Adaptive differential evolution and pattern search tuned fractional order fuzzy PID for frequency control of power systems

2021 ◽  
pp. 1-15
Author(s):  
Prangya Mohanty ◽  
Rabindra Kumar Sahu ◽  
Dillip Kumar Sahoo ◽  
Sidhartha Panda
Keyword(s):  
Power Systems ◽  
Differential Evolution ◽  
Fractional Order ◽  
Frequency Control ◽  
Pattern Search ◽  
Fuzzy Pid ◽  
Adaptive Differential Evolution

scholarly journals Comparative performance analysis of hybrid differential evolution and pattern search technique for frequency control of the electric power system

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Pratap Chandra Pradhan ◽  
Rabindra Kumar Sahu ◽  
Sidhartha Panda
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Power System ◽  
Differential Evolution ◽  
Frequency Control ◽  
Electrical Power ◽  
Pattern Search ◽  
Thermal System ◽  
Electrical Power Systems ◽  
Suggested Approach

AbstractIn the current situation, operation and control of power system is a greater challenge. The most significant situation in power system control is load frequency control. In the present work, a hybrid differential evolution and pattern search (hDE-PS) method has been suggested for frequency regulation of electrical power systems. Fractional-order proportional integral derivative (FOPID) controller is implemented for design and analysis purpose. The suggested control method has been applied for two electrical power systems model, i.e., 2-area diverse source power system with/without HVDC linkage and 2-area thermal system. The performances of the suggested controller have been evaluated with PID and optimal controller. The simulation results indicate that system performances are enhanced with the suggested approach for identical structure. Robustness of the suggested approach has been analyzed by variation in random load and the system parameters. The suggested method (hDE-PS tuned FOPID) is further investigated with a 2-area thermal system. The performance of the recommended approach is analyzed by equating the results with other newly available approaches, like Genetic Algorithm (GA), Bacteria Foraging Optimization Algorithm (BFOA), Particle Swarm Optimization (PSO), hybrid BFOA and PSO (hBFOA-PSO), multi-objective Non-dominated Sorting Genetic Algorithm (NSGA)-II and Firefly Algorithm for the similar structure.

scholarly journals MVO-PS Optimized Hybrid FOFPID Controller for Load Frequency Control of an AC Micro-Grid System

2019 ◽  
Vol 8 (2) ◽  
pp. 3805-3812 ◽  
Keyword(s):  
Fractional Order ◽  
Frequency Control ◽  
Storage System ◽  
Energy Storage System ◽  
Pattern Search ◽  
Load Frequency Control ◽  
Grid System ◽  
Fuzzy Pid ◽  
Load Frequency ◽  
Micro Grid

This paper proposes a new approach for load frequency control in a multi micro grid system by using hybrid multi verse with pattern search (hMVO-PS) algorithm based Fractional Order Fuzzy PID controller. A multi micro grid system may be molded by some of the renewable resources (RESs) like photovoltaic (PVs), wind (WTGs), energy storage system (ESSs) and loads. The fractional order fuzzy PID (FOFPID) controller parameters are optimized by novel hybrid Multi verse with pattern search (hMVO-PS) technique. The flexibility and robustness of proposed FOFPID controller is inspected under different disturbance like stochastic variations. The superiority of FOFPID structure over conventional Fuzzy PID/PID and hMVO-PS technique over multi verse optimization (MVO), particle swarm optimization (PSO) and genetic algorithm (GA) has been manifested

scholarly journals Fractional Order Fuzzy PID Controller for Automatic Generation Control of Power Systems

2021 ◽  
Vol 19 (1) ◽  
pp. 71
Author(s):  
Dillip Kumar Sahoo ◽  
Rabindra Kumar Sahu ◽  
Sidharth Panda
Keyword(s):  
Power Systems ◽  
Fractional Order ◽  
Optimization Algorithm ◽  
Search Algorithm ◽  
Thermal Power ◽  
Automatic Generation ◽  
Test System ◽  
Pattern Search ◽  
Fuzzy Pid ◽  
Bee Colony

In this study, a Hybrid Adaptive Differential Evolution and Pattern Search (hADE-PS) tuned Fractional Order Fuzzy PID (FOFPID) structure is suggested for AGC of power systems. At first, a non-reheat type two-area thermal system is considered and the improvement of the proposed approach over Bacteria Foraging Optimization Algorithm (BFOA), Teaching Learning Based Optimization (TLBO), Jaya Algorithm (JA), Genetic Algorithm (GA) and Hybrid BFOA and Particle Swarm Optimization Algorithm (hBFOA-PSO) for the identical test systems has been demonstrated. The analysis was then extended to interconnected thermal power system of reheat type and two-area six-unit system. The results are compared with Firefly Algorithm (FA), Symbiotic Organism Search Algorithm (SOSA) and Artificial Bee colony (ABC) for second test system and TLBO, Hybrid Stochastic Fractal Search and Local Unimodal Sampling (hSFS-LUS), ADE and hADE-PS tuned PID for third test system. Finally, robustness of the suggested controller is examined under varied conditions.

Grasshopper Algorithm Optimized Fractional Order Fuzzy PID Frequency Controller for Hybrid Power Systems

2019 ◽  
Vol 12 (6) ◽  
pp. 519-531
Author(s):  
Deepak Kumar Lal ◽  
Ajit Kumar Barisal
Keyword(s):  
Power Systems ◽  
Power System ◽  
Fractional Order ◽  
Pid Controller ◽  
Load Frequency Control ◽  
Pid Controllers ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Hybrid Power ◽  
Increasing Demand

Background: Due to the increasing demand for the electrical power and limitations of conventional energy to produce electricity. Methods: Now the Microgrid (MG) system based on alternative energy sources are used to provide electrical energy to fulfill the increasing demand. The power system frequency deviates from its nominal value when the generation differs the load demand. The paper presents, Load Frequency Control (LFC) of a hybrid power structure consisting of a reheat turbine thermal unit, hydropower generation unit and Distributed Generation (DG) resources. Results: The execution of the proposed fractional order Fuzzy proportional-integral-derivative (FO Fuzzy PID) controller is explored by comparing the results with different types of controllers such as PID, fractional order PID (FOPID) and Fuzzy PID controllers. The controller parameters are optimized with a novel application of Grasshopper Optimization Algorithm (GOA). The robustness of the proposed FO Fuzzy PID controller towards different loading, Step Load Perturbations (SLP) and random step change of wind power is tested. Further, the study is extended to an AC microgrid integrated three region thermal power systems. Conclusion: The performed time domain simulations results demonstrate the effectiveness of the proposed FO Fuzzy PID controller and show that it has better performance than that of PID, FOPID and Fuzzy PID controllers. The suggested approach is reached out to the more practical multi-region power system. Thus, the worthiness and adequacy of the proposed technique are verified effectively.

scholarly journals Ant Lion Optimized Fractional Order Fuzzy Pre-Compensated Intelligent Pid Controller for Frequency Stabilization of Interconnected Multi-Area Power Systems

2019 ◽  
Vol 2 (2) ◽  
pp. 17 ◽  
Author(s):  
A. H. Gomaa Haroun ◽  
Yin-Ya Li
Keyword(s):  
Power Systems ◽  
Power System ◽  
Fractional Order ◽  
Frequency Control ◽  
Absolute Error ◽  
Load Frequency Control ◽  
Computational Technique ◽  
Intelligent Pid ◽  
Ant Lion ◽  
Simulation Results

Load frequency control (LFC) is considered to be the most important strategy in interconnected multi-area power systems for satisfactory operation and distribution. In order to transfer reliable power with acceptable quality, an LFC mechanism requires highly efficacy and intelligent techniques. In this paper, a novel hybrid fractional order fuzzy pre-compensated intelligent proportional-integral-derivative (PID) (FOFP-iPID) controller is proposed for the LFC of a realistic interconnected two-area power system. The proposed FOFP-iPID controller is incorporated into the power system as a secondary controller. In doing so, the parameters of the suggested FOFP-iPID controller are optimized using a more recent evolutionary computational technique called the Ant lion optimizer (ALO) algorithm utilizing an Integral of Time multiplied Absolute Error (ITAE) index. Simulation results demonstrated that the proposed FOFP-iPID controller achieves better dynamics performance under a wide variation of load perturbations. The supremacy of the proposed FOFP-iPID controller is demonstrated by comparing the results with some existing controllers, such as fractional order PID (FOPID) and fractional order intelligent PID (FOiPID) controllers for the identical system. Finally, the sensitivity analysis of the plant is examined and the simulation results showed that the suggested FOFP-iPID controller is robust and performs satisfactorily despite the presence of uncertainties.

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