Fractional order frequency proportional-integral-derivative control of microgrid consisting of renewable energy sources based on multi-objective grasshopper optimization algorithm

2021 ◽  
pp. 014233122110346
Author(s):  
Abdulsamed Tabak
Keyword(s):  
Fractional Order ◽  
Optimization Algorithm ◽  
Frequency Control ◽  
Frequency Deviation ◽  
Control Signal ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Multi Objective ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization

In recent years, fractional order proportional-integral-derivative (FOPID) controllers have been applied in different areas in the academy due to their superior performance over conventional proportional-integral-derivative (PID) controllers. When the literature is reviewed, it has been observed that lack of studies that use swarm-based and multi-objective optimization algorithms together with FOPID controllers in frequency control of micro-grid. The load frequency control (LFC) problem is considered as two objectives in order to eliminate the complications that occur when only the frequency deviation is minimized. In our study, a method called MOGOA-FOPID in which both the frequency deviation and the control signal are minimized together for the frequency control in the microgrid is proposed. By using the multi-objective grasshopper optimization algorithm (MOGOA), both the frequency deviation and the control signal are minimized together, and thus, it is aimed to limit the battery capacity, reduce the flywheel jerk and avoid high diesel fuel consumption as well as an effective frequency control. In order to obtain a more realistic system, not only the photovoltaic (PV) solar and wind power but also the load demand is taken in a stochastic structure. Then, the results of the proposed MOGOA-FOPID are compared with the results of multi-objective genetic algorithm (MOGA)-based PID/FOPID and MOGOA-PID and its superiority is demonstrated. Finally, robustness tests of the system are performed under the perturbed parameters and outperform of MOGOA-FOPID over other methods is seen.

A novel cascaded fuzzy PD-PI controller for load frequency study of solar-thermal/wind generator-based interconnected power system using grasshopper optimization algorithm

2020 ◽  
pp. 002072092093036
Author(s):  
Debasis Tripathy ◽  
NB Dev Choudhury ◽  
BK Sahu
Keyword(s):  
Power System ◽  
Optimization Algorithm ◽  
Pi Controller ◽  
Solar Thermal ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Load Frequency ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Fuzzy Pd

This work analyses the load-frequency responses of a multi-unit based two-area power system by proposing a novel cascaded fuzzy Proportional Derivative-Proportional Integral (PD-PI) controller tuned with a recently proposed grasshopper optimization algorithm. Performance of the power system comprising of conventional sources like hydro and thermal generating units is evaluated by cascaded fuzzy PD-PI controller optimised by grasshopper optimization algorithm. The potential of grasshopper optimization algorithm is validated by comparing with other algorithms. Further, load-frequency response is studied by penetrating solar-thermal and wind power generating units into the recommended system. The power system integrated with renewable sources puts forth a great stability challenge in the wake of high load perturbation. Hence, a robust secondary controller named cascaded fuzzy PD-PI controller is designed by endorsing a profound grasshopper optimization algorithm technique, to tackle this stability challenge. The credibility of the cascaded fuzzy PD-PI controller with/without nonlinearities presented in the system is validated by comparing the results obtained from proportional–integral–derivative and fuzzy-proportional–integral–derivative controllers. Besides this, the performance of the system under highly perturbed step load variation confers the robustness of the proposed method.

Fuzzy adaptive robust proportional–integral–derivative control optimized by the multi-objective grasshopper optimization algorithm for a nonlinear quadrotor

2020 ◽  
Vol 26 (17-18) ◽  
pp. 1574-1589
Author(s):  
Mohammad Javad Mahmoodabadi ◽  
Nima Rezaee Babak
Keyword(s):  
Control System ◽  
Sliding Surface ◽  
Proportional Integral Derivative ◽  
Adaptation Mechanism ◽  
Proportional Integral Derivative Controller ◽  
Proportional Integral ◽  
Grasshopper Optimization Algorithm ◽  
Proportional Integral Derivative Control ◽  
Grasshopper Optimization ◽  
Fuzzy Adaptive

Proportional–integral–derivative is one of the most applicable control methods in industry. Although it is simple and effective in most cases, it does not provide robustness against disturbances and may not perform well in cases with uncertainties and nonlinearities. In this study, a fuzzy adaptive robust proportional–integral–derivative controller is used to control a nonlinear 4 degree-of-freedom quadrotor. An adaptation mechanism is submitted to the proportional–integral–derivative controller for updating the proportional, derivative, and integral gains of proportional–integral–derivative control. Furthermore, a sliding surface is generated and submitted to the adaptation mechanism for better regulation of proportional–integral–derivative gains. Afterward, a fuzzy engine is applied to regulate the sliding surface for better performance of the adaptive proportional–integral–derivative when there are disturbance and uncertainties. The multi-objective grasshopper optimization algorithm is implemented on the control system for the regulation of the control system parameters to minimize the error and control effort of the proposed hybrid control system. Finally, the obtained results are presented for a nonlinear 4 degree-of-freedom multi-purpose (for marine, ground, and aerial maneuvers) quadrotor system designed and built in Sirjan University of Technology, Sirjan, Iran, to assure the effectiveness of this technique.

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