Multiple-Model Adaptive Control of a Hybrid Solid Oxide Fuel Cell Gas Turbine Power Plant Simulator

Abstract

A multiple model adaptive control (MMAC) methodology is used to control the critical parameters of a solid oxide fuel cell gas turbine (SOFC-GT) cyberphysical simulator, capable of characterizing 300 kW hybrid plants. The SOFC system is composed of a hardware balance of plant (BoP) component, and a high fidelity FC model implemented in software. This study utilizes empirically derived transfer functions (TFs) of the BoP facility to derive the MMAC gains for the BoP system, based on an estimation algorithm which identifies current operating points. The MMAC technique is useful for systems having a wide operating envelope with nonlinear dynamics. The practical implementation of the adaptive methodology is presented through simulation in the matlab/simulink environment.

Investigation of the Influence of Gas Turbine Power Stations on the Quality of Electric Energy in the Associated Petroleum Gas Utilization

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Research on the influence of fuel gas on energy characteristics of a gas turbine

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Study on an adaptive multi-model predictive controller for the thermal management of a SOFC-GT hybrid system

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