Fuzzy Logic-based Digital Hydraulics Control of Blade Pitch Angle in Wind Turbines

The pitch control system is generally employed in a wind turbine to mitigate load and maintain uniform power generation at above-rated wind speed regions. The hydraulic system has more power to weight ratio and so it is incorporated in the pitch system of large scale wind turbines. Some of the issues related to the usage of conventional valves in the Hydraulic Pitch System (HPS) are: internal leakage, throttling losses, high power loss, less fault-tolerant, requires high manufacturing tolerance, and more sensitive to contamination. To overcome these issues, digital hydraulics technology should be introduced as Digital Hydraulics Pitch System (DHPS). Commercially, Proportional Integral Derivative (PID) controller is used as a pitch controller but these controller performances don’t hold good when excessive disturbance or change in operating point occurs in the system. So, heuristic-based Fuzzy Logic Controller (FLC) is preferred which can surpass the PID problems. In this paper, a heuristic FLC based control strategy is proposed for a novel DHPS configuration to control the pitching action. The simulation model of DHPS is developed and system simulations are conducted. The comparative study on the effectiveness of FLC for DHPS and conventional valve controlled HPS is conducted.


Introduction
The necessity for renewable energy has started increasing exponentially due to the harmful effects created by non-renewable energy sources over the environment. On comparing the renewable energy sources, wind energy seems to be the most promising source of electric energy [1][2][3]. Since, Wind Turbine (WT) is given more priority than a conventional power plant by many countries, the technology related to WT has started to increase. To generate optimal power and also to safeguard the WT during high wind speeds, Pitch Control System (PCS) and yaw control system are mostly preferred [4][5][6]. Generally, PCS is employed at above-rated wind speed condition to maintain the uniform power generation and to mitigate erratic blade loads [7,8]. The two types of PCS used in WT are: electro-mechanical and Hydraulic Pitch System (HPS). Electric motors are used as pitch actuators in case of an electro-mechanical pitch system whereas hydraulic cylinder/motor are used in the case of HPS. Since HPS are more robust to disturbance and has more power to weight ratio than its counterpart, HPS is mostly preferred in large scale WT [9,10]. The advantage of using the hydraulic motor as the end actuator in HPS over the hydraulic cylinder is that the final pitch angle is directly proportional to the displacement of the hydraulic motor [11,12]. Conventionally, pump control, and valve control technique are preferred in HPS [13]. The reason for considering Valve Controlled (VC) HPS to be better because it has higher bandwidth than the pump control HPS [14]. Conventional IOP Publishing doi:10.1088/1757-899X/1123/1/012064 2 VCHPS uses proportional or servo valves to control flow rate and uses a directional valve to control the direction of the fluid [15] as shown in figure 1.
These valves have few drawbacks like internal leakage, throttling losses, high power loss, less fault-tolerant, requires high manufacturing tolerance, high cost, and more sensitive to contaminations [16][17][18]. The drawback of the conventional valve controlled HPS can be overcome by implementing Digital Hydraulics (DH) technology. The DH uses a 2/2 hydraulic valve arranged in parallel combination along with various sizes of orifice known as Digital Flow Control Unit (DFCU) as shown in figure 2. Based on positioning the DFCU in the hydraulic system, DH can be categorized into few types such as: digital displacement motor and pump, switching control, and parallel valve technology [19,20]. Here the digital motor concept is implemented. While designing the DFCU, the sizing of the orifice plays a vital role. The different methods utilized for sizing the orifice are to attain the varying flow rates are discussed in [19,21].
Though there are many advantages in the DH, the controllability of DH is still a tedious task [16,23]. The different valve actuation methods that are implemented in  21,24]. P + PID controllers were incorporated in [24] to analyze the robustness in the stability of DH which is subjected to unknown load and results show that the controller has better performance. In [25] a novel fine positioning method was developed where four DFCU were used which resulted in the accurate positioning of the hydraulic system. Zero-Flowrate-Switching (ZFS) control method makes the valve to turn off when the flow rate through the valve is zero [26]. The output of ZFS was found to be effective. Though different control techniques have opted in DH, still DH control has a large scope to improve the controllability due to the extreme non-linearity of 2/2 valves. To improve the controllability by resolving the nonlinearities in the system, heuristic-based Fuzzy Logic Controller (FLC) is implemented in this paper.
The contribution of this paper involves the development of a novel DHPS for wind turbine and also FLC. The output of FLC is DFCU pair valve state selection which results in varying the flow rate and also controlling the direction of the hydraulic fluid by using DFCU so that the required pitching action takes place at the pitch actuator to achieve the appropriate pitch angle. This paper is structured as follows: Section 2 presents a description of the system. Section 3 details the modeling of the  proposed system and FLC. Section 4 reveals the simulation results and discussion. Finally, section 5 discusses the conclusion. Figure 3 illustrates the proposed novel DHPCS which consists of FLC and DHPS. The DHPS consists of a fixed displacement pump driven by an electric motor. As discussed earlier the DFCU consist of 2/2 valves and orifice which is attached at the end of each valve.

System modeling
In this section, the blade load model and FLC are modeled for the proposed DHPCS. The closed-loop control strategy of DHPCS is shown in figure 4. FLC was chosen for the proposed configuration due to its advantage over the Proportional Integral (PI) and Proportional Integral Derivative (PID) [27]. The inputs to the FLC are blade load Pl and pitch angle error βe where βe is obtained from equation 1.
where βref is the pitch angle reference and βg is the pitch angle generated. The output of the FLC is states

Blade load model
The load that is developed over the blades due to varying wind speed is an important parameter to be considered while designing DHPS since the DHPS should overcome the blade load Pl and has to achieve the required pitch angle. The Pl is arrived from [28] The different blade loads for varying pitch angle and wind speed are shown in table 2 which is obtained by substituting the wind speed and pitch angle values in equation 2. The blade load model is

Fuzzy logic controller
FLC is based on the rules which are helpful when the dynamics of the system and also the complete nonlinearities of the system are not known. Similar to human beings making decisions, FLC applies reasoning and so the rules possess the knowledge of an expert of the system. The main advantage of FLC is that a mathematical description of the system which is to be controlled is not required. Fuzzy Logic Toolbox TM which is available in Matlab/SIMULINK. Generally, there are three stages in the FLC and they are fuzzification, fuzzy rules, and defuzzification. In the fuzzification process, the inputs are converted into fuzzy sets using linguistic terms and membership functions. Inputs and output use Triangular Membership Functions (TMF) which is shown in figure 5. TMF is highly sensitive when variables arrive at zero value [29]. Fuzzy rules are assigned as shown in table 2, where if and then statements are used to coin the rules like 1= 1 2= 2 = . The last process in the FLC is defuzzification where the fuzzy sets are converted into precise action with real values.

Simulations results and discussion
The FLC performance is tested by implementing it in the DHPS. Simulations were conducted from 3 sec to 10 sec (since it took 0-3 sec for the DHPCS to initiate). Reference pitch angle data of a 2MW wind turbine was obtained from [30]. These data reveal the exact pitch angle the blade should set in the wind turbine to extract optimal power and also to mitigate blade load. Here were are not going to discuss the optimal power generated and also load mitigated. Here we are going to discuss the performance of controller tracking the reference pitch angle. A random wind profile as shown in figure 6(a) was given as an input to the reference pitch angle model to generate the required βref. Further, the states generated by the FLC is shown in figure 6(b). The reference pitch angle generated is shown in figure 6c which was obtained by giving figure 6(a) wind profile as input. Figure 6(c) shows the comparison of βg to βref. The βg follows the same trend as βref. At the same time, there is a lag in terms of magnitude between βref and βg which is due to the nonlinearities exist in the DHPS. The pitch angle error has more influence over the states, if the error is more, then higher states are assigned to DFCU so that the high flow rate is attained by DFCU to compensate the error. For more pitch error, higher states values are assigned which can be observed in figure 6(d). The maximum pitch error observed was 1.009˚ as indicated in figure 6(d). The minimum error shows that the FLC has a better tracking ability which was developed for DHPS. Since the wind speed is drastically changing, FLC plays a vital role in tracking the pitch angle at all conditions. Future work involves reducing the lag so that the tracking performance can be improved and also to reduce the hydraulic system initiation lag.

Conclusion
The hydraulic pitch system delivers high power to weight ratio to mitigate load and maintain uniform power generation. In this paper, Digital hydraulics technology is implemented in a hydraulic pitch system to achieve the same performance of proportional or servo valve controlled system. The output of the fuzzy logic controller selects the DFCU pair and also the states to achieve the required pitch angle. The results show the controller has better tracking ability and the maximum pitch error observed was 1.009˚. The model was tested for various wind patterns and the output was found to be effective. So by implementing the proposed DHPCS, cost-effective, highly robust, fault-tolerant, and high response pitch systems can be established in wind turbines.