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Design and Implementation of FIPID Controller for LFC of Multi-unit Multi-source Linear/Non-linear Power System

Design and Implementation of FIPID Controller for LFC of Multi-unit Multi-source... Due to dynamic load on interconnected power system, the system frequency tends to vary. It is important to balance the active power demand and active power generation at all the time in order to minimise the deviation of frequency in interconnected power system. The control mechanism by which the demand and generation is balanced in order to minimise the frequency deviation is known as load frequency control (LFC). This article explains the load frequency control (LFC) in multi-area multi-unit interlinked linear as well as nonlinear power system by employing fuzzy logic integrated PID (FIPID) controller. A PID controller is also separately implemented for performance comparison. Every control area in the system possesses with a non-reheat thermal plant and a hydro plant. The parameters of the implemented controllers are fine-tuned by application of teaching learning based optimisation (TLBO) algorithm and modified sine cosine algorithm (MSCA) separately using integral time absolute error (ITAE) as the fitness function. Thus, four different controllers are implemented to study the LFC issues and the four controllers so implemented are TLBO-PID, MSCA-PID, TLBO-FIPID and MSCA-FIPID controllers. A comparative performance analysis is accomplished between these controllers by injecting an instantaneous load of 1.5% in area-1. At last, the robustness of the proposed MSCA-FIPID controller is examined by performing the sensitivity analysis and injecting a random step load in area-1 of the power system in presence of communication delay and system nonlinearities. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Technology and Economics of Smart Grids and Sustainable Energy Springer Journals

Design and Implementation of FIPID Controller for LFC of Multi-unit Multi-source Linear/Non-linear Power System

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References (29)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2021
eISSN
2199-4706
DOI
10.1007/s40866-021-00121-y
Publisher site
See Article on Publisher Site

Abstract

Due to dynamic load on interconnected power system, the system frequency tends to vary. It is important to balance the active power demand and active power generation at all the time in order to minimise the deviation of frequency in interconnected power system. The control mechanism by which the demand and generation is balanced in order to minimise the frequency deviation is known as load frequency control (LFC). This article explains the load frequency control (LFC) in multi-area multi-unit interlinked linear as well as nonlinear power system by employing fuzzy logic integrated PID (FIPID) controller. A PID controller is also separately implemented for performance comparison. Every control area in the system possesses with a non-reheat thermal plant and a hydro plant. The parameters of the implemented controllers are fine-tuned by application of teaching learning based optimisation (TLBO) algorithm and modified sine cosine algorithm (MSCA) separately using integral time absolute error (ITAE) as the fitness function. Thus, four different controllers are implemented to study the LFC issues and the four controllers so implemented are TLBO-PID, MSCA-PID, TLBO-FIPID and MSCA-FIPID controllers. A comparative performance analysis is accomplished between these controllers by injecting an instantaneous load of 1.5% in area-1. At last, the robustness of the proposed MSCA-FIPID controller is examined by performing the sensitivity analysis and injecting a random step load in area-1 of the power system in presence of communication delay and system nonlinearities.

Journal

Technology and Economics of Smart Grids and Sustainable EnergySpringer Journals

Published: Dec 8, 2021

Keywords: Load frequency control; Governor dead band; Area control error; Generation rate constraint; FIPID controller; Objective function; Teaching learning based optimisation; Modified sine cosine algorithm; Transient response

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