Spider Monkey Optimization Based Cascade Controller for LFC of a Hybrid Power System

7 Pages Posted: 28 Mar 2019

See all articles by Debasisa Tripathy

Debasisa Tripathy

National Institute of Technology (NIT), Silchar - Department of Electrical Engineering

B. K. Sahu

Siksha O Anusandhan University (SOA) - Department of Electrical Engineering

Nalin B. Dev Choudhury

National Institute of Technology (NIT), Silchar - Department of Electrical Engineering

Subhojit Dawn

Siliguri Institute of Technology - Department of Electrical Engineering

Date Written: 2018

Abstract

This report proposed a proportional–derivative with filter cascaded with a proportional–integral (PDF-PI) controller optimally design by spider monkey optimization (SMO) algorithm for load frequency control (LFC). Firstly, a commonly used thermal-thermal two area system has been considered to validate the performance of SMO based proportional-integral (PI) controller over recently published PI controller designed with teaching learning-based optimization (TLBO), differential evolution (DE), hybrid bacterial foraging optimization-particle swarm optimization (hBFOA-PSO), BFOA, genetic algorithm (GA) and conventional Ziegler Nichols (ZN). Furthermore, to verify superiority of proposed cascade controller over conventional integralderivative (ID), PI and proportional-integral-derivative with filter ( PIDF) controller in SMO framework, the system extended to a hybrid one by incorporating distributed generation unit and diesel unit in area-1 & area-2 respectively along with thermal generating unit (considering nonlinearities). Additionally, a combination of redox flow battery energy storage system and high voltage-DC is used to improve the dynamic performance of the overall system. Finally, the robustness of the proposed controller verified by applying a random load pattern in area-1.

Suggested Citation

Tripathy, Debasisa and Sahu, B. K. and Dev Choudhury, Nalin B. and Dawn, Subhojit, Spider Monkey Optimization Based Cascade Controller for LFC of a Hybrid Power System (2018). International Journal of Computational Intelligence & IoT, Vol. 2, No. 4, 2018. Available at SSRN: https://ssrn.com/abstract=3361193

Debasisa Tripathy

National Institute of Technology (NIT), Silchar - Department of Electrical Engineering ( email )

Silchar
India

B. K. Sahu (Contact Author)

Siksha O Anusandhan University (SOA) - Department of Electrical Engineering ( email )

Bhubaneswar, 751030
India

Nalin B. Dev Choudhury

National Institute of Technology (NIT), Silchar - Department of Electrical Engineering ( email )

Silchar
India

Subhojit Dawn

Siliguri Institute of Technology - Department of Electrical Engineering ( email )

Siliguri, 734009
India

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