Smoothing wind power fluctuations by fuzzy logic pitch angle controller

doi:10.1016/j.renene.2011.07.034

Renewable Energy

Volume 38, Issue 1, February 2012, Pages 224-233

https://doi.org/10.1016/j.renene.2011.07.034 Get rights and content

Abstract

Wind energy has been receiving more acceptance as a reproducible, resourceful and clean energy source since last decade. Wind power is not constant and may fluctuate below the rated wind power when the wind speed is lower than the rated speed. This fact affects the stability of the power system, to which the wind generators are connected. This is becoming more significant with the increasing penetration of wind energy systems. Pitch angle control has been one of the most common methods for smoothing output power fluctuations during below rated wind incidents. A fuzzy logic pitch angle controller is proposed in this paper for smoothing wind power fluctuations during below rated wind incidents beside traditional power regulations during above rated wind incidents. Two smoothing methods have been presented: the determination of the command output power based on the exponential moving average with a proper selection of correction factor by fuzzy reasoning and the dynamic selection of target output power according to the wind incident. Simulation results show the effectiveness of the proposed fuzzy logic pitch angle controller in smoothing output power fluctuations with significantly small drop of output power.

Highlights

► Regulated power during above rated wind using fuzzy logic systems. ► Smoothed power fluctuations during below rated wind using two fuzzy logic methods. ► Performance of both methods were compared with conventional method. ► Method 1 performed partial smoothing with 4.7% more of power drop. ► Method 2 performed complete smoothing with 8.28% more of power drop.

Introduction

In recent years, wind energy has become popular due to its inherent attribute of reproducible, resourceful and pollution-free characteristics against the rapid depletion and increasing environmental threats of conventional energy. Moreover, wind energy has been competing with conventional energy as a result of its cost reduction with technological advancements and incentives for adopting renewable energy since last decade. All these factors have caused wind power to become the fastest growing energy source.

In this situation, many small scale wind farms are connected to the distribution network while many wind farms of 50 MW or more are directly connected to transmission network [1]. These bring new challenges to the stability of power system. One of the challenges is that wind power is not constant and can fluctuate significantly below the rated power since wind power is proportional to the cube of the wind speed. The problems originated by the wind power fluctuations are as follows [2]:

•
Wind power fluctuations may cause the grid frequency to fluctuate.
•
Amount of absorbed reactive power by the induction generator from power grid is directly related to the active power generation. The variation in wind speed causes the fluctuation of the active power generation and thus the absorbed reactive power, leading to voltage flicker at the buses of the power grid.
•
Frequency fluctuation and voltage flicker provide poor power quality and originate instability problems in the power system, especially when there are loads sensitive to accept high voltage and frequency variations.

The importance of smoothing output power fluctuations (SOPF) becomes more significant with the increasing penetration of wind energy systems into the grid. The synchronization phenomena of wind turbines in a wind farm have been discussed [3]. It showed that a wind farm with many wind turbines has the natural tendency of the SOPF, however this tendency may be lost if the output power fluctuation is synchronized from the synchronization phenomena. Recently, the provision of power storage system for the SOPF has been proposed [2], [4], [5], [6], [7]. This strategy is effective when power quality is concerned for high sensitive loads, but it is not efficient from economic point of view.

On the other hand, pitch angle control has become a very popular method for the SOPF, which can be achieved by different methods, like minimum variance control [8], H_∞ control [9], fuzzy logic control (with single fuzzy logic system (FLS)) [2], generalized predictive control [10] to ensure that the generated output power follows a command value determined by exponential moving average (EMA). Although these methods provided a reliable smoothing operation at low cost, they can only perform partial SOPF and hence offer the partial solution to the problems originated by the output power fluctuations. This kept the compensation role of the power storage system for proper smoothing still significant. In addition, they caused a large drop in output power.

In this paper, a fuzzy logic pitch angle controller is proposed on the motivation of better smoothing performance with a lesser drop in output power than that achieved in the previous literatures. It consists of two FLSs for both above and below rated wind incidents, which increases flexibility for construction of fuzzy rules for the improved SOPF. Two smoothing methods based on the FLS during the below rated wind incidents are presented. The first method combines the work in [2] and [10], it determines the command output power through the EMA with a proper selection of correction factor by fuzzy reasoning so that the output power follows the command value by dynamic pitch actuation. It eases the FLS construction with positive domain control input to achieve optimum SOPF with minimum possible pitch angle generation. It results in lesser drop in output power. The second method selects target output power to which the output power would be limited to. Different fuzzy rules are assigned for different target values to enable such dynamic pitch actuation so that it ensures proper SOPF with lesser drop in output power. A dynamic simulation is carried out to validate the effectiveness of the proposed fuzzy logic pitch angle controller.

This paper is organized as follows. Section 2 presents the configuration of wind generation system with their characteristic equations and describes the conventional proportional integral (PI) pitch angle controller. Section 3 presents the control strategy and structure of the proposed FLS. Section 4 presents the simulation results demonstrating the effectiveness of the proposed methods in smoothing output power fluctuations, followed by the conclusions in Section 5.

Section snippets

Wind power generation system

The aerodynamics of the wind turbine is characterized by C_p-λ-β curve, which is usually provided by the manufacturers. C_p is the power coefficient, it corresponds to maximum mechanical power extraction from wind at its maximum value and is a function of the tip-speed ratio (λ) and the pitch angle (β). For a given C_p, the mechanical power (P_m) and mechanical torque (T_m) extracted from the wind by the wind turbine can be expressed by [11] $P_{m} = \frac{ρ A C_{p} (λ, β) V_{W}^{3}}{2}$ $T_{m} = \frac{P_{m}}{ω_{t}}$ where ρ is the air density, A is the

Fuzzy logic pitch angle controller

Wind generators may operate above rated wind speed or below rated wind speed (the rated wind speed in this study is 13.3 m/s). Two fuzzy logic systems (FLSs) have been incorporated in the pitch angle controller for the operation of wind turbine above the rated wind incident (FLS-A) and below the rated wind incident (FLS-B).

In this paper, a fuzzy logic pitch angle controller is proposed on the motivation of better smoothing performance with a lesser drop in output power. Pitch angle controller

Simulations results

To investigate the effectiveness of the proposed methods, a wind turbine connected to a grid has been simulated using MATLAB/Simulink. The control action and collective responses of the conventional method (with PI pitch angle controller) and the proposed methods (with fuzzy logic pitch angle controller) at the grid have been compared. A fluctuating wind is simulated, whose pattern is adopted from [2] and [10]. The effectiveness of the proposed fuzzy logic pitch angle controller is demonstrated

Conclusions

This paper presents a fuzzy logic pitch angle controller, which is controlled by two mutually exclusive fuzzy logic systems. The main functions of the controller are to regulate output power during above rated wind incidents and smooth wind power fluctuations during below rated wind incidents by dynamic pitch actuation. Two methods have been depicted for the smoothing of wind power fluctuations The first method is to determine the command output power based on the EMA with a proper selection of

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Smoothing wind power fluctuations by fuzzy logic pitch angle controller

Abstract

Highlights

Introduction

Section snippets

Wind power generation system

Fuzzy logic pitch angle controller

Simulations results

Conclusions

Energy

App Ener

Elec Pow Sys Res

Comparison of pitch angle control models of wind farm for power system analysis

IEEE Pow Ener Soc Gen Meet

Synchronization of asynchronous wind turbines

IEEE Trans Power Syst

Output leveling of wind power generation system by EDLC energy storage system

Elec Eng Jpn

Terminal voltage and output power control of induction generator by series and parallel compensation using SMES

Elec Eng Jpn

Application of energy capacitor system to wind power generation

Wind Ener