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Energy Systems

, Volume 9, Issue 2, pp 439–468 | Cite as

Symbiotic organism search algorithm applied to load frequency control of multi-area power system

  • Dipayan Guha
  • Provas Kumar Roy
  • Subrata Banerjee
Original Paper

Abstract

In this article, a novel powerful metaheuristic optimization technique called symbiotic organism search (SOS) is proposed for the first time to solve the load frequency control problem (LFC). SOS pretends the symbiotic interaction strategies accepted by an organism to sustain in the ecosystem. Initially, an interconnected two-area reheat thermal power plant equipped with proportional–integral–derivative (PID) controller is considered for design and analysis. PID controller gains are optimally selected using SOS algorithm employing integral time absolute error based fitness function. To confirm the superiority of SOS algorithm, an extensive comparative analysis is performed with some newly published optimization methods reported in the literature. Time domain simulation results show that the dynamic stability of the concerned power system is effectively enhanced with SOS. Furthermore, the performance of the proposed method is appraised by changing system loading settings and system constraints in the range of \(\pm 50\% \). To authenticate the tuning ability of proposed SOS algorithm, the study is extended to two more test systems, namely (1) an unequal nonlinear three-area power system and (2) two-area multi-unit thermal-hydro-wind-diesel power plant including generation rate constraint, governor dead band, boiler dynamics, and time delay nonlinearities. Comparison with existing LFC schemes validates the efficacy of SOS algorithm.

Keywords

Load frequency control Nonlinearities of power system Symbiotic organism search Transient analysis Robustness analysis 

Abbreviations

SOS

Symbiotic organism search

LFC

Load frequency control

ACE

Area control error

PID

Proportional integral derivative

EA

Evolutionary algorithm

ITAE

Integral time absolute error

ITSE

Integral time square error

ISE

Integral square error

IAE

Integral absolute error

TD

Time delay

GRC

Generation rate constraint

GDB

Governor dead band

TD

Time delay

BD

Boiler dynamics

SLP

Step load perturbation

BF

Beneficial factor

MV

Mutual vector

\(X_i\)

ith organism of ecosystem

\(X_{best} \)

Best organism

MDR

Minimum damping ratio

\(n_p \)

Population size

ub

Upper bound

lb

Lower bound

\(\dim \)

Dimension of control variable

\(T_{final} \)

Final simulation time

J

Fitness function

\(T_{sg} \)

Hydraulic time constant in sec

\(T_t \)

Time constant of steam turbine in sec

\(K_r \)

Gain of reheat unit

\(T_r \)

Reheat time constant in sec

\(T_{ps} \)

Time constant of power system in sec

\(K_{ps}\)

Gain of power system

\(R_i \)

Governor speed regulation constant of i th control area in Hz/pu MW

\(B_i \)

Frequency biasing constant of i th control area in pu MW/Hz

\(\Delta f_i \)

Frequency deviation of i th control area

\(\Delta P_{tie,i,j} \)

Tie-line power deviation between ith and jth control areas

\(N_1 ,N_2 \)

Fourier coefficients

\(\Delta P_D \)

Load perturbation in pu

\(k_p ,k_i ,k_d \)

Proportional, integral and derivative gains of PID-controller

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Dipayan Guha
    • 1
  • Provas Kumar Roy
    • 2
  • Subrata Banerjee
    • 3
  1. 1.Department of Electrical EngineeringDr. B C Roy Engineering CollegeDurgapurIndia
  2. 2.Department of Electrical EngineeringKalyani Government Engineering CollegeKalyaniIndia
  3. 3.Department of Electrical EngineeringNational Institute of Technology-DurgapurDurgapurIndia

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