# Dual-Boost Inverter for PV Microinverter Application--An Assessment of Control Strategies
###### Abstract  
Photovoltaic (PV) microinverters have grown rapidly in the small-scale PV market, where typical two-stage converters are used to connect one PV module to the single-phase AC grid. This configuration achieves better performance in terms of energy yield compared with other PV configurations. However, the conversion efficiency of a two-stage system is the main drawback, especially when a high-voltage gain effort is required. In this context, single-stage microinverter topologies have been recently proposed since only one power conversion stage is required to extract the maximum power of the PV module and inject the AC power to the grid. This single-stage configuration allows considerable improvement of the overall efficiency of microinverters by reducing the number of elements in the system. However, the main challenge of these topologies is their control, since all variables of the converter are composed by the AC waveform with DC-bias. In this paper, four control strategies are analyzed for the mainstream single-stage topology, which is the dual-boost inverter (DBI). Classical linear control and three non-linear strategies, namely finite control set-model predictive control, flatness-based control, and sliding mode control, are detailed. The main contribution of this work is a complete comparison of the control strategies, to give insights into the most suitable control strategy for the DBI in PV microinverter application. photovoltaic energy; single-stage topologies; PV microinverter; FCS-model predictive control; flatness-based control; sliding mode control Article  
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the lowest efficiency among all PV system configurations (central, string, and multi-string configurations). In order to solve this issue, different types of topologies for the power converters have been proposed in the academic and industrial fields. Several of these PV microinverters were reviewed in [2; 3; 4; 5]. In the last few years, some research has focused on single-stage topologies since only one power stage is necessary to control the grid current and perform the MPPT, thus allowing increasing the efficiency. Among these single-stage topologies, the most common solution is the differential mode connection of two bidirectional DC-DC converters. The concept of the single-stage differential inverter is shown in Figure 1, where the output of each DC-DC converter is composed by a sinusoidal waveform with a DC-bias. The differential connection allows canceling the DC-bias, obtaining only the AC component at the output voltage. Differential inverters can be formed by any DC-DC converter topology; thus, the presence of galvanic isolation is optional and depends on the selected DC-DC converter topology. The dual-boost inverter (DBI), originally introduced in [6], is one of the most popular topologies of this type of connection. The power circuit of the DBI consists of two bidirectional DC-DC boost converters. The biggest underlying problems for single-stage topologies are the restrictions and challenges that arise from the control perspectives. In fact, these topologies are very difficult to control, because the operation point of each DC-DC converter presents large variations, making the linearization process a difficult task. Additionally, each variable of the inverter, including the duty cycle, is composed by DC and AC components. Since the DBI appeared in the 9090s [6], several control strategies have been proposed and developed in the academic field. These control strategies can be classified into two families, depending on the switching strategy: individual boost converter switching strategy and global switching strategy. In the first family, each DC-DC converter is controlled to generate a sinusoidal output voltage with a DC-bias, as shown in Figure 2a. Note that the output voltage of each DC-DC converter is independent of the output voltage of the inverter. The output current or voltage of the inverter is the main control objective in the second family, as seen in Figure 2b.