scholarly journals Optimization of Two Area AGC based Power System Using PSO Tuned Fuzzy PID Controller and PSO Trained SSSC And TCPS

2018 ◽  
Vol 7 (4.10) ◽  
pp. 163 ◽  
Author(s):  
Geoffrey Eappen ◽  
T. Shankar
Keyword(s):  
Power Systems ◽  
Power System ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Minimum Cost ◽  
Automatic Generation ◽  
Control Area ◽  
Fuzzy Pid ◽  
Particle Swarm Optimizer ◽  
System Frequency

Automatic generation control or AGC system is significant controlling system that operates efficiently to balance the load and generation in power system at minimum cost for economical operation. System frequency will vary from nominal value if there is mismatch occurs between generation and demand. Due to this high frequency deviation system may breakdown. A very fast, reliable and accurate controller is needed to maintain the system frequency within the range to maintain stability. In this paper the proposed model consisting of PID controller whose parameters have been optimized using PSO tuned Fuzzy Logic Controller and it’s been compared with conventional PSO-PID controller. Each control area in power systems includes the dynamics response of the systems. The results contained in this paper present the strength of the particle swarm optimizer for tuning the Fuzzy based PID controller parameter for two area power system network, for better performance PSO trained SSSC and TCPS has been introduced to the system. The enhancement in the dynamic response of the power system network is verified. The output response of the proposed work is compared with conventional PSO-PID & PSO Fuzzy-PID based AGC system. Simulation experiments so conducted in MATLAB showed that the proposed system outperformed the conventional one by achieving better response.  

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 Hybrid Fuzzy Load Frequency Controller for a Two Area Interconnected Power System

2012 ◽  
pp. 278-282
Author(s):  
U. Prasad ◽  
P.K. Mohanty ◽  
P.K. Chattopadhyaya ◽  
C.K. Panigrahi
Keyword(s):  
Power System ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Automatic Generation ◽  
Dynamic Responses ◽  
System Stability ◽  
Interconnected Power System ◽  
Stability Issues ◽  
System Frequency

This work addresses the special requirements of Automatic Generation Control in Modern interconnected Power system. In order to track the system frequency and handling the power system stability issues many control strategies has been suggested by the researchers .A new Hybrid fuzzy approach is introduced here .Fuzzy Logic controller with Mamdani interface having five member ship functions is tested with the Thermal Thermal and hydro thermal system Further hybrid Fuzzy controller is also tested with the same system and results are compared for the both The system Which is having Hybrid Fuzzy concept and thereby the response of frequency and tie line power can be improved substantially following a load change in any area. Further dynamic responses for small perturbation have been observed, considering HFLC and integral controller and the results of both have been compared.

A Hybrid PSO-LEVY Flight Algorithm Based Fuzzy PID Controller for Automatic Generation Control of Multi Area Power Systems

2017 ◽  
Vol 6 (2) ◽  
pp. 42-63 ◽  
Author(s):  
Ajit Kumar Barisal ◽  
Tapas Kumar Panigrahi ◽  
Somanath Mishra
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Pid Controller ◽  
Particle Swarm ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Fuzzy Pid ◽  
Swarm Optimization ◽  
Fuzzy Pid Controller ◽  
Generation Control

This article presents a hybrid PSO with Levy flight algorithm (LFPSO) for optimization of the PID controllers and employed in automatic generation control (AGC) of nonlinear power system. The superiority of the proposed LFPSO approach has been demonstrated with comparing to recently published Lozi map-based chaotic optimization algorithm (LCOA) and Particle swarm optimization to solve load-frequency control (LFC) problem. It is found that the proposed LFPSO method has robust dynamic behavior in terms of settling times, overshoots and undershoots by varying the system parameters and loading conditions from their nominal values as well as size and locations of disturbance. Secondly, a three-area thermal power system is considered with nonlinear as Generation Rate Constraints (GRC) and outperforms to the results of Bacteria Foraging algorithm based integral controller as well as hybrid Differential Evolution and Particle Swarm Optimization based fuzzy PID controller for the similar power system. Finally, the proficiency of the proposed controller is also verified by random load patterns.

Stability Analysis in RECS Integrated Multi-area AGC System with Modified- SOS Optimized Fuzzy Controller

2019 ◽  
Vol 12 (6) ◽  
pp. 532-542 ◽  
Author(s):  
Prakash Chandra Sahu ◽  
Ramesh Chandra Prusty
Keyword(s):  
Power System ◽  
Frequency Response ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Fitness Function ◽  
Automatic Generation ◽  
Settling Time ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Pi Controllers

Background: Automatic Generation Control (AGC) of multi-area nonlinear power system integrated with wind energy based Renewable Energy Conversion System (RECS). Methods: A fuzzy PID controller has been proposed for AGC of a three equal area thermal system integrated with RECS. Different physical nonlinear constraints like Governor Dead Band (GDB) and boiler dynamics are introduced in the model for realization of non linear and realistic of proposed multi area power system. To determine the optimum gain parameter, a Modified Symbiotic Organism Search (M-SOS) algorithm has been used along with a fitness function which based on Integral of Time Multiplied Absolute Error (ITAE). Results: For performance analysis, the performance of proposed M-SOS optimized fuzzy-PID controller is compared with PI, PID and fuzzy PI controllers. For technique comparison, performance of proposed M-SOS technique is compared with original SOS and conventional PSO algorithms. Robustness of proposed controller has also been verified by varying applied load and system parameters. Conclusion: It is observed that M-SOS technique exhibits improved performance over original SOS and PSO algorithms. It is also observed that proposed Fuzzy-PID controller provides better system performance than PI, PID and fuzzy PI controllers. It has been observed that the proposed M-SOS tuned fuzzy PID controller improves settling time of frequency response in area 1 by 11.30%, 15% and 17.75% compared to M-SOS tuned fuzzy PI, PID and PI controllers respectively. Significant improvements in settling time, peak overshoot and peak undershoot of the frequency response in area 2 and tie line power are observed with the implementation this proposed approach.

scholarly journals Automatic generation control of multi source interconnected power system using adaptive neuro-fuzzy inference system

2020 ◽  
Vol 12 (3) ◽  
pp. 66-80
Author(s):  
Deepesh Sharma
Keyword(s):  
Power System ◽  
Pid Controller ◽  
Fuzzy Inference ◽  
Frequency Control ◽  
Automatic Generation ◽  
Load Frequency Control ◽  
Inference System ◽  
Interconnected Power System ◽  
Small Peak ◽  
System Frequency

LFC (Load Frequency Control) difficulty is created by load of power system variations. Extreme acceptable frequency distinction is ±0.5 Hz which is  extremely intolerable. Here, LFC is observed by PID controller (PID-C), Fuzzy and ANFIS controller (ANFIS-C). To control different errors like frequency and area control error (ACE) in spite of occurrences of load disturbance and uncertainties of system is checked by MATLAB/SIMULINK software. Proposed Controller offers less, and small peak undershoot, speedy response to make final steady state. LFC is mandatory for reliability of  large interconnected power system. LFC is used to regulate power output of generator within specified area to maintain system frequency and  power interchange. Here, two area multi source LFC system is analyzed. ANFIS is utilized for tie-line power deviation and controlling frequency. Proposed controller is compared with other controller and it is found that proposed controller is better than other controller. Proposed controller is better in terms of Robustness. The output responses of interconnected areas have been compared on basis of peak-undershoot, peak-overshoot and settling time (Ts). Result of FLC is compared to that of with classical controller such as proportional derivative plus integral (PID) controller  which suggests that conventional controller is slow. Keywords: LFC, Fuzzy, PID, ANFIS, LFC; FLC; ACE; PID-C, AGC.

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