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Automatic Generation Control Using Novel PD Plus FOPI Controller Tuned by Salp Swarm Algorithm

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Artificial Intelligence and Evolutionary Computations in Engineering Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1056))

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Abstract

To reduce the frequency variation problem, here a novel controller is projected named as proportional derivative plus fractional order proportional integral (PD plus FOPI) controller. The newly designed controller is realised in a dual control area-based multi-unit model. The desired and suitable value of the parameter of the projected controller is obtained by salp swarm algorithm (SSA) concerning integral time absolute error (ITAE) as fitness or cost function. The designed multi-unit model is inspected with proportional integral derivative (PID), proportional derivative plus proportional integral (PD plus PI) and PD plus FOPI controller, and the dominance of the projected PD plus FOPI controller is established over others concerning different performance indices such as least undershoot, settling time and maximum overshoot. The system response is surveyed under two circumstances, namely (i) an abrupt load deviation of magnitude 0.01 per unit in control area 1 and (ii) abrupt load deviation of magnitude 0.06 per unit in control area 1. The later investigation also reveals that projected controller is robust as it can successfully manage the frequency abnormalities without further tuning the controller gains.

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Correspondence to Nimai Charan Patel .

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Appendix 1

Appendix 1

\(T_{H} = 0.08\,{\text{s}}\), \(T_{T} = 0.3\,{\text{s}}\), \(T_{r} = 10\,{\text{s}}\), \(K_{r} = 0.5\), \(T_{P} = 20\,{\text{s}}\), \(K_{P} = 120\), \(R = 2.5\) Hz/MW, \(B = 0.425\) MW/Hz, \(T_{21} = 0.086\), \(\upalpha_{11} =\upalpha_{12} =\upalpha_{13} =\upalpha_{21} =\upalpha_{22} =\upalpha_{23} = 1/ 3\).

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Patel, N.C., Debnath, M.K., Sahu, B.K., Dash, S.S. (2020). Automatic Generation Control Using Novel PD Plus FOPI Controller Tuned by Salp Swarm Algorithm. In: Dash, S., Lakshmi, C., Das, S., Panigrahi, B. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 1056. Springer, Singapore. https://doi.org/10.1007/978-981-15-0199-9_1

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