONICYT PCCI 12048 Project, in part by the Universidad Técnica Federico Santa María, and in part by the NPRP under Grant 4-077-2-028 through the Qatar National Research Fund. Recommended for publication by Associate Editor Wenzhong Gao. V. Yaramasu and B. Wu are with the Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada (e-mail: [email protected]; [email protected]). M. Rivera is with the Department of Industrial Technologies, Universidad de Talca, Curico 3460000, Chile (e-mail: [email protected]). J. Rodriguez is with the Department of Electronics Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JESTPE.2013.2294920

(MV), megawatt-level, multilevel converter, permanent magnet synchronous machine, power conversion, predictive control, renewable energy, state-space model, wind energy.

I. I NTRODUCTION

T

HE AGE of multi-megawatt (MW) wind turbines has arrived and currently 7.5 MW units are available in the market [1], [2]. The future generation of turbines is anticipated to be in the range of 10–15 MW. At these power levels, the use of medium-voltage (MV) technology is a better suited, efficient, economical, and promising approach [1]–[8]. Many MV power conversion systems are reported in [3], [6], and [9]–[13] for permanent magnet synchronous generator (PMSG)-based wind turbines. The commercial solutions based on back-to-back (BTB) connected neutral-point-clamped (NPC) converters [14], [15] are already available in the market by ABB (PCS6000) and Converteam (MV7000). The power flow in wind turbines is unidirectional, i.e., from the generator to the grid. Moreover, the PMSG does not require a magnetizing current, unlike the squirrel cage induction generator [3]. Having this freedom (which is an advantage), an uncontrolled diode rectifier can be used for generator-side power conversion [16], [17]. This helps reduce cost and complexity compared with active front-end rectifiers. The use of passive front-end is also commercialized at the megawatt-level and low-voltage (LV) ( 0, the switching frequency reduction can be obtained. Therefore, the optimization of weighting factor λswc, f can start from 0 and increase to a higher value. All these control objectives for the FLBC are merged into a cost function as g f (k) = gtrack, f (k) + gbal, f (k) + gswc, f (k).

(27)

The control algorithm for the digital implementation twostep prediction for the FLBC is shown in Fig. 7(a). The algorithm is initialized by setting the switching state number i to 0 and optimal g value to ∞, and then the algorithm enters the loop. The measured quantities and 5 switching states are used in the prediction of (k + 1) instant variables. The predicted variables at (k + 1) instant and the extrapolated quantities are used in the prediction of (k + 2) variables. It is important to note that the number of predictions at (k + 1) and (k +2) instants are 5 only. The cost function minimization is based on the (k + 2) variables only. The switching state, which produces minimal value of gop , is chosen and applied to the FLBC gating terminals directly. The current regulators and modulation are eliminated with the proposed approach. B. Control System for Four-Level Inverter The FLDCI control system is shown in the Fig. 6(c). The control objectives for the FLDCI include regulation of grid active and reactive powers. The grid active and reactive powers can be expressed as [4], [8] 3 v dg i dg + v qg i qg 2 3 v qg i dg − v dg i qg . Qg = 2 Pg =

(28)

For grid-voltage orientation, the d-axis of the SRF is aligned with the grid voltage vector and thus v qg = 0. With this, the active and reactive power expressions in (28) can be simplified as ⎫ 3 ⎬ Pg = + v dg i dg ⎪ 2 for v qg = 0. (29) 3 ⎪ ⎭ Q g = − v dg i qg 2

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Fig. 6. Proposed model predictive control scheme for four-level converters based PMSG WECS. (a) Block diagram of complete control system with control objectives and measurements. (b) Control system for four-level boost converter. (c) Control system for four-level diode-clamped inverter.

From (29), it can be observed that the active and reactive powers fed to the grid can be regulated by controlling the d and q-axis currents, respectively. Through the regulation of net dcbus voltage by a PI controller, the reference d-axis current is generated. The reference q-axis current is obtained according

to (29). This is demonstrated as follows: ∗ ∗ (k) = K p + K i /S v dc (k) − v dc (k) i dg Q ∗g (k) ∗ i qg (k) = −1.5 v dg (k)

(30)

YARAMASU et al.: NEW POWER CONVERSION SYSTEM FOR MEGAWATT PMSG WIND TURBINES—PART I

Fig. 7.

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Proposed two-step predictive control algorithm for (a) FLBC and (b) FLDCI.

∗ is net dc-bus voltage reference, and for grid-tied where v dc applications this value is constant and usually set to 3.062 times grid phase voltage [4]. The Q ∗g is the reference reactive power that needs to be provided by a wind turbine to support the grid voltage. The Q ∗g is zero for unity power factor, negative for leading power factor and positive for lagging ∗ and i ∗ power factor. It should be noted that the generation i dg qg is similar to the classical voltage oriented control [4]. The above two control objectives can be met by forcing the grid currents to track to their references. This is defined as 2 ∗ (k + 2) − i dg (k + 2) gtrack,i (k) = i dg 2 ∗ + i qg (k + 2) − i qg (k + 2) (31) ∗ (k i dg

∗ (k + 2) i qg

where + 2) and are the extrapolated reference currents. The two-step prediction for the grid currents are

obtained according to (18). Since the reference tracking of grid currents is the primary objective, the corresponding weighting factor is one, as shown in (31). The switching frequency reduction objective is expressed as | Sxj (k) − Sxj,op(k) | (32) gswc,i (k) = λswc,i ∗ x=1,2,3 j =a,b,c

where λswc,i is a weighting factor. Sxj,op (k) is the optimal FLDCI switching signal in the previous sampling instant. The explanation given earlier for the selection of λswc, f value also applies to the λswc,i . The CMV can be minimized by penalizing the following cost function: gcmv,i (k) = λcmv,i ∗ | v cm (k) |

(33)

where λcmv,i is weighting factor for CMV minimization. The CMV minimization is the secondary control objective, thus,

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the selection of λcmv,i value can start from 0 and progress to higher values. The final cost function for the FLDCI is defined as gi (k) = gtrack,i (k) + gswc,i (k) + gcmv,i (k).

(34)

The control algorithm for the FLDCI is shown in Fig. 7(b) and it is similar to the FLBC algorithm in terms of implementation. During each iteration, the future behavior of the control variables are predicted using the 64 switching states. The switching state (among 64), which minimizes the cost function gi (k), is chosen and applied to the FLDCI. The linear regulators (PI) are eliminated in the internal current control loops and there is no need to design the pulse width or space vector modulation. V. C ONCLUSION The major contributions of this paper are summarized as follows. 1) A simple, low cost and promising MV power conversion system consisting of diode rectifier, FLBC, and FLDCI is proposed for megawatt-level PMSG wind turbines. The proposed topology combines the advantages of low cost passive front-end and efficient multilevel operation. 2) The grid-tied inverter need not to balance the dc-link capacitor voltages, and this facilitates a simplified control system for the inverter. 3) The continuous- and discrete-time modeling of the proposed power conversion is presented. The control objectives such as MPPT, dc-link capacitor voltages balancing, regulation of net dc-bus voltage, reactive power generation, lower switching frequency operation, and CMV minimization are modeled in terms of switching signals of the proposed power electronic converters. The proposed approach omits the need for wind turbine and generator models. The proposed methodology can be easily extended to passive load and motor drive applications. 4) A simplified two-step model predictive strategy is proposed to achieve optimal performance compared with the one-step prediction. The complete system model and control algorithms are presented and compared with the standard one-step prediction. R EFERENCES [1] M. Liserre, R. Cardenas, M. Molinas, and J. Rodriguez, “Overview of multi-MW wind turbines and wind parks,” IEEE Trans. Ind. Electron., vol. 58, no. 4, pp. 1081–1095, Apr. 2011. [2] F. Blaabjerg and K. Ma, “Future on power electronics for wind turbine systems,” IEEE J. Emerging Sel. Topics Power Electron., vol. 1, no. 3, pp. 139–152, Sep. 2013. [3] V. Yaramasu and B. Wu, “Three-level boost converter based medium voltage megawatt PMSG wind energy conversion systems,” in Proc. IEEE ECCE, Phoenix, AZ, USA, Sep. 2011, pp. 561–567. [4] B. Wu, Y. Lang, N. Zargari, and S. Kouro, Power Conversion and Control of Wind Energy Systems (IEEE Press Series on Power Engineering), 1st ed. Hoboken, NJ, USA: Wiley, Jul. 2011. [5] R. Teodorescu, M. Liserre, and P. Rodriguez, Grid Converters for Photovoltaic and Wind Power Systems. Chichester, U.K.: Wiley, Jan. 2011.

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Venkata Yaramasu (S’08) received the B.Tech. degree in electrical and electronics engineering from Jawaharlal Nehru Technological University, Hyderabad, India, in 2005, and the M.E. degree in electrical engineering from the S. G. S. Institute of Technology and Science, Indore, India, in 2008. He is currently pursuing the Ph.D. degree in electrical engineering with Ryerson University, Toronto, ON, Canada. His current research interests include renewable energy system, high power converters, and predictive control. Mr. Yaramasu received six Best Student Paper Awards and two first prizes in national level technical quiz competitions. He received the Best Poster Award at the NSERC–WESNet Annual Meeting in 2010, the Best Teaching Assistant Award from the Faculty of Engineering and Architectural Science in 2010, the Student Research Awards from the Toronto Hydro and Connect Canada in 2010, 2011, and 2012, and the Research Excellence Awards from the Electrical and Computer Engineering Department in 2012 and 2013.

Bin Wu (S’89–M’92–SM’99–F’08) received the Ph.D. degree in electrical and computer engineering from the University of Toronto, Toronto, ON, Canada, in 1993. He joined Ryerson University, Toronto, ON, Canada, after being with Rockwell Automation, Cambridge, ON, Canada as a Senior Engineer, where he is currently a Professor and NSERC/Rockwell Industrial Research Chair of power electronics and electric drives. He has published more than 280 technical papers, authored or co-authored two WileyIEEE Press books, and holds more than 20 issued/pending patents in the area of power conversion, advanced controls, adjustable-speed drives, and renewable energy systems. Dr. Wu is a fellow of the Engineering Institute of Canada and the Canadian Academy of Engineering. He received the Gold Medal of the Governor General of Canada, the Premiers Research Excellence Award, the Ryerson Distinguished Scholar Award, the Ryerson Research Chair Award, and the NSERC Synergy Award for Innovation.

Marco Rivera (S’09–M’11) received the B.Sc. degree in electronics engineering and the M.Sc. degree in electrical engineering from Universidad de Concepción, Biobío, Chile, in 2007 and 2008, respectively, and the Ph.D. degree from the Department of Electronics Engineering, Universidad Técnica Federico Santa María, Valparaíso, Chile, in 2011. He was a Post-Doctoral Fellow with Universidad Técnica Federico Santa María in 2011 and 2012, and he is currently a Professor with Universidad de Talca, Talca, Chile. His current research interests include matrix converters, predictive and digital controls for high-power drives, four-leg converters, renewable energies, and development of high performance control platforms based on field-programmable gate arrays.

Jose Rodriguez (M’81–SM’94–F’10) received the Engineer degree in electrical engineering from Universidad Técnica Federico Santa María, Valparaíso, Chile, in 1977, and the Dr.-Ing. degree in electrical engineering from the University of Erlangen, Erlangen, Germany, in 1985. He has been with the Department of Electronics Engineering, Universidad Técnica Federico Santa María, since 1977, where he is currently a Full Professor and Rector. He has co-authored more than 350 journal and conference papers. His current research interests include multilevel inverters, new converter topologies, control of power converters, and adjustable-speed drives. Dr. Rodriguez is a member of the Chilean Academy of Engineering.