In recent times, wind energy receives maximum attention and has become a significant green energy source globally. The wind turbine (WT) entered into several domains such as power electronics that are employed to assist the connection process of a wind energy system and grid. The turbulent characteristics of wind profile along with uncertainty in the design of WT make it highly challenging for prolific power extraction. The pitch control angle is employed to effectively operate the WT at the above nominal wind speed. Besides, the pitch controller needs to be intelligent for the extraction of sustainable secure energy and keep WTs in a safe operating region. To achieve this, proportional–integral–derivative (PID) controllers are widely used and the choice of optimal parameters in the PID controllers needs to be properly selected. With this motivation, this paper designs an oppositional brain storm optimization (OBSO) based fractional order PID (FOPID) design for sustainable and secure energy in WT systems. The proposed model aims to effectually extract the maximum power point (MPPT) in the low range of weather conditions and save the WT in high wind regions by the use of pitch control. The OBSO algorithm is derived from the integration of oppositional based learning (OBL) concept with the traditional BSO algorithm in order to improve the convergence rate, which is then applied to effectively choose the parameters involved in the FOPID controller. The performance of the presented model is validated on the pitch control of a 5 MW WT and the results are examined under different dimensions. The simulation outcomes ensured the promising characteristics of the proposed model over the other methods.
Electric power source from wind energy (WE) becomes a main contribution power resource in the electrical system over the world. A substantial emphasis is located on cost-effective usage of the energy source for attaining simultaneous reliable and quality electrical supply [
The WT penetrated in novel regions such as power electronic system that is utilized for facilitating the connectivity procedure of a WE scheme with the grid. Moreover, this system helps in improving the extracted energy from the WE scheme and maximizes the entire performance. The maximal power point tracker (MPPT) is a vital controller needed for improving the output power from the WE scheme. Various researchers have been stated in the implementation field of MPPT controller with WT. In previous years, many effective and beneficial controlling methods have been issued for guarantying efficiency when taking into account economic factors. In [
Fuzzy logic controllers (FLCs), because of their strength they can control the system with complex mathematical modules and a higher degree of non-linearity [
This paper designs an oppositional brain storm optimization (OBSO) based fractional order PID (FOPID) design for sustainable and secure energy in WT systems. The proposed model focuses on the effective extraction of the maximum power point (MPPT) in the low range of weather condition and save the WT in high wind regions by the use of pitch control. Besides, the OBSO algorithm is derived from the integration of oppositional based learning (OBL) concept with the traditional BSO algorithm in order to improve the convergence rate, which is then employed for the optimal parameter selection of the FOPID controller. For examining the improved outcomes of the proposed model, a simulation process takes place on the pitch control of a 5 MW WT.
The rest of the paper is arranged as follows. The next section examines recent state-of-the-art controller technologies applied to WT systems. Section 3 elaborates the wind energy system model; Section 4 designs an OBSO-based FOPID controller. Section 5 evaluates the results of the proposed model, and Section 6 draws the conclusion.
This section performs a detailed review of existing controller designs for WT systems. In Kumar et al. [
Fathy et al. [
In Singh et al. [
Qais et al. [
The existing methodologies of MPPT control in wind turbines extract more efforts of control measures which lead to loss of energy. The loss of energy affects the sustainability in the power generation, thus reducing the efficiency of the power generation system using wind turbines. To overcome the observed pitfalls of the existing methodologies, the objectives of the proposed research work is framed and is listed as follows: Design a novel FOPID controller using OBSO algorithm for MPPT-Pitch Control of WT system
Aims to achieve sustainable and secure energy in WT systems by the use of optimal pitch control Derive an OBSO algorithm by integrating the concepts of OBL with the BSO algorithm in population initialization process Validate the efficiency of the OBSO algorithm on a
The proposed method is an hybrid meta-heuristic method to achieve high level of sustainability and efficiency in power generation system using wind turbines. The Maximum Power Point Tracking (MPPT) is performed effectively using OBL and BSO optimization algorithms.
The overall system model of wind energy is depicted in
WT is employed to convert the wind power into mechanical power, and the wind power is defined in
The coefficient values are allocated as follows as
The maximal mechanical power generated from the WT is defined in
Based on
A DFIG is employed. The mechanical
The pitch actuator offers the rotational movements of the blades in the WT over the longitudinal axis. The pitch actuator in WT generally has two restrictions in the amplitude and rate of change of pitch angle. The amplitude and rate limitations are assumed in the range of 0°−90° and −8°/s to +8°/s, correspondingly [
The energy from the wind turbines are extracted by the aerodynamic forces based on the drag and lift operations. In the proposed method, the aerodynamics is controlled by the pitch actuator, which acts as a subsystem for controlling the pitch angle of the overall system. The extracted energy by the aerodynamics is fed to the drive train which converts the mechanical energy to the electrical energy with the combined function of generator, gear box and power electronic converters. The generated energy is transmitted to the power grid/load through the generator and a part of generated power is fed back for the process of pitch controlling and torque controlling process such that to perform an efficient pitch controlling process. The controlling process drives the wind turbine power generation system to the high level of efficiency and the proposed system is composed of FOPID controller to execute this objective which is illustrated in the Section 4.
For satisfying the demands of control requirements, an effective FOPID controller is designed. Besides, the optimal parameters of the FOPID controller are tuned by OBSO algorithm.
The PI controller is usually employed in industry procedure control owing to the simplicity and better performance in linear as well as non-linear systems [
Another Version of the PID controller design has higher degree of freedom compared to the conventional PID controller. It is evolved from the integrator as well as differentiator with respect to
For implementing the FOPID in simulation and practically, an approximation with integer order transfer function is needed. Here, the Crone approximation is employed in which the approximation utilizes a recursive distribution of
The BSO technique is inspired using the concept of brainstorming, and it is an extensively utilized tool to increase inspiration in organizations that have attained broad acceptance as means of assisting creativeness [
Afterward selecting one/two ideas, the chosen idea(s) is upgraded by
To boost the convergence performance of the BSO technique, OBL concept is employed. OBL concept is utilized to enhance the quality of the initial population solution by the diversification of the solutions. The OBL scheme searches in all directions in the searching area, namely original solution direction, and opposite solution direction. At last, the OBL concept considers the fittest solution from every solution.
Opposite number
The above equation can be generalized to employ it in a searching area space with multiple dimensions. So, for generalization, each search agent and the corresponding opposite positions can be defined using
The value of every individual element in
Here, the fitness function is
The processes involved in the OBSO algorithm are listed as follows.
Population initiation X as Compute the opposite position of individuals OX as
Elect the
Here, the integral absolute error (ISE) condition is employed for minimizing the error signal. The objective function of the OBSO algorithm can be represented in
In this paper, the WT is modeled and designed by the use of Bladed software. The parameter setting of the WTs is given in
Parameters | Values |
---|---|
Air density ( |
1.22 kg/m3 |
Air viscosity | 1.82 e−5 kg/ms |
Nominal power |
5 MW |
Gearbox ratio (G) | 83.33 |
Total hub height | 80 m |
Rotor diameter | 118 m |
Time constant |
0.3 s |
Cut-in wind speed |
3.5 m/s |
Cut-out wind speed |
25 m/s |
The results of the OBSO algorithm under three different controllers are investigated in terms of ISE, NFE, SD, and CPU running time. An ISE analysis of the OBSO with other optimization algorithms under three controllers is made in
Methods | Controllers | ISE |
---|---|---|
BAT | PID | 10.389 |
FPID | 06.390 | |
FOPID | 08.521 | |
BSO | PID | 08.482 |
FPID | 05.391 | |
FOPID | 07.652 | |
OBSO | PID | 07.681 |
FPID | 04.918 | |
FOPID | 06.739 |
A detailed comparative results analysis of the OBSO algorithm with other methods in terms of CPU time is given in
Controllers | Methods | CPU time (s) |
---|---|---|
PID | DE | 34271 |
CDE | 34189 | |
PSO | 34218 | |
CPSO | 33984 | |
BSO | 32839 | |
OBSO | 32647 | |
OBSO | DE | 36105 |
CDE | 34530 | |
PSO | 34895 | |
CPSO | 34137 | |
BSO | 33998 | |
DE | 38850 | |
CODE | 38729 | |
PSO | 38601 | |
CPSO | 39146 | |
BSO | 38953 | |
OBSO | 38326 |
Besides, on investigating the performance of the OBSO with other approaches under FPID controller, it is evident that the DE algorithm has shown worse performance by offering a superior CPU time of 36105 s. Eventually, the PSO and CDE algorithms have demonstrated slightly enhanced outcomes with the CPU time of 34895 s and 34530 s respectively. In the meantime, the CPSO algorithm has revealed moderate performance over the other systems with a CPU time of 34137 s. Though the BSO algorithm has reached a reasonable CPU time of 33998 s, the proposed OBSO algorithm displayed superior performance with the least CPU time of 33864 s. Finally, on inspecting the performance of the OBSO with other algorithms under FOPID controller, it is evident that the DE algorithm has shown worse performance by offering a higher CPU time of 38850 s. Eventually, the PSO and CDE algorithms have demonstrated slightly enhanced outcomes with the CPU time of 38601 s and 38729 s respectively. Meanwhile, the CPSO algorithm has demonstrated moderate performance over the other algorithms with a CPU time of 39146 s. But, the BSO technique has reached a reasonable CPU time of 38953 s, the proposed OBSO system exhibited superior performance with the least CPU time of 38326.
This paper has devised an effective OBSO technique in the designing of FOPID controller to accomplish sustainable and secure energy in WT systems. The FOPID controller is proficiently designed with an aim of proficiently extracting the MPPT under different weather conditions using pitch control. The optimal design of FOPID pitch control in WT system results in enhanced performance under different aspects. In addition, the inclusion of OBL concept in the classical BSO algorithm results in improved convergence rate. For examining the improved outcomes of the proposed model, a simulation process takes place on the 5 MW WT. The experimental results highlighted the promising outcomes of the presented technique over the recent methods. In future, the settling time of the WT system can be reduced to boost the system stability. In addition, the multi-objective optimization method to reduce error and rate of control effort two paradoxical objectives could be utilized in future.
The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number IFPRC-040-135-2020 and King Abdulaziz University, DSR, Jeddah, Saudi Arabia.