scholarly journals Design of 2-Dof Pid Controller for Load Frequency Control of Two Area Power System using Mfo Algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 158-161
Keyword(s):  
Heuristic Algorithm ◽  
Optimization Algorithm ◽  
Pid Controller ◽  
Frequency Control ◽  
Load Frequency Control ◽  
The Other ◽  
Load Frequency ◽  
Integral Controller ◽  
Moth Flame Optimization Algorithm ◽  
Tie Line

The paper endeavours to analyse the load frequency control for two area system. In this paper, two areas has been considered in which non-reheated type of turbine in both area are used and whose secondary loop consists a latest controller called 2 degree-of-freedom PID (2-DOF-PID) controller. The parameter of the this controller is been optimized by the latest meta heuristic algorithm also called Moth flame optimization algorithm (MFO) to minimize the deviation in frequency of area and tie-line power respectively. The same processes are repeated with PID controller and Integral controller whose parameters are also optimized by MFO. A comparison is made among the result of these and 2-DOF-PID controller prove its superiority over the other controller for minimizing the deviation which occurs in frequency of the area as well as the tie-line power.

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.

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.

BFO Optimized Automatic Load Frequency Control of a Multi-Area Power System

2016 ◽  
pp. 369-412
Author(s):  
Pravat Kumar Ray ◽  
Sushmita Ekka
Keyword(s):  
Resource Utilization ◽  
Optimization Algorithm ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Simultaneous Optimization ◽  
Computational Burden ◽  
Load Frequency ◽  
Speed Regulation ◽  
Integral Controller ◽  
Bacteria Foraging Optimization Algorithm

This chapter presents an analysis on operation of Automatic Load Frequency Control (ALFC) by developing models in SIMULINK which helps us to understand the principle behind ALFC including the challenges. The three area system is being taken into account considering several important parameters of ALFC like integral controller gains (KIi), governor speed regulation parameters (Ri), and frequency bias parameters (Bi), which are being optimized by using Bacteria Foraging Optimization Algorithm (BFOA). Simultaneous optimization of certain parameters like KIi, Ri and Bi has been done which provides not only the best dynamic response for the system but also allows us to use much higher values of Ri than used in practice. This will help the power industries for easier and cheaper realization of the governor. The performance of BFOA is also investigated through the convergence characteristics which reveal that that the Bacteria Foraging Algorithm is quite faster in optimization such that there is reduction in the computational burden and also minimal use of computer resource utilization.

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.

scholarly journals Multi-Area Load Frequency Control of Hydro-Thermal-Wind Power Based on Improved Grey Wolf Optimization Algorithm

2020 ◽  
Vol 26 (6) ◽  
pp. 32-39
Author(s):  
Fannie Kong ◽  
Jinfang Li ◽  
Daliang Yang
Keyword(s):  
Wind Power ◽  
Optimization Algorithm ◽  
Pid Controller ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Grey Wolf Optimizer ◽  
Random Disturbance ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Load Frequency

The mathematical model of load frequency control is established in the interconnected power system of hydro, thermal, and wind for solving the problem of frequency instability in this paper. Besides, the improved grey wolf optimization algorithm (GWO) is presented based on the offspring grey wolf optimizer (OGWO) search strategy to handle local convergence for the GWO algorithm in the later stage. The experimental results show that the improved grey wolf algorithm has a superior optimization ability for the standard test function. The traditional proportional integral derivative (PID) controller cannot track the random disturbance of wind power in the hydro, thermal, and wind interconnected power grid. However, the proposed OGWO dynamically adjusts the PID controller control parameters to follow the wind power random disturbance, regional frequency deviation, and tie-line power deviation.

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