Gudimindla, H.K, M.S.2026-02-052020Sustainable Energy Technologies and Assessments, 2020, 42, , pp. -22131388https://doi.org/10.1016/j.seta.2020.100800https://idr.nitk.ac.in/handle/123456789/23571Power flow control and peak point tracking are significant in grid-tied renewable energy systems to improve power factor and efficient energy extraction. In this paper, the design of robust controllers for the power electronic converters of the grid-connected PEM fuel cell with thermal modeling is deliberated. Further, the transfer function model of the power electronic converters is derived by considering uncertainty in system parameters. A low complexity algorithm is used to design the converter parameters from the uncertainty range. The proposed robust automated power flow controller is designed to minimize the objective function using a genetic algorithm in the quantitative feedback theory framework. The robustness and disturbance rejection with enhanced transient response of the proposed controller is evaluated under heavy and light loading conditions, DC-link voltage and grid voltage distortion uncertainty conditions are investigated. Finally, comprehensive simulations are performed to validate the proposed controller performance with the existing controller under the above-mentioned uncertainty conditions. © 2020 Elsevier LtdComputational complexityControllersDisturbance rejectionElectric load flowElectric power transmission networksEnergy efficiencyFlow controlGenetic algorithmsPower controlPower convertersPower electronicsProton exchange membrane fuel cells (PEMFC)Renewable energy resourcesTransient analysisDesign of robust controllersDynamic performance evaluationsGrid-voltage distortionLow complexity algorithmPower electronic convertersQuantitative feedback theoryRenewable energy systemsTransfer function modelElectric power system controlcontrol systemdesigndynamic analysisdynamic responsefuel cellgenetic algorithmmodelingquantitative analysistransfer functionuncertainty analysis