A Hybrid Search Group Algorithm and Pattern Search Optimized PIDA Controller for Automatic Generation Control of Interco
A hybrid Search Group Algorithm (SGA) and Pattern Search (hSGA-PS) technique with the PIDA controller, to deal with Automatic Generation Control (AGC) of power system is presented. In the first stage, three nonlinear power systems with PID controller is c
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Abstract A hybrid Search Group Algorithm (SGA) and Pattern Search (hSGAPS) technique with the PIDA controller, to deal with Automatic Generation Control (AGC) of power system is presented. In the first stage, three nonlinear power systems with PID controller is considered and the controller parameters are tuned by SGA. The supremacy of the SGA -tuned PID-controlled AGC system is demonstrated by comparing the published Firefly Algorithm (FA) optimization procedure for the same interconnected power system. Then in the second stage, the PID controller is replaced with Proportional–Integral–Derivative and Acceleration (PIDA) controller and the optimum gains of the PIDA controller are optimized employing the SGA technique. It has been demonstrated that SGA-tuned PIDA controller improves the performance significantly compared with the SGA -tuned PID controller. Pattern Search (PS), a local optimization method is used in the third stage to fine-tune the PIDA controller parameters delivered by the SGA. The advantage of the hSGAPS-tuned PIDA controller over the SGA-tuned PIDA controller, SGA-tuned PID controller, FA-tuned PID controller is demonstrated. Furthermore, in the sensitivity analysis, the system parameters, operation load conditions, and the location of disturbance are changed and the results are analyzed. The performance and results from the sensitivity analysis reveal the effectiveness of the hSGA-PS-tuned PIDA controller aimed at AGC of the power system.
S. Nayak · S. Kar Department of Electrical Engineering, ITER, Sikha ‘O’ Anusandhan University, Bhubaneswar, Odisha, India e-mail: [email protected] S. Kar e-mail: [email protected] S. S. Dash (B) Department of Electrical Engineering, Government College of Engineering Keonjhar, Keonjhar, Odisha, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2021 S. S. Dash et al. (eds.), Intelligent Computing and Applications, Advances in Intelligent Systems and Computing 1172, https://doi.org/10.1007/978-981-15-5566-4_27
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Keywords Automatic generation control (AGC) · Governor dead band (GDB) · Generation rate constraint (GRC) · PIDA controller · Search group algorithm (SGA) · Pattern search (PS)
1 Introduction In the multi-area power system, units of individual areas are interconnected with another area via transmission lines. If real power load changes abruptly, the frequency of the power system and the power flow in tie line changes from its nominal value. The deviations are due to the difference between the electrical load demand and generation and cause unwanted effects. Automatic Generation Control (AGC) in each area regulates the generator set point automatically for the corresponding load change by calculating and driving Area Control Error (ACE) to zero [1–4]. Therefore, an effort is made for the design of the PIDA controller for AGC which is tuned by the hSGA-PS technique. The aim of this work is of threefold: (i) to exhibit the superiority of new powerful computational intelligence technique lik
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