scholarly journals Coordinated SMES and TCSC Damping Controller for Load Frequency Control of Multi Area Power System with Diverse Sources

2020 ◽  
Vol 12 (4) ◽  
pp. 747-769
Author(s):  
CH. Naga Sai Kalyan ◽  
◽  
G. Sambasiva Rao ◽  
Keyword(s):  
Power System ◽  
Pid Controller ◽  
Magnetic Energy ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Superconducting Magnetic Energy Storage ◽  
Load Frequency ◽  
Total Analysis ◽  
Magnetic Energy Storage ◽  
Tie Line

This paper investigates the load frequency analysis (LFC) of two area interconnected realistic power system with multi-fuel generating units. Each area consists of thermal, hydro and gas power generating plants. A new evolutionary algorithm is proposed, named Hybrid artificial electric field (HAEFA) optimization algorithm and integral square error (ISE) performance index is utilized to find classical PI/PID controller gains. Later, total analysis is carried out in presence of PID an account of its superiority functioning rather than PI. Moreover, the efficacy of the presented algorithm is deliberated by testing on two area conventional power system model of thermal unit with structure of non-reheat turbines and also on sphere benchmark function. As the load variation is dynamic in nature, mitigating the area frequency fluctuations and tie-line power variations could not been fulfilled by primary regulator and secondary controller. Effective governing needs additional devices. Therefore, superconducting magnetic energy storage (SMES) devices are incorporated in both areas in addition to Thyristor controlled series capacitor (TCSC) is connected in tie-line. Results, shows the system performance has been significantly improved with SMES and TCSC in the presence of HAEFA based PID controller. The potency of the HAEFA algorithm is compared with other optimizations covered in literature.

Improvement Of Load Frequency Control By Using Self–Tuning Controller

2012 ◽  
Author(s):  
M.R.I. Sheikh ◽  
M.S Anower ◽  
M. G. Rabbani
Keyword(s):  
Power System ◽  
Magnetic Energy ◽  
Frequency Control ◽  
Automatic Generation ◽  
Load Frequency Control ◽  
Superconducting Magnetic Energy Storage ◽  
Load Frequency ◽  
Self Tuning ◽  
Magnetic Energy Storage ◽  
Generation Control

Since a Superconducting Magnetic Energy Storage (SMES) unit with a self–commutated converter is capable of controlling both the active and reactive powers simultaneously and quickly, increasing attention has been focused recently on power system stabilization by SMES control. This paper presents a novel control method of SMES with a self-tuned Fuzzy Proportional Integral (FPI) controller associated with the Automatic Generation Control (AGC) for improving Load Frequency Control (LFC) in a single area power system. Boiler dynamics and nonlinearities such as governor dead band (DB) and generator rate constraints (GRC) are considered in the developed comprehensive mathematical model of a single area isolated power system. The effects of the self–tuning configuration of FPI controller in AGC on SMES control is compared with that of fixed gain PI controlled AGC. It is seen that with addition of FPI controller, SMES can perform a more effective primary frequency control for single area power system. Key words: Load frequency control; single area power system; automatic generation control; superconducting magnetic energy storage unit; fuzzy proportional integral controller

scholarly journals Load Frequency Control of Photovoltaic-Gasifier for Interconnected Two-Area Power Systems

2019 ◽  
Vol 9 (1) ◽  
pp. 2101-2105
Keyword(s):  
Power Systems ◽  
Power System ◽  
Pid Control ◽  
Pid Controller ◽  
Power Flow ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Interconnected Power System ◽  
Load Frequency ◽  
Tie Line

Load frequency control (LFC) in interconnected power system of small distribution generation (DG) for reliability in distribution system. The main objective is to performance evaluation load frequency control of hybrid for interconnected two-area power systems. The simulation consist of solar farm 10 MW and gasifier plant 300 kW two-area in tie line. This impact LFC can be address as a problem on how to effectively utilize the total tie-line power flow at small DG. To performance evaluation and improve that defect of LFC, the power flow of two-areas LFC system have been carefully studied, such that, the power flow and power stability is partially LFC of small DG of hybrid for interconnected two-areas power systems. Namely, the controller and structural properties of the multi-areas LFC system are similar to the properties of hybrid for interconnected two-area LFC system. Inspired by the above properties, the controller that is propose to design some proportional-integral-derivative (PID) control laws for the two-areas LFC system successfully works out the aforementioned problem. The power system of renewable of solar farm and gasifier plant in interconnected distribution power system of area in tie – line have simulation parameter by PID controller. Simulation results showed that 3 types of the controller have deviation frequency about 0.025 Hz when tie-line load changed 1 MW and large disturbance respectively. From interconnected power system the steady state time respond is 5.2 seconds for non-controller system, 4.3 seconds for automatic voltage regulator (AVR) and 1.4 seconds for under controlled system at 0.01 per unit (p.u.) with PID controller. Therefore, the PID control has the better efficiency non-controller 28 % and AVR 15 %. The result of simulation in research to be interconnected distribution power system substation of area in tie - line control for little generate storage for grid connected at better efficiency and optimization of renewable for hybrid. It can be conclude that this study can use for applying to the distribution power system to increase efficiency and power system stability of area in tie – line.

Load Frequency Control in Power System via Improving PID Controller Based on Particle Swarm Optimization and ANFIS Techniques

2015 ◽  
pp. 462-481 ◽  
Author(s):  
Naglaa K. Bahgaat ◽  
M. I. El-Sayed ◽  
M. A. Moustafa Hassan ◽  
F. A. Bendary
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Pid Controller ◽  
Frequency Control ◽  
Particle Swarm ◽  
Load Frequency Control ◽  
Swarm Optimization ◽  
Load Frequency ◽  
System Frequency ◽  
Tie Line

The main objective of Load Frequency Control (LFC) is to regulate the power output of the electric generator within an area in response to changes in system frequency and tie-line loading. Thus the LFC helps in maintaining the scheduled system frequency and tie-line power interchange with the other areas within the prescribed limits. Most LFCs are primarily composed of an integral controller. The integrator gain is set to a level that compromises between fast transient recovery and low overshoot in the dynamic response of the overall system. This type of controller is slow and does not allow the controller designer to take into account possible changes in operating conditions and non-linearities in the generator unit. Moreover, it lacks robustness. This paper studies LFC in two areas power system using PID controller. In this paper, PID parameters are tuned using different tuning techniques. The overshoots and settling times with the proposed controllers are better than the outputs of the conventional PID controllers. This paper uses MATLAB/SIMULINK software. Simulations are done by using the same PID parameters for the two different areas because it gives a better performance for the system frequency response than the case of using two different sets of PID parameters for the two areas. The used methods in this paper are: a) Particle Swarm Optimization, b) Adaptive Weight Particle Swarm Optimization, c) Adaptive Acceleration Coefficients based PSO (AACPSO) and d) Adaptive Neuro Fuzzy Inference System (ANFIS). The comparison has been carried out for these different controllers for two areas power system. Therefore, the article presents advanced techniques for Load Frequency Control. These proposed techniques are based on Artificial Intelligence. It gives promising results.

Load Frequency Control in Power System via Improving PID Controller Based on Particle Swarm Optimization and ANFIS Techniques

2014 ◽  
Vol 3 (3) ◽  
pp. 1-24 ◽  
Author(s):  
Naglaa K. Bahgaat ◽  
M. I. El-Sayed ◽  
M. A. Moustafa Hassan ◽  
F. A. Bendary
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Pid Controller ◽  
Frequency Control ◽  
Particle Swarm ◽  
Load Frequency Control ◽  
Swarm Optimization ◽  
Load Frequency ◽  
System Frequency ◽  
Tie Line

The main objective of Load Frequency Control (LFC) is to regulate the power output of the electric generator within an area in response to changes in system frequency and tie-line loading. Thus the LFC helps in maintaining the scheduled system frequency and tie-line power interchange with the other areas within the prescribed limits. Most LFCs are primarily composed of an integral controller. The integrator gain is set to a level that compromises between fast transient recovery and low overshoot in the dynamic response of the overall system. This type of controller is slow and does not allow the controller designer to take into account possible changes in operating conditions and non-linearities in the generator unit. Moreover, it lacks robustness. This paper studies LFC in two areas power system using PID controller. In this paper, PID parameters are tuned using different tuning techniques. The overshoots and settling times with the proposed controllers are better than the outputs of the conventional PID controllers. This paper uses MATLAB/SIMULINK software. Simulations are done by using the same PID parameters for the two different areas because it gives a better performance for the system frequency response than the case of using two different sets of PID parameters for the two areas. The used methods in this paper are: a) Particle Swarm Optimization, b) Adaptive Weight Particle Swarm Optimization, c) Adaptive Acceleration Coefficients based PSO (AACPSO) and d) Adaptive Neuro Fuzzy Inference System (ANFIS). The comparison has been carried out for these different controllers for two areas power system. Therefore, the article presents advanced techniques for Load Frequency Control. These proposed techniques are based on Artificial Intelligence. It gives promising results.

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