A robust PID controller for load frequency control of single area re-heat thermal power plant using elephant herding optimization techniques

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

International Journal of Engineering Research in Africa ◽

10.4028/www.scientific.net/jera.50.79 ◽

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.

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Voltage and frequency control in conventional and PV integrated power systems by a particle swarm optimized Ziegler–Nichols based PID controller

SN Applied Sciences ◽

10.1007/s42452-021-04327-8 ◽

2021 ◽

Vol 3 (3) ◽

Author(s):

Arabinda Ghosh ◽

Anjan Kumar Ray ◽

Md. Nurujjaman ◽

Mo Jamshidi

Keyword(s):

Power Plant ◽

Power Systems ◽

Thermal Power Plant ◽

Pid Controller ◽

Frequency Control ◽

Thermal Power ◽

Particle Swarm ◽

Objective Functions ◽

Performance Improvements ◽

Frequency Variations

AbstractVariations of load demands, expansion of power system by interconnections among different areas and integration of renewable energy sources bring new challenges for stable, reliable and uninterrupted operations of power systems. In this paper, a control technique is proposed to control and optimize the performances of the three models having importance in the present and future energy systems. These are the output variations of an automatic voltage regulation (AVR) system, frequency variations in a load frequency control (LFC) system of a thermal power plant and frequency variations of a PV integrated thermal power plant. The proposed controller is a particle swarm optimized Ziegler–Nichols (ZN) method based proportional-integral-derivative (PID) controller. A particle swarm optimization (PSO) method suffers from the unavailability of prior knowledge of initial values of parameters. Whereas, the classical ZN method leaves the scope for performance improvements of a system. A rejuvenation to the classical ZN method is proposed by integrating PSO. The combined effect optimizes the voltage and the frequency performances, while ensuring system stability. Additionally, different objective functions inspired from energy industry requirements are considered to demonstrate performance improvements of the systems (e.g. maximum overshoot, steady-state error, settling time). The robustness of the proposed method is demonstrated by considering parametric uncertainty in the system. The proposed method is compared with performances of different controllers (e.g. PI, fuzzy PI, fuzzy PID), different iterative soft computing methods (e.g. pattern search, artificial bee colony, different variants of PSO) and classical optimization method (e.g. linear matrix inequality) considering different objective functions and different load disturbances for the aforementioned models. It is also observed that better performances are obtained using a significantly less number of iterations.

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