Maximum Power-Point Tracking and Stall Control with Eddy Current Brake System on Small-Scaled Wind Turbines and its Application on Agricultural Harvesting

A R T I C L E I N F O A B S T R A C T Article history: Received: 21 May, 2020 Accepted: 21 June, 2020 Online: 12 July, 2020 This research aims to enhance the generated power of the small-scaled wind turbine using the eddy current brake system and Maximum Power Point Tracking (MPPT) control method. We analyzed the behavior of the generated power and power factor, with and without the MPPT control which implemented by eddy current brake system. Also, the feasibility of the system investigated using different wind conditions such as strong and calm wind conditions. The load data has different voltage respond to the system since its conditions depend on the day/night loads pattern, weather conditions, soil moisture. Moreover, the analogical experiment for small-scaled wind turbine blade destruction is analyzed to determine the maximum penetration value of mechanical power in order to retrieve an optimal angular velocity which resulting in provides a possible maximum power to loads. At the same time, emergency break is operated when angular velocity reaches to critical speed to avoid destruction. In the simulation, we collected the real load data from a mango farm in Okinawa prefecture in Japan. The results were analyzed through simulations for the different wind conditions. In the end of simulation, we could verify that either Maximum Power Point and emergency control are activated correspondingly.


Introduction
As a renewable energy generating equipment, small-scaled wind turbines have rising demand to fulfill the modern energy requirements. The small-scaled wind turbines have several merits such as less area needed for setting up the entire system, low cost maintenance and easy to assemble which are advantages for household use [1]. Comparing to the conventional large-scale wind turbines, small-scaled wind turbines produces small amount of power while large scale wind turbines produces maximum 8MW power. Therefore small-scaled wind turbines are suitable for household and small-scaled green houses and farms.
To supply a stable electricity output, small-scaled wind turbines uses several control methods such as pitch control [2][3], yaw control, brake control [4][5][6]. Considering brake control, it is mainly focus on brake pad-based system for the safety of the wind turbine [7] while contactless brake systems related research is ongoing currently. In [8] we proposed to realize a contactless angular velocity in emergency case by eddy current method, however, the optimal control was not concerned. In this research, we are focusing to enhance the power through maximum power point tracking (MPPT) using eddy current brake system and eddy current brake system for emergency rotational control.
Since the wind speed stability is always unpredictable, it is a difficult task to generate the maximum power continuously and keep the generated power in a stable state. In this regard MPPT control can be considered as an important controlling method to generate the maximum power. Many types of MPPT control methods are used for generating maximum power such as using fuzzy logic controllers [9], adaptive control [10], etc. In this research, we use the eddy current brake as the main controller tool for the MPPT control. Here, MPPT operation is to convey the maximum possible power from turbine to generator. Therefore, this operation contains power enhancement characteristics. Meanwhile, emergency break is implemented as well to avoid any destruction or malfunction of entire system since small-scaled wind turbine's angular velocity rise up drastically during the high wind penetration.

ASTESJ ISSN: 2415-6698
In this study, the mango green house is a mango cultivating farm where the location is in Okinawa, Japan. The mango plants are required to be grown in a controlled environment in order to make best condition for cultivating. Also, the conditions are monitored using Internet of Things (IoT) technology. Therefore, the farmer can analyze the real time mango plants conditions such as its soil moisture, farm temperature, CO 2 conditions, light conditions and humidity.
In this paper, first we explain about the structure of the proposed system including proposed brake system, control diagram, simulation block diagram. Next, we explain the mathematical modeling of the system. Afterwards, we describe the simulation and results. Finally, we describe the conclusion of our research. This research is an extended work of [11].

Blade destruction analysis
This section explains the analogical experiment of the blade destruction. We performed this experiment to analyze the blade destruction for different penetration values. In other words, we did this experiment to decide the safety margins of the small-scaled wind turbine. In Figure 1, the experimented broken small-scaled wind turbine blade is displayed. In the following equation (1) F max means the maximum allowable force on the wind turbine blade and m means the mass of the turbine's blades. Also, ω represents the blade destruction angular velocity. Table 1 shows the specification of the blade. The material of the blade is made using Fiber Reinforced Plastic (FRP).    Figure 2, the A point stands for the maximum force safety margin. If the penetration exceeds the point A then the turbine's blades start to brake. When the penetration value reaches nearly 28kN (point D), the turbine's blades were destroyed. Therefore, to protect the turbine, we put c as the primary safety margin which has penetration value of 2.5kN. B means the secondary safety margin that 4kN is penetrated. For secondary safety margin, the angular velocity is 25rad/s and angular velocity for primary safety margin is 20rad/s. Hence, for the simulation purpose, we set the primary safety margin angular velocity ω as follows: ω = 20rad/s.

Structure of the system
It is necessary to consider the electrical and mechanical aspect of the proposed system structure. For the mechanical section, we consider the brake system controlling structure. Here, the emergency rotation control eddy current brake system and MPPT control eddy current brake works independently which is illustrated in Figure 3. They always control the reference value of the angular velocity ω ref and the angular velocity output ω. When the controller receives the angular velocity of the turbine, controller will send its signal to two servo motors which are operates as emergency rotation control and MPPT control unit to place the magnets nearby the copper plates to control the rotation.
When the wind turbine rotates, the signal controller will receive the angular velocity measurement and it will send the signals to the emergency rotation control eddy current brake and MPPT control eddy current brake. According to the current rotation situation, above mentioned two brake systems will control the f emergency(ω) which corresponds to emergency rotation control eddy current brake and f MPPT(ω) . Here, f MPPT(ω) corresponds to MPPT control eddy current brake. This process is illustrated in Figure 4. Figure 5, shows the entire block diagram of the small-scaled wind turbine system for realization in hardware. Here, 1/s symbol represent the integrator symbol. For this system, the generator is considered as DC generator. Figure 6, displays the equivalent circuit of DC generator including the protection diode, load and battery.
Regarding the electrical aspect of the proposed system, important conditions are explained as follows. When the battery charge becomes low, the additional current from the generator will charge the battery. In the other hand, if the generator unable to supply demanded current, then battery will supply the required current to the load. If the battery is full and the required power is supplied to the load, then the turbine rotation is reduced using the eddy current brake system.

Structure of eddy current brake system
Electromagnetic brake systems can be seen in modern world applications such as Maglev train brake system, gym instruments, and elevators, etc. Unlike the non-contactless braking operation, eddy current brake system can be considered as an efficient brake system [12].
Here, let us describe the eddy break system specifically. When the rotor shaft rotates in ω angular velocity, the magnetic flux between the two magnets are changing due to the interaction with the copper plate. Due to this magnetic flux change, eddy current will induce on the copper plate according to the faraday law of induction [13]. Due to the induced current, there will be opposing force or in the rotational case the torque generate against the rotation. This torque will act as the eddy current brake torque. In Figure 7, means the magnitude of magnetic charge on magnetic poles and qc means magnitude of induced magnetic charge on copper plate. The induced voltage is expressed in following equation that is based on the Faraday law of induction, where, ε stands for electromotive force and φ for magnetic flux.
Here, RC is the resistance of the copper plate and Ieddy is the induced eddy current on the copper plate. The relation with the RC and Ieddy is shown in (3), which is based on the ohm's law, ε = R c I eddy (3) From above equations, we can write down the eddy current as follows.
Due to occurrence of above current, the break system is activated. Next section describes the dynamics of whole system.

Mathematical modeling of the system
This section introduces the mathematical modeling of the entire system. Therefore, it is important to consider the dynamics representation of mechanical and electrical part of the proposed system. The parameters were used for the mechanical section is displayed in table 2 and the electrical section is displayed in table 3 along with combined electrical and mechanical equations.

Equation (5) displays the summation of the inertia moments of the wind turbine and blades
J=J ω +J G (5) The conventional mechanical and electrical dynamics of the system displayed in (6) J dω(t) This formula stands for controlling the brake plate rotation in a contact manner. However, in [8] we have proposed for contactless break system that is shown as follows.
Here, µ stands for permeability of the space. and stands for magnitude of the magnetic field of the magnet and copper plate respectively. This formula is based on gilbert model magnetic force [14].
Next, we are going to model the electrical part of the system. In the following table the parameters are described.
Generated power is displayed in (8).
Electrical torque of the generator displayed in (9) T e = P e ω (9) where, e stands for induced voltage and i for armature current. Equation (10) displays the battery electrical charge dynamics Induced eddy current brake torque for emergency brake initial capacity. Adversely, the current exchange among battery, turbine and loads can be retrieved by derivative of equation (10) which is Therefore, whenever equation (11) becomes zero, the consuming and generating currents are balanced or if iR is greater than zero it is both charging mode to battery and providing currents to loads, simultaneously. Adversely, if iR is less than zero then the battery only provides the power to loads that is discharging mode.
From equivalent circuit of DC generator in Figure 6, the electrical dynamics of the system is obtained as follows.
The purpose of setting diode in the output terminal of dc generator is to avoid being motor mode for dc generator when there is no wind penetration since battery is connected to generator's terminal. Thus, diode characteristic should be considered as well. The drop voltage of diode is shown in following equation.
Where, I d corresponds to armature currents as following expression (14).
Next, the induced electromotive force (emf) of the generator is displayed in (15).
Here, K e stands for Induced emf constant.
Up to here, the electrical model were described. From next equation the mechanical parts including the break terms are expressed.
The following equation shows the mechanical torque.
Below equation is based on the conventional break method, however, Cp is variable with respect to tip speed ratio.
Then we can reform the above equation for proposed method by adding the eddy current brake for emergency brake and MPPT control that is shown as (18).
In above equation, f MPPT and f emergency has different values and f em value is larger than f MPPT since f emergency requires more braking force to control the over-rotation of the turbine than the force use to realize MPPT.
Equation 19 task is to work as a switch to keep the output power in a maximum state which means keep the angular velocity ω in the following condition: ( ω < ω ref ) that is in the MPPT operation status. However, if ω exceed ω ref value ( ω> ω ref ), then the output power is not in a Maximum power state. Nevertheless, still the system is generating power since ω value isn't reached to ω lim yet which is the safety margin of the wind turbine. If this situation going to happen then the emergency brake will start to reduce the ω value to keep the state as ω < ω lim condition. Therefore, equation 20 [15] task is to work as a switch to determine ( ω<ω lim ) condition. Due to the compatibility of small-scaled turbine, we designed the mathematical expression of the C P as mentioned below in (22) and C P -λ relationship shown in Figure 8.
Where, the condition of coefficients is a > 0 and β > α.  As it is shown in Figure 7 the output terminal of generator is connected to a battery and battery is connected to the loads in parallel. Therefore, in order to verify the battery voltage, we have designed a battery capacity charging in which the battery voltage can be obtained by the Equation (24) represents the characteristic of the accumulated consumed current.
Notice that the load voltage and battery voltage is identical since as it has been mentioned they are connected in parallel.

Simulation and results
In this section, we conduct the simulation in two steps. First, we simulated the entire system for different average wind velocities from 7m/s, 14m/s, 21m/s and 28m/s, respectively. Then plotted the stall control charts for above velocities. We did this step to analyze the wind turbines stall control behavior for different wind velocities. Afterwards, we plotted the Mechanical power (Pm) and power coefficient of the system for different conditions. For the second step, we simulated the entire system for calm and storm days wind conditions for one day and analyzed the behavior of outputs of the system.

Simulation conditions
This section explains the conditions of the simulation and system we used in order to conduct the simulation. The load data for the system is applied using real mango greenhouse system in Okinawa [16]. Load pattern is displayed in Figure 9. This load consists of Light emitting diode (LED) lights, Compact Fluorescent Light (CFL) lights, Electrical Fans. According to the Figure 9 the highest load value is 12.8A. Here, the sample time for the simulation is 0.01s. MATLAB/Simulink software platform is used for the simulation. For the simplicity, simulation time is set to be 100s from Figure 10 to Figure 21. From Figure 22 to Figure  33, simulation time is one day long. Values of the parameters for simulation are displayed specifically in Table 4.

Results
From figure 10 to figure 13, they display the stall control chart for 7m/s, 14m/s, 21m/s, 28m/s, respectively. According to above stall control figures, the wind turbine angular velocity emergency control is valid up to 28m/s velocity. Therefore, the eddy current brake system can control the overrotation of the wind turbine up to 28m/s. Table 5 shows the ωref which is optimal angular velocity to realize the maximum power operation and ωstall is the actual output of angular velocity. As it is obvious in the above table, the output angular velocity for input wind is lower than the optimal angular velocity since in high wind penetration emergency break is activated. Specifically, comparing to the ω , value is becoming lower when wind velocity increase. That means when the input wind velocity is 28m/s the value is 25.199 the MPPT control is stopped because ω> ω ref . However wind turbine is still operating using the emergency eddy current brake since ω is nearly the value of ω . Next, from Figure 14 to Figure 17, The instantaneous angular velocity deviation = − show their behavior for 7m/s, 14m/s, 21m/s, 28m/s average wind velocities, respectively. According to the Figure 18, when the average wind velocity is 7m/s the mechanical power with the MPPT and emergency brake has higher value comparing to without the MPPT and emergency brake. As well, for Cp, when the MPPT and emergency brake is triggered it contains higher value. But, when Cp is without the control of MPPT and emergency brake, the value is low.
In Figure 19, Figure 20 and Figure 21 which are correspond to average wind velocity of 14m/s, 21m/s and 28m/s, they have the same comparison results as mentioned in above for 7m/s. Therefore, it is obvious that when the system is under the controlled state for MPPT and over-rotation, the mechanical power of the wind turbine and the power factor (Cp) have their maximum values. We have artificially created two wind patterns for the simulation process. First, we have done the simulation for calm day and then for the storm day condition. For calm day and storm day wind patterns are shown in Figure 22 and Figure 23. For the first phase of calm day the velocity gradually increases from 7m/s to 14m/s. Afterward, it decreases gradually from 14m/s to 10m/s. Then the 10m/s wind velocity maintain stable for few hours. Afterwards the velocity will decrease until 8m/s. Then, it will increase from 8m/s to 12m/s. Again, it will increase from 12m/s to 14m/s gradually. Finally, the velocity will decrease from 14m/s to 8m/s. For calm day the highest wind speed is approximately 14.3m/s and storm day the highest wind speed is approximately 30m/s. Lowest wind speed for calm day and storm day are 7m/s and 10m/s. Next, Figure 24 and Figure 25 shows the angular velocity deviation ∆ values which changes with respect to the wind condition. There are some peaks occurred according to the Figure  22. These peaks happen due to the emergency braking for sudden wind condition changes. Here, the ∆ is nearly zero means the wind turbine produces its maximum power. In calm day, the angular velocity does not achieve to critical value which is 20 rad/s. Nevertheless, according to angular velocity deviation in Figure 24, it is attempting to reach the angular velocity that operates at maximum power point. Same to Storm day, angular velocity tries to operate at its maximum power point.
However, as it can be seen Figure 25, the deviation of angular velocity has negative two peaks for some determined period. Correspondingly, it is obvious in Figure 27 that during the peaks of angular velocity deviations the output of angular velocity is suppress by 20 rad/s. Thus, the emergency brake is also activated in storm situation.

The angular velocity always kept under
= 20 for both calm day and storm day stall control patterns which are shown in Figure 26 and Figure 27. Electrical power (Pe), Electrical torque (Te) for calm day and Pe, Pm, Te, Tm for storm day. According to those figures the Pe, Pm, Te, Tm have higher values comparing to the calm day for emergency brake and MPPT brake activated state. Therefore, the small wind turbine is capable of generating high power even in a storm day.  Figure 30 and Figure 31, the battery voltage for storm day has good performance comparing to the battery voltage for calm day. Thus, for both cases we can say it has sufficient amount of voltage.  Figure 32 and Figure 33 shows the generator output current for calm day and storm day. For storm day, the generator output current has significant increase comparing to the clam day current in the MPPT and emergency brake-controlled condition. Nevertheless, even in calm day sufficient capacity of battery is maintained which is sustainable for providing the power to greenhouse environmental loads. Thus, we can conclude that efficiency of power extraction is improved with cooperative of the emergency operation.

Conclusion
We have conducted the simulation for different wind condition and analyzed the behavior of the system when the system is in control of MPPT and Eddy current brake conditions. Moreover, the analogical experiment for the small-scaled wind turbines to decide the maximum penetration value and maximum angular velocity the wind turbine blades can withhold was performed. Therefore, we can conclude that the behavior of the system is in controlled state by using above mentioned control methods. We believe the eddy current brake system can be implemented in a small-scaled wind turbine system for the purpose of MPPT and control the over-rotation by strong wind. As future works, we will add pitch control for establish the system more robust. Also, the real system will be implemented.