Model Predictive Control of Grid-Connected Fuel cell/ Photovoltaic/Wind power System
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Abstract
This paper presents an optimal control strategy for a grid-connected hybrid power generation system utilizing hydrogen, solar, and wind energy. The main objective of paper is to develop a simple and efficient control strategy for the grid-connected hybrid system. The goal is to mitigate grid power fluctuations and ensure reliable load demand fulfillment. Hybrid Renewable Energy Systems (HRES) should be carefully designed with a suitable combination of various renewable energy sources to address the intermittent nature of these resources. The studied hybrid system incorporates three renewable energy sources: a photovoltaic subsystem, a wind energy subsystem, and a fuel cell subsystem. These three subsystems are connected to a common DC bus, which is then linked to the electric grid via an inverter. Each subsystem employs an MPPT algorithm to maximize power extraction. The combined extracted power is injected into the grid through the inverter. Model predictive control techniques are implemented to regulate the active and reactive power of the grid, as well as to maintain the DC bus voltage. Simulation results demonstrate the applicability and effectiveness of the proposed control methods.
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References
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