IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 49, NO. 3, MAY/JUNE 2013 1129 Stability Analysis of Maximum Power Point Tracking (MPPT) Method in Wind Power Systems Yu Zou, Malik E. Elbuluk, Senior Member, IEEE, and Yilmaz Sozer, Member, IEEE Abstract—The maximum power point tracking (MPPT) method is the key to notably improve efficiency and energy extraction in wind turbine systems. The MPPT method through the charac- teristic power curve is one of the popular MPPT methods. The reference current can be obtained using the relationship between power and current without requiring real-time wind speed infor- mation. This paper presents the steady-state and dynamic analyses of this MPPT method and proposes a single-pole transfer function to describe the effect of variation of wind speed on the generator speed. This is conducted by applying the small-signal analysis on a nonlinear turbine-rotor mechanical system. To verify the performance of the wind turbine system, both simulation and experimental systems are implemented based on MPPT power control. By the variation of wind speed, the behavior of the gener- ator speed presents good consistency among the proposed theory, simulation, and experiments. Index Terms—Doubly fed induction generator (DFIG), maxi- mum power point tracking (MPPT) method, small-signal model, wind emulator, wind power system. I. I NTRODUCTION A S ONE OF the most commonly used renewable energy sources, wind is the most promising one for replacing the fossil fuel in the near future. To achieve high efficiency in a wind power conversion system, the maximum power point tracking (MPPT) in variable-speed operation systems, like doubly fed induction generator (DFIG) and permanent- magnet synchronous generator systems, attracts a lot of atten- tion [1]–[3]. The studied MPPT methods in the history include three strategies, namely: 1) methods relying on wind speed; 2) methods relying on output power measurement and calcu- lation; and 3) methods relying on characteristic power curve. Most wind energy control systems are based on the wind speed measurement [4], [5]. In these systems, anemometers are typically required to measure the wind speed. Such systems suf- fer from additional cost of sensors and complexity. To solve this problem, wind speed estimation methods have been reported Manuscript received June 30, 2011; revised December 19, 2011; accepted May 8, 2012. Date of publication March 13, 2013; date of current version May 15, 2013. Paper 2011-IACC-163.R1, presented at the 2011 IEEE Industry Applications Society Annual Meeting, Orlando, FL, USA, October 9–13, and approved for publication in the IEEE TRANSACTIONS ON I NDUSTRY APPLICATIONS by the Industrial Automation and Control Committee of the IEEE Industry Applications Society. Y. Zou was with the Department of Electrical and Computer Engineering, The University of Akron, Akron, OH 44325-3904 USA. He is now with the Department of Electrical and Computer Engineering, Saginaw Valley State University, Saginaw, MI 48710 USA (e-mail: yzoul123@svsu.edu). M. E. Elbuluk and Y. Sozer are with the Department of Electrical and Computer Engineering, The University of Akron, Akron, OH 44325-3904 USA (e-mail: melbuluk@uakron.edu; ys@uakron.edu). 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/TIA.2013.2251854 Fig. 1. Characteristic power curve-based MPPT. [6]–[9]. Relying on complex software algorithms, the wind speed can be captured for controlling the optimal tip-speed ratio so that the MPPT can be implemented. In addition, tracking the maximum power could also be implemented through measuring the output power directly [10]–[13]. The idea of this method is the online measurement of the output power and checking the rate of change of power with respect to speed, i.e., dP/dω, to extract maximum power from the wind turbine system. MPPT can be achieved when dP/dω =0, through adjusting either the rotor speed or duty cycle of the converter. This method relies on a large amount of online computation, and thus, it would be difficult to achieve MPPT for fast-varying wind speeds. Although the varying tracking step could be used to improve computation speed, this disadvantage cannot be eliminated. Recently, a proposed method of employing the power versus rotor speed characteristic curve is frequently used due to its simplicity in hardware and software [14]–[17]. The optimal reference power curve is constructed according to experimental tests and programmed in a microcontroller memory, working as a lookup table. The system configuration is illustrated in Fig. 1. One could either measure the rotor speed and obtain the power reference to regulate the power or measure the wind speed and obtain the rotor speed reference to regulate the rotor speed. The former produces more accurate output power while the latter will have faster control response [18]. Aside from an accurate reference power curve, analysis is necessary to verify the stability of the method in terms of varying wind speed and output power. Few publications just address the stability issue of such method [19], but more detailed quantitative analysis should be conducted. This paper studies the performance of wind turbine under reference power curve MPPT power control. In particular, it presents a small-signal analysis on generator speed dynamics induced by variable wind speed. Also, an experimental setup to emulate the wind turbine operation in torque control mode is presented. Both steady-state and dynamic responses are implemented to verify the proposed analysis and conclusions. Section II will present how to obtain the optimal reference power curve and analyze the stability of this method by con- ducting the small-signal analysis. Section III will present the 0093-9994/$31.00 © 2013 IEEE