A REVIEW OF CONTROL STRATEGIES FOR ANALYZING AND DESIGNING MANAGING WIND GENERATORS

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1 A REVIEW OF CONTROL STRATEGIES FOR ANALYZING AND DESIGNING MANAGING WIND GENERATORS Vaa K. Gkountrouman (a), Peter P. Groumpos (b) (a) Department of Electrcal and Computer Engneerng, Unversty of Patras (b) Department of Electrcal and Computer Engneerng, Unversty of Patras (a) (b) ABSTRACT Wnd energy s currently a fast-growng nterdscplnary feld that encompasses many dfferent branches of engneerng and scence. Modelng and controllng wnd energy systems s a dffcult and challengng problem. The basc structure of wnd turbnes and some wnd control system methods are brefly revewed. The need for usng advanced theores from fuzzy and ntellgent systems n studyng wnd energy systems s dentfed and justfed. Fuzzy Cogntve Maps are used to model wnd energy systems. Smulaton studes are performed and obtaned results are dscussed. Many open problems n the areas of modelng and controllng wnd energy systems are outlned. Keywords: modelng, control, energy systems, wnd generators, fuzzy cogntve maps 1. INTRODUCTION The purpose of modern wnd energy converson systems (WECS) s to extract the aerodynamc power from the wnd and convert t to electrc power. Today the most wde spread verson of WECS s the horzontal axs wnd turbne (HAWT) wth a 3 blade upwnd rotor (Hau 2010; Tong 2010). Before the ntroducton of varable speed generators, the rotor speed on the HAWT was kept constant. Ths constrant lmted the effcency of the wnd power capture. New wnd turbnes are able to operate more effcent over a wder range of wnd speeds, whch has lead to more sophstcated control strateges wth the added degrees of freedom. Modern wnd turbnes are controlled by the ptch of the rotor blades, the electromagnetc torque of the generator and by the yaw of the nacelle. Tradtonally wnd turbnes are placed on land or on sold foundatons f placed n the water. Ths lmts ther deployment to locatons of relatvely shallow water because the constructon costs of an underwater monopole are too expensve or techncally mpossble. Modelng and controllng such systems s extremely dffcult but absolutely needed. In ths paper an overvew of exstng advanced modelng and control theores n analyzng and studyng wnd generators s presented. In Greece lately many wnd farms have been nstalled on mountans. Wnd energy producton attracts nterest as t encompasses many dfferent branches of engneerng and scence. Standard and Adaptve technques have been used for modelng and control wnd generators. The strong ponts of these methods are revewed, studed and presented. So, nowadays there are many methods to generate and control wnd energy. However, the wnd energy management s a challengng feld. The need for development of wnd energy wll be modeled usng Fuzzy Cogntve Maps. An ntroducton to basc theores of Fuzzy Cogntve Maps s presented. Especally the potental use of Fuzzy Cogntve Maps s nvestgated and future research drectons are proposed. 2. WIND TURBINE THEORIES A wnd turbne (WT) conssts of turbne tower, blades, rotor, generator, nacelle, shaft, drve or couplng devce, converter and control system. Fgure 1: Wnd Turbne Structure The nacelle houses the generator, whch s drven by the hgh-speed shaft. The hgh-speed shaft s n turn usually drven by a gear box, whch steps up the rotatonal speed from the low-speed shaft. The low-speed shaft s connected to the rotor, whch ncludes the arfol-shaped blades. These blades capture the knetc energy n the wnd and transform t nto the rotatonal knetc energy of the wnd turbne. 109

2 There are two man types of wnd turbnes: horzontal axs and vertcal axs. Horzontal axs turbnes, whch are more common, have to pont nto the wnd and ther axs s horzontal. Because of the angle of ther blades, they can collect the maxmum amount of wnd energy. Vertcal axs turbnes have axes that are vertcally stckng out of the ground and blades that rotate around the axs. They don't need to pont nto the wnd, whch makes them more useful n places where the wnd drecton s unpredctable. Some wnd turbnes are desgned to operate at a constant speed, whle others are bult to rotate at varable speeds. The nternal components of these two types of turbnes are very dfferent. In constant speed machnes, the connecton between the generator and grd do not allow for much varaton n the blade rotaton speed. Varable speed turbnes use power converters that allow for a wder range n blade rotatons. Power converters add to the cost of these machnes, but varable speed wnd turbnes provde sgnfcant advantages to a wnd farm and engneers contnue to research ways to make these turbnes more effcent. The output power of wnd turbnes vares wth wnd speed, but s not proportonal to t, as the energy that the wnd contans ncreases wth the cube of the wnd speed. Varable speed wnd turbnes have four man regons of operaton. A stopped turbne or a turbne that s just startng up s consdered to be operatng n Regon 1 n whch the wnd speed s too low for the turbne to generate power. Regon 2 s an operatonal mode n whch t s desrable to capture as much power as possble from the wnd and les between the cut-n speed and rated speed. Here the generator operates at below rated power. In Regon 3, n whch the wnd s suffcent for the turbne to reach ts rated output power, the turbne must lmt the captured wnd power so that safe electrcal and mechancal loads are not exceeded. Regon 4 s the perod of stronger wnds, where the power n the wnd s so great that t could be detrmental to the turbne, so the turbne shuts down. 3. CONTROL STRATEGIES Above rated wnd speed, the prmary objectve s to keep power output of the turbne and assocated loads on the turbne structure wthn desgn lmts. Classcal technques such as proportonal, ntegral, and dervatve (PID) control of blade ptch (Svensson and Ulen 1982) are typcally used to lmt power and speed on both the low-speed shaft and hgh-speed shaft for turbnes operatng n regon 3. In addton, several model-based classcal/optmal control desgn technques have been used to desgn controllers to regulate generator speed n hgh wnd speed condtons (Stol and Ballas 2001; Vhrala 2002). Below rated wnd speed, the focus s on maxmzng power capture. The loads on structure are, generally, small. In ths regon of operaton (regon 2), generator torque control (Fngersh and Carln 1998) s usually used. In (Stol and Ballas 2002) dsturbance accommodatng control s used to lmt power and speed n regon 3. The reducton of mechancal loads on the tower and blades s another area of turbne control research (Wrght and Balas 2004). Furthermore, there are many aspects of wnd turbne performance that can be mproved wth more advanced control development. Researchers have developed methods for usng adaptve control to compensate for unknown or tme-varyng parameters n regons 2 and 3 (Bhowmk, Spée and Ensln 1999; Freeman and Balas 1999; Song, Dhnakaran and Bao 2000). A few researchers have also begun to nvestgate the addton of feedforward control to mprove the dsturbance rejecton performance when the ncomng wnd profle devates from that expected (Hand, Wrght, Fngersh and Harrs 2006). Most of these feedforward controllers use estmates of the dsturbance or wnd devaton. For nstance, ldar sensors can provde quanttes representng the wnd speed and drecton and varous wnd turbulence and shear parameters (Hand, Wrght, Fngersh and Harrs 2006). Advanced wnd turbne controllers are dscussed n (Laks, Pao and Wrght 2009). Other researchers have developed technques n order to qualfy output power and guarantee operaton of the wnd turbne. Ther studes focus on: vector control, optmzaton control, power smoothng control and voltage control. Vector control s wdely appled n the control of nducton machnes and several types of ths control type are dscussed n (Cárdenas and Pena 2004; Chowdhury and Chellaplla 2006). Optmzaton control of wnd turbne ncludes several objectves, such as maxmum power output, maxmum power effcency, mnmum control nput, mnmum loss, etc. References (Mhet-Popa, Blaabjerg and Boldea 2004; Munteanu, Cutululs, Bratcu and Ceanga 2005) dscuss optmzaton control methods for maxmzng power extracton usng algorthms, robust controllers, etc. Power fluctuaton s one drawback of wnd power whch can nfluence power qualty. In (Cárdenas, Peña, Asher and Clare 2004; Senjyu, Sakamoto, Urasak, Funabash, Fujta and Sekne 2006) control strateges pontng to power smoothng are presented. Voltage control of wnd turbne or wnd farm s not ndspensable for tself, but also plays a great role n voltage stablty of grd. In (Tapa, Tapa and Ostolaza 2004; Hatzargyrou, Karakatsans and Lorentzou 2005) the ssue of voltage control s dscussed. Modelng and control nonlnear complex systems, wth new system theores, have always been frutful challenges. Many approaches have been developed. Some of them had good success n applyng them to wnd energy whle some others had some problems. However, a queston as to how much wnd energy should be produced on a gven geographcal regon has not yet found a realstc and acceptable soluton. Although FCMs have been used for wnd modelng there stll s the queston of optmal and cost effectve generaton. 110

3 4. INTRODUCTION TO FUZZY COGNITIVE MAPS Fuzzy cogntve map (FCM) s a soft computng technque, whch s capable of dealng wth complex systems. FCM s a promsng modelng method for descrbng partcular domans showng the concepts (varables) and the relatonshps between them (weghts) whle t encompasses advantageous features. FCM model represents the whole system by a sgned drected graph wth feedbacks, whch ndcate cause and effect among the concepts. It models a system as a collecton of concepts and causal lnks between them. The concepts are represented by nodes n ths graph and each concept represents a partcular characterstc of the system. In the FCM model cause and effect relatonshps among these concepts s ndcated by nterconnected weghted lnks whch have ether postve or negatve sgns and dfferent weghts. Each lnk gets a weght Wj accordng to the strength of the causal relatonshp between the concepts C and Cj. Some experts understand potental nfluences and nteractons between concepts. So, the expert s knowledge s transformed nto a dynamc weghted graph. Experts descrbe the exstng relatonshp between the concepts as a degree of nfluence usng a lngustc varable, such as "low", "medum", "hgh", etc. More specfcally, the causal nterrelatonshps among concepts are declared usng the varable nfluence whch s nterpreted as a lngustc varable takng values n the unverse of dscourse [-1, 1]. A detaled descrpton of the development of FCM model s gven n (Stylos and Groumpos 2004). The value of each concept at every smulaton step s calculated by applyng the followng calculaton rule (Groumpos and Stylos 2000): N t t 1 t 1 = ( j j + ) j= 1 j A f A W A t 1 A (1) where s the value of the concept C at t A teraton step t-1 and s the value of the concept C at teraton step t. Usually the f functon s: C3, C4) and one output whch s the development of wnd energy (C5). So, the concepts are: C1: Energy demand C2: Fossl fuel reserves C3: Wnd technologes / equpment / cost C4: Energy cost (from conventonal sources) C5: Development of wnd energy Concepts stand n the nterval [0, 1]. The closer to the 1 the value of the output concept s gettng, the hgher the need wnd energy producton s. An expert gave hs opnon about the nteracton between the concepts and nformed us about how much energy demand (concept 1), fossl fuel reserves (concept 2), wnd technologes / equpment / cost (concept 3) and energy cost (from conventonal sources only) (concept 4) nfluence the producton of wnd energy (output: concept 5). So the weghts between concepts are: Table 1: Weghts between Concepts Weghts C1 C2 C3 C4 C5 C C C C C The weght matrx s presented below: W= Table 2: Weght matrx The ntal Fuzzy Cogntve Map wth the frst values of concepts wll be as follows: f( x) 1 = 1 + x e λ (2) whch s the unpolar sgmod functon, where λ>0 determnes the steepness of the contnuous functon f(x). 5. THE CONSTRUCTION OF A WIND GENERATOR SYSTEM USING FCM THEORIES In ths secton a Fuzzy Cogntve Map wll be constructed for a smple wnd generator system. An expert proposed us a system wth four nputs (C1, C2, Fgure 2: The FCM Model The model shown n Fgure 2 wll be used n the next secton n order to predct the wnd energy producton. 111

4 6. SIMULATION, RESULTS AND DISCUSSION Three dfferent scenaros wll be smulated n order to decde how much wnd energy producton s necessary. As t was mentoned above the values of the concepts are between [0, 1]. 1 st Scenaro: Suppose that the expert decded as energy producton s low: Table 3: Intal Values of Inputs (1 st scenaro) C1 0.25/1 Very low C2 0.5/1 Medum C3 0.75/1 Hgh C4 0.4/1 Medum The FCM smulaton for the 1 st scenaro has the Fgure 4: Subsequent Values of Concepts where the output value s C5= Ths value, producton should be medum when the nputs (C1, C2, C3, C4) have these ntal values. 3 rd scenaro: Suppose that the expert decded as energy producton s hgh: Table 5: Intal Values of Inputs (3 rd scenaro) C1 0.75/1 Hgh C2 0.25/1 Very low C3 0.35/1 Low C4 0.65/1 Hgh Fgure 3: Subsequent Values of Concepts where the output value s C5= Ths value, producton should be low when the nputs (C1, C2, C3, C4) have these ntal values. 2 nd scenaro: Suppose that the expert decded as energy producton s medum: The FCM smulaton for the 3 rd scenaro has the Table 4: Intal Values of Inputs (2 nd scenaro) C1 0.5/1 Medum C2 0.45/1 Medum C3 0.6/1 Hgh C4 0.55/1 Medum The FCM smulaton for the 2 nd scenaro has the Fgure 5: Subsequent Values of Concepts where the output value s C5= Ths value, producton should be hgh when the nputs (C1, C2, C3, C4) have these ntal values. 7. CONCLUSIONS AND FUTURE RESEARCH In ths paper, we frst revewed the basc structure of wnd turbnes and then descrbe wnd turbne control systems and control loops. We have seen that the generator torque and blade ptch control systems are very mportant n wnd energy system desgn. Sgnfcant performance mprovements are achevable wth more advanced systems and control research. The 112

5 new method of Fuzzy Cogntve Maps for modelng and controllng nonlnear systems s used for frst tme to model wnd energy converson systems. The proposed model s very smple n whch only one expert s used. However the smulaton studes show that the use of FCMs does provde a new promsng methodology approach n modelng and controllng wnd energy systems. Some nterestng challengng research topcs nclude: 1) the valdaton of the proposed model 2) nclude addtonal concepts n modelng wnd energy converson systems especally for dfferent geographcal regons 3) use more than the one expert 4) conduct smulaton studes usng real data for varous applcatons and 5) use learnng algorthms to tran the experts. 8. REFERENCES Bhowmk, S., Spée, R., Ensln, J Performance optmzaton for doubly-fed wnd power generaton systems. IEEE Trans. Ind. Applcat. vol. 35: Cárdenas, R., Pena, R., Sensorless vector control of nducton machnes for varable-speed wnd energy applcatons. IEEE Trans. Energy Converson vol. 19: Cárdenas, R., Peña, R., Asher, G., Clare, J., Power Smoothng n Wnd Generaton Systems Usng a Sensorless Vector Controlled Inducton Machne Drvng a Flywheel. IEEE Trans. Energy Converson vol. 19: Chowdhury, H. B., Chellaplla, S., Double-fed nducton generator control for varable speed wnd power generaton. Electrc Power Systems Research vol. 76: Fngersh, L., Carln, P., Results from the NREL varable-speed test bed. n Proc. 17th ASME Wnd Energy Symp., pp January 12-15, Reno, NV. Freeman, J., Balas, M., An nvestgaton of varable speed horzontal axs wnd turbnes usng drect model-reference adaptve control. n Proc. 18th ASME Wnd Energy Symp., pp January 11-14, Reno, NV. Groumpos, P.P., Stylos, D.C., Modelng supervsory control systems usng fuzzy cogntve maps. Chaos Solt Fract., 11(3), Hand, M. M., Wrght, D. A., Fngersh, J. L., Harrs, M., Advanced wnd turbne controllers attenuate loads when upwnd velocty measurements are nputs. n Proc. 25th AIAA/ASME Wnd Energy Symp., Reno, NV. Hatzargyrou, D. N., Karakatsans, S. T., Lorentzou, I.M., Voltage control settngs to ncrease wnd power based on probablstc load flow. Electrcal Power and Energy Systems vol. 27: Hau, E., Wnd Turbnes: Fundamentals, Technologes, Applcaton, Economcs. Berln, New York : Sprnger. Laks, H. J., Pao, Y.L., Wrght, A., Control of wnd turbnes: Past, present, and future. n Proc. Amercan Control Conf. June 2009, St. Lous, MO. Mhet-Popa, L., Blaabjerg, F., Boldea, I., Wnd Turbne Generator Modelng and Smulaton Where Rotatonal Speed s the Controlled Varable. IEEE Trans. Industry applcatons vol. 40:3-10. Munteanu, I., Cutululs, A. N., Bratcu, I. A., Ceanga, E., Optmzaton of varable speed wnd power systems based on a LQG approach. Control Engneerng Practce vol. 13: Senjyu, T., Sakamoto, R., Urasak, N., Funabash, T., Fujta, H., Sekne, H., Output Power Levelng of Wnd Turbne Generator for All Operatng Regons by Ptch Angle Control. IEEE Trans. Energy Converson vol. 21: Song, Y., Dhnakaran, B., Bao, X., Varable speed control of wnd turbnes usng nonlnear and adaptve algorthms. J. Wnd Eng. Ind. Aerodyn. vol. 85: Stol, K., Ballas, M., Full-State Feedback Control of a Varable-Speed Wnd Turbne: A Comparson of Perodc and Constant Gans. Journal of Solar Energy Engneerng vol 123: Stol, K., Ballas, M., Perodc dsturbance accommodatng control for speed regulaton of wnd turbnes. n Proc. 21st ASME Wnd Energy Symp., pp January 14-17, Reno, NV. Stylos, D. C., Groumpos, P. P., Modelng complex systems usng fuzzy cogntve maps. IEEE Transactons on Systems, Man and Cybernetcs, Part A: Systems and Humans, 34, Svensson, J., Ulen, E., The control system of WTS-3 nstrumentaton and testng. n Proc. 4th Int. Symp. Wnd Energy Systems, pp September 21-24, Stockholm, Sweden. Tapa, A., Tapa, G., Ostolaza X. J., Reactve power control of wnd farms for voltage control applcatons. Renewable Energy vol. 29: Tong, W., Wnd Power Generaton and Wnd Turbne Desgn. USA, Canada, Mexco:WIT Press. Vhrala, H., Control of varable speed wnd turbnes. Thess (PhD). Tampere Unversty of Technology. Wrght, A., Balas, M., Desgn of controls to attenuate loads n the Controls Advanced Research Turbne. J. Solar Energy Eng. vol. 126: