Automatic generation control of a multi-area power system with renewable energy source under deregulated environment: adaptive fuzzy logic-based differential evolution (DE) algorithm


In this paper, an adaptive fuzzy logic-based differential evolution (DE) algorithm is proposed to optimize the gain of proportional–integral–derivative (PID) controllers. Using the proposed controller, the speed regulation parameters are tuned. Here, fuzzy logic is used to generate the controlled range of population set to DE algorithm. So that most favourable offspring population is created and the drawback of conventional DE algorithm is reduced. Using the proposed controller, the approximation errors and the external disturbance effects are minimized. The proposed method is implemented in MATLAB/Simulink working platform and the effectiveness is verified by multi-source two-area power generation system with renewable energy source. Three test cases are used to evaluate the simulation behaviour of proposed method. Simulation results of the tested power systems prove the effectiveness of the proposed load frequency control and proved its superiority over traditional PID controller, DE-tuned PID controller and fuzzy logic—DE algorithm-based PID controller. Comparison results show that proposed method has less overshoot, undershoot and fast settling time.

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Correspondence to S. Ajithapriyadarsini.

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Ajithapriyadarsini, S., Mary, P.M. & Iruthayarajan, M.W. Automatic generation control of a multi-area power system with renewable energy source under deregulated environment: adaptive fuzzy logic-based differential evolution (DE) algorithm. Soft Comput 23, 12087–12101 (2019).

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  • Multi-area system
  • Deregulation
  • PID tuning
  • Adaptive fuzzy logic
  • DE algorithm