Analysis and synthesis of sliding mode control for large scale variable speed wind turbine for power optimization Jov  an M  erida a, * , Luis T. Aguilar a , Jorge D  avila b a Instituto Polit ecnico Nacional e CITEDI, Av. del Parque 1310, Mesa de Otay, Tijuana, BC 22510, Mexico b Instituto Polit ecnico Nacional, ESIME e Ticom an, Av. Ticom an 600, Col. San Jos e Ticom an, Delegaci on Gustavo A. Madero, M exico, DF 07340, Mexico article info Article history: Received 2 August 2013 Accepted 18 June 2014 Available online 15 July 2014 Keywords: Sliding mode control Wind turbines Maximum power point tracking Renewable energy Nonlinear control abstract The problem of designing a nonlinear feedback control scheme for variable speed wind turbines, without wind speed measurements, in below rated wind conditions was addressed. The objective is to operate the wind turbines in order to have maximum wind power extraction while also the mechanical loads are reduced. Two control strategies were proposed seeking a better performance. The first strategy uses a tracking controller that ensures the optimal angular velocity for the rotor. The second strategy uses a Maximum Power Point Tracking (MPPT) algorithm while a non-homogeneous quasi-continuous high- order sliding mode controller is applied to ensure the power tracking. Two algorithms were devel- oped to solve the tracking control problem for the first strategy. The first one is a sliding mode output feedback torque controller combined with a wind speed estimator. The second algorithm is a quasi- continuous high-order sliding mode controller to ensure the speed tracking. The proposed controllers are compared with existing control strategies and their performance is validated using a FAST model based on the Controls Advanced Research Turbine (CART). The controllers show a good performance in terms of energy extraction and load reduction. © 2014 Elsevier Ltd. All rights reserved. 1. Introduction 1.1. Overview As a result of population expansion and increased global inte- gration, there has been a high growth in energy consumption. The high rates of electricity consumption supposes a risk for the depletion of natural resources, therefore the demand of renewable energy generation systems has increased [1]. Such demand is supported by social and environmental reasons: the debate on climate change, depletion of fossil resources and nuclear damage caused by the use of non-fossil fuels. All these factors have led to the global community, and national governments to set new pol- icies in favor of renewable energy and drive future improvements in related technologies. Wind energy has been proved to be an important source of clean and renewable energy in order to produce electrical energy. Wind energy is currently one of the fastest growing renewable energy technologies in the world [2]. On the other hand, wind turbines present great challenges because they are complex nonlinear systems containing uncertain parameters, unmodeled dynamics, and unknown disturbances. Ongoing research is focused on increasing energy efficiency and reducing mechanical stress. One solution is to use advanced control strategies that enhance the performance of the turbine, which allows a better use of resources of the turbine, augmenting the lifetime of mechanical and electrical components, earning higher returns. There are two primary types of horizontal-axis wind turbines: fixed speed and variable speed [3]. In this work, we choose the variable speed because although the fixed speed system is easy to build and operate, it does not have the ability that the variable speed system has in energy extraction, up to a 20e30% increase over fixed speed [3]. Wind turbine controller objectives depend on the operation area [4e7]. Variable speed wind turbine operation can be divided into three operating regions (Fig. 1):  Region I: below cut-in wind speed.  Region II: between cut-in wind speed and rated wind speed.  Region III: between rated wind speed and cut out wind speed. * Corresponding author. E-mail addresses: merida@citedi.mx, jovan21@gmail.com (J. M erida), laguilarb@ ipn.mx (L.T. Aguilar), jadavila@ipn.mx (J. D avila). Contents lists available at ScienceDirect Renewable Energy journal homepage: www.elsevier.com/locate/renene http://dx.doi.org/10.1016/j.renene.2014.06.030 0960-1481/© 2014 Elsevier Ltd. All rights reserved. Renewable Energy 71 (2014) 715e728