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


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.


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



Symbiotic organism search


Load frequency control


Area control error


Proportional integral derivative


Evolutionary algorithm


Integral time absolute error


Integral time square error


Integral square error


Integral absolute error


Time delay


Generation rate constraint


Governor dead band


Time delay


Boiler dynamics


Step load perturbation


Beneficial factor


Mutual vector


ith organism of ecosystem

\(X_{best} \)

Best organism


Minimum damping ratio

\(n_p \)

Population size


Upper bound


Lower bound

\(\dim \)

Dimension of control variable

\(T_{final} \)

Final simulation time


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


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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