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• W2085514298 abstract "This article presents automatic generation control (AGC) of a two-area interconnected power system with diverse energy sources using the bacteria foraging optimization technique. The control areas of interconnected power systems consist of hydro, thermal, and gas power plants. In this study, the proportional-integral-derivative (PID) structures of AGC regulators are designed for various case studies identified herein. An artificial intelligent optimization algorithm using the modeling behavior of E. Coli bacteria present in human intestines, is applied to tune the gains of PID structured AGC regulators. The closed-loop system dynamic response plots are obtained with designed AGC regulators for various power system models. The effectiveness of the proposed AGC regulators is demonstrated in the wake of a 1% step load disturbance in one of the control areas. It has been shown that the system dynamic responses subject to a step load disturbance are superior over other power plant combinations in a control area with only thermal and gas power plants participating in the AGC schemes, and it is sluggish/poor when only hydro power plants participated in the AGC scheme as one of the diverse sources in the power system." @default.
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• W2085514298 date "2014-12-31" @default.
• W2085514298 modified "2023-09-26" @default.
• W2085514298 title "Automatic Generation Control in an Interconnected Power System Incorporating Diverse Source Power Plants Using Bacteria Foraging Optimization Technique" @default.
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• W2085514298 doi "https://doi.org/10.1080/15325008.2014.975871" @default.
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