This paper reviews state of the art maximum power point tracking (MPPT) algorithms for wind energy systems. Due to the instantaneous changing nature of the wind, it is desirable to determine the one optimal generator speed that ensures maximum energy yield. Therefore, it is essential to include a controller that can track the maximum peak regardless of wind speed. The available MPPT algorithms can be classified as either with or without sensors, as well as according to the techniques used to locate the maximum peak. A comparison has been made between the performance of different MPPT algorithms on the basis of various speed responses and ability to achieve the maximum energy yield. Based on simulation results available in the literature, the optimal torque control (OTC) has been found to be the best MPPT method for wind energy systems due to its simplicity. On the other hand, the perturbation and observation (P&O) method is flexible and simple in implementation, but is less efficient and has difficulties determining the optimum step-size.

A review of maximum power point tracking algorithms for wind energy systems

Wind power is the most reliable and developed renewable energy source over past decades. With the rapid penetration of the wind generators in the power system grid, it is very essential to utilize the maximum available power from the wind and to operate the wind turbine (WT) at its maximal energy conversion output. For this, the wind energy conversion system (WECS) has to track or operate at the maximum power point (MPP). A decent variety of publication report on various maximum power point tracking (MPPT) algorithms for a WECS. However, making a choice on an exact MPPT algorithm for a particular case require sufficient proficiency because each algorithm has its own merits and demerits. For this reason, an appropriate review of those algorithms is essential. However, only a few attempts have been made in this concern. In this paper, different available MPPT algorithms are described for extracting maximum power which are classified according to the power measurement i.e. direct or indirect power controller. Merits, demerits and comprehensive comparison of the different MPPT algorithms also highlighted in the terms of complexity, wind speed requirement, prior training, speed responses, etc. and also the ability to acquire the maximal energy output. This paper serves as a proper reference for future MPPT users in selecting appropriate MPPT algorithm for their requirement.

A review of conventional and advanced MPPT algorithms for wind energy systems

In order to be economically competitive, various control systems are used in large scale wind turbines. These systems enable the wind turbine to work efficiently and produce the maximum power output at varying wind speed. In this paper, an adaptive control based on radial-basis-function neural network (NN) is proposed for different operation modes of variable-speed variable-pitch wind turbines including torque control at speeds lower than rated wind speeds, pitch control at higher wind speeds and smooth transition between these two modes The adaptive NN control approximates the nonlinear dynamics of the wind turbine based on input/output measurements and ensures smooth tracking of the optimal tip-speed-ratio at different wind speeds. The robust NN weight updating rules are obtained using Lyapunov stability analysis. The proposed control algorithm is first tested with a simplified mathematical model of a wind turbine, and then the validity of results is verified by simulation studies on a 5 MW wind turbine simulator.

Adaptive Control of a Variable-Speed Variable-Pitch Wind Turbine Using Radial-Basis Function Neural Network

Wind energy conversion systems have been attracting wide attention as a renewable energy source due to depleting fossil fuel reserves and environmental concerns as a direct consequence of using fossil fuel and nuclear energy sources. Wind energy, even though abundant, varies continually as wind speed changes throughout the day. The amount of power output from a wind energy conversion system (WECS) depends upon the accuracy with which the peak power points are tracked by the maximum power point tracking (MPPT) controller of the WECS control system irrespective of the type of generator used. This study provides a review of past and present MPPT controllers used for extracting maximum power from the WECS using permanent magnet synchronous generators (PMSG), squirrel cage induction generators (SCIG) and doubly fed induction generator (DFIG). These controllers can be classified into three main control methods, namely tip speed ratio (TSR) control, power signal feedback (PSF) control and hill-climb search (HCS) control. The chapter starts with a brief background of wind energy conversion systems. Then, main MPPT control methods are presented, after which, MPPT controllers used for extracting maximum possible power in WECS are presented.

/pdf/mppt-control-methods-in-wind-energy-conversion-systems-ttypb7aotl.pdf

MPPT Control Methods in Wind Energy Conversion Systems

Maximum power point tracking (MPPT) is a very important necessity in a system of energy conversion from a renewable energy source. Every year a number of publications appear in various journals and conferences claiming to offer better and faster MPPT techniques for wind energy conversion system (WECS). This research paper provides a concise yet comprehensive critical analysis of these techniques with an in-depth review of their strengths and drawbacks. This review is unique as there has been no other research paper so far that offers such a complete and up-to-date investigation of MPPT techniques in WECS. Therefore this research paper can serve as a precise reference for the future research on MPPT for WECS.

Review and critical analysis of the research papers published till date on maximum power point tracking in wind energy conversion system

This paper presents a new adaptive control algorithm for maximum power point tracking (MPPT) in wind energy systems. A mathematical model of a wind turbine system is also provided. The proposed control algorithm allows the generator to track the optimal operation points of the wind turbine system under fluctuating wind conditions and the tracking process speeds up over time. This algorithm does not require the knowledge of intangible turbine mechanical characteristics such as its power coefficient curve, power characteristic or torque characteristic. It employs a search and reuse concept, a modified Hill Climb Searching (HCS) method and two newly defined loops: change detection loop (CDL) and operation point adjustment loop (OPAL). The adaptive nature of the proposed algorithm eliminates the need for customized algorithms that are optimal for only one particular turbine. It is also a solution to achieve fast optimum power point detection after its initial learning process. A simulated system has been built in PSIM 7.0 for mathematical verification of the wind energy system and for the verification of the proposed algorithm. The algorithm is realized in C++ script and detailed descriptions of the proposed control algorithm are provided for illustration purposes.

/pdf/a-new-adaptive-control-algorithm-for-maximum-power-point-37sv624wa7.pdf

J. Hui

Papers

A new adaptive control algorithm for maximum power point tracking for wind energy conversion systems