Investigation of multi-level inverters and intelligent control methods for power circuit of grid-connected fuel cells

In grid-connected power generation systems, dc-link voltage control is needed to prevent energy losses, reduce voltage fluctuations and provide a stable energy flow. In addition, control of the power factor via the voltage source inverter is a process that supports the efficient use of the energy produced. Moreover, keeping the total harmonic distortion (THD) of the current injected into the grid in accordance with IEEE-519 harmonic standards (<5%), will increase the quality of the grid electrical current. In this thesis, the circuit structure and total harmonic distortion performances of multilevel inverters and also, three different methods for dc-link control (cascade pi-based, adaptive network-based fuzzy inference system (ANFIS) and artificial neural networks (ANN)-based control methods) were investigated. In addition, a three-level neutral point clamping (NPC) inverter is modeled for grid-connected proton exchange membrane fuel cells (PEMFC) due to its high power factor and low harmonic distortion performance. Moreover, the grid-connected fuel cell three-phase circuit topology is modeled. The rated power of the proposed system is 50 kW and the system was tested under five different operation scenarios. According to the performance results, the THD in the grid current has been reduced from 8.02% to 3.52% on avarage compared to traditional methods, dc-link voltage ripple was observed to be around 1V (<1%), and also the power factor regulation performance increased as unity (>0.99).