Application of Modified Biogeography Based Optimization in AGC of an Interconnected Multi-Unit Multi-Source AC-DC Linked Power System

Application of Modified Biogeography Based Optimization in AGC of an Interconnected Multi-Unit Multi-Source AC-DC Linked Power System

Dipayan Guha, Provas Kumar Roy, Subrata Banerjee
Copyright: © 2016 |Pages: 18
DOI: 10.4018/IJEOE.2016070101
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Abstract

An attempt has been made for the effective application of biogeography based optimization and its modified version to solve load frequency control (LFC) problem. Two-area interconnected multi-unit multi-source power system having thermal, hydro and gas power plant without and with AC-DC link is considered for study. Proportional-integral-derivative controller is used as secondary controller in LFC system and its gains are tuned by proposed algorithms through minimization of integral time absolute error based objective function. The results confirm the effectiveness of proposed algorithms after comparing results with other evolutionary algorithms like differential evolution (DE), teaching learning based optimization (TLBO) for the similar test system. The robustness of proposed algorithm is checked with different objective functions like integral square error, integral absolute error, integral time square error criterions and under different loading conditions. Critical analysis of results reveals that proposed method gives better performance than that obtained with DE, TLBO.
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1. Introduction

Modern power system network becomes more and more complicated with increasing of load demand. To ensure quality of electric power supply with stability, high efficiency and high reliability under normal and disturbed conditions, consistency of system frequency and interchange power has to be maintained “Sudha, Raju, Sekhar (2012)”. Power system network comprises several controlled area connected by tie-line. Stabilizing area frequency and interchange power oscillations after sudden step load perturbation (SLP) are the main concerns of power system engineers which lead to the attention in automatic generation control (AGC) or load frequency control (LFC) “Khodabakhshian, Pour, Hooshmand (2012)”. LFC is an important area of power system operation and control. The main objectives of AGC are: (i) maintain system frequency and tie-line power to their scheduled values, (ii) to mismatch power allocation among the units within each control area at their scheduled values.

A multitude technique is available in the literature to ensure better solutions of LFC problem over last two-three decades. Classical PI-controller “Sathya, Ansari (2015)”, “Sahu, Panda, Sekhar (2015)” is the most widely used controller strategy in LFC area due to its simplicity and applicability. Literature review reveals that optimum design of proportional plus integral (PI) controller gives week transient performance, therefore researchers proposed proportional plus integral plus derivative (PID) controller to improve the dynamic responses of the system instead of PI-controller “Bahgaat, Sayed, Hassan and Bendary (2014)”, Mohanty, Panda, Hota (2014)”, “Sahu, Panda, Padhan (2015)”. Apart from classical control techniques, many advanced methods have been applied to LFC area, like H control “Dey, Ghosh, Ray, Rakshit (2012)”, intelligent controller “Prakash, Sinha (2014)”, “Karnavas (2010)”, sliding mode based controller “Ouassaida, Maaroufib, Cherkaoui (2012)”, reinforced learning neural network “Saikia, Mishra, Sinha, Nanda (2011)”, fractional order based controller “Debbarma, Saikia, Sinha (2014)”, fuzzy logic controller “Arya, Mathur, Gupta (2012)” etc. “Sabahi, Ghaemi, Pezeshki (2014)” proposed type-II fuzzy logic controller based on feedback error learning approach and highlights effectiveness of designed controller by comparative analysis. “Yazdizadeh, Ramezani, Hamedrahmat (2012)” designed a decentralized robust optimal MISO PID controller based on characteristic matrix Eigen values and Lyapunov method for LFC problem and applied the designed controller to investigate the performances of power plant having two large dams in KHOZESTAN (a province in southwest of Iran).

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