The uncertainties associated with multi-area power systems comprising both thermal and distributed renewable generation(DRG)sourcessuch assolar and wind necessitate the use of an efficient load frequency control(LFC...
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The uncertainties associated with multi-area power systems comprising both thermal and distributed renewable generation(DRG)sourcessuch assolar and wind necessitate the use of an efficient load frequency control(LFC)***,a hybrid version of two metaheuristic algorithms(arithmeticoptimization and africanvulture’soptimizationalgorithm)is *** is called the‘arithmeticoptimizedafricanvulture’soptimizationalgorithm(AOAVOA)’.Thisalgorithm is used to tune a novel type-2 fuzzy-based proportional–derivative branched with dual degree-of-freedom proportional–integral–derivative controller for the LFC of a three-area hybrid deregulated power ***,electric vehicle(EV),and DRG sources(including a solar panel and a wind turbine system)are con-nected in ***-2 involves thermal and gas-generating units(GUs),while thermal and geothermal units are linked in *** restrictionssuch as thermo-boiler dynamics,thermal-governor dead-band,and genera-tion rate constraints are also *** proposed LFC method is compared to other controllers and optimizers to demonstrate itssuperiority in rejecting step and random load *** functioning as energy storage ele-ments,EVs and DRG units can enhance dynamic responses during peak *** a result,the effect of the afore-mentioned units on dynamic reactions is also *** validate its effectiveness,the closed-loop system issubjected to robust stability analysis and is compared to various existing control schemes from the *** is determined that the suggested AOAVOA improves fitness by 40.20%over the arithmetic optimizer(AO),while fre-quency regulation is improved by 4.55%over an AO-tuned type-2 fuzzy-based branched controller.
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