Particle swarm optimisation-based parameters optimisation of PID controller for load frequency control of multi-area reheat thermal power systems

2017 ◽  
Vol 9 (5/6) ◽  
pp. 464 ◽  
Author(s):  
K. Jagatheesan ◽  
B. Anand ◽  
Sourav Samanta ◽  
Nilanjan Dey ◽  
Amira S. Ashour ◽  
...  
Keyword(s):  
Power Systems ◽  
Pid Controller ◽  
Frequency Control ◽  
Thermal Power ◽  
Particle Swarm ◽  
Particle Swarm Optimisation ◽  
Load Frequency Control ◽  
Load Frequency

Optimal Design of PID Controller Based Sampe-Jaya Algorithm for Load Frequency Control of Linear and Nonlinear Multi-Area Thermal Power Systems

2020 ◽  
Vol 50 ◽  
pp. 79-93
Author(s):  
Adel A. Abou El Ela ◽  
Ragab A. El-Sehiemy ◽  
Abdullah M. Shaheen ◽  
Abd El Galil Diab
Keyword(s):  
Optimal Design ◽  
Power Systems ◽  
Pid Controller ◽  
Frequency Control ◽  
Thermal Power ◽  
Absolute Error ◽  
Load Frequency Control ◽  
Jaya Algorithm ◽  
Load Frequency ◽  
The Impact

Modern multi-area power systems are in persistent facing to imbalances in power generation and consumption which directly causes frequency and tie-line power fluctuations in each area. This paper deals with the load frequency control (LFC) problem where the control objective of regulating their error signals despite the presences of several external load disturbances. It proposes an optimal design of proportional integral derivative controller (PID) based on a novel version of Jaya algorithm called self-adaptive multi-population elitist (SAMPE) Jaya optimizer. A filter with derivative term is integrated with PID controller to alleviate the impact of noise in the input signal. A time domain based-objective functions are investigated such as integral time-multiplied absolute value of the error (ITAE) and integral of absolute error (IAE). Both SAMPE-Jaya and Jaya optimizers are employed to optimally tune the PID parameters for interconnected power systems comprising two non-reheat thermal areas. Three test cases are performed with various load disturbances in both areas individually and simultaneaously. Also, the practical physical constraints related to generation rate constraint (GRC) with its nonlinearity characteristics are taken into account. In addition, the obtained results using the designed PID controller based on SAMPE-Jaya are compared with various reported techniques. These simulated comparisons declare the great efficiency and the high superiority of the designed PID controller based on SAMPE-Jaya.

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.

Grey Wolf Optimization to Solve Load Frequency Control of an Interconnected Power System

2016 ◽  
Vol 5 (4) ◽  
pp. 62-83 ◽  
Author(s):  
Dipayan Guha ◽  
Provas Kumar Roy ◽  
Subrata Banerjee
Keyword(s):  
Power System ◽  
Pid Controller ◽  
Frequency Control ◽  
Thermal Power ◽  
Load Frequency Control ◽  
Fine Tuning ◽  
Average Error ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Load Frequency

In this article, a novel optimization algorithm called grey wolf optimization (GWO) with the theory of quasi-oppositional based learning (Q-OBL) is proposed for the first time to solve load frequency control (LFC) problem. An equal two-area thermal power system equipped with classical PID-controller is considered for this study. The power system network is modeled with governor dead band and time delay nonlinearities to get better insight of LFC system. 1% load perturbation in area-1 is considered to appraise the dynamic behavior of concerned power system. Integral time absolute error and least average error based fitness functions are defined for fine tuning of PID-controller gains employing the proposed method. An extensive comparative analysis is performed to establish the superiority of proposed algorithm over other recently published algorithms. Finally, sensitivity analysis is performed to show the robustness of the designed controller with system uncertainties.

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