Predictive Control of the Boost Inverter with Bypass Mode Connection for PV Microinverter Applications

In photovoltaic (PV) systems, the adoption of the single-stage microinverters present an attractive proposition. Unlike their two-stage counterparts, which consist of separate dc-dc and dc-ac conversion stages, single-stage microinverters simplify the conversion process by integrating both functions into a single unit. This combination offers advantages in terms of size, efficiency and overall system performance. In this context, the boost inverter with bypass mode connection emerges as an attractive alternative; however control challenges arise, particularly in the non-linearities inherent in these systems. The linearization process of the converter for conventional control strategies becomes complicated, promoting the exploration of alternative control approaches. This paper proposes a predictive control scheme for a Bypass Boost Inverter (BBI), addressing the aforementioned challenges. The control strategy employs a cascaded design, where the inner loop uses Finite Control Set-Model Predictive Control (FCS-MPC) to regulate inductor currents, indirectly controlling the output current for grid connection. The proposed control scheme is validated through simulations in PLECs software, demonstrating its performance in managing a PV panel. The results show good tracking of inductor current references and compliance with the standards for grid connection.

Authors

Institutions

Publication Details

Published
2024-11-03
DOI
https://doi.org/10.1109/iecon55916.2024.10984023
Primary Topic
Advanced DC-DC Converters
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive Control of the Boost Inverter with Bypass Mode Connection for PV Microinverter Applications

Diana López-Caiza, José Rodríguez, Felipe Ruiz, Matias Quijada
Advanced DC-DC Converters
article

Predictive Control of the Boost Inverter with Bypass Mode Connection for PV Microinverter Applications

Diana López-Caiza, José Rodríguez, Felipe Ruiz, Matias Quijada
article en

Abstract

In photovoltaic (PV) systems, the adoption of the single-stage microinverters present an attractive proposition. Unlike their two-stage counterparts, which consist of separate dc-dc and dc-ac conversion stages, single-stage microinverters simplify the conversion process by integrating both functions into a single unit. This combination offers advantages in terms of size, efficiency and overall system performance. In this context, the boost inverter with bypass mode connection emerges as an attractive alternative; however control challenges arise, particularly in the non-linearities inherent in these systems. The linearization process of the converter for conventional control strategies becomes complicated, promoting the exploration of alternative control approaches. This paper proposes a predictive control scheme for a Bypass Boost Inverter (BBI), addressing the aforementioned challenges. The control strategy employs a cascaded design, where the inner loop uses Finite Control Set-Model Predictive Control (FCS-MPC) to regulate inductor currents, indirectly controlling the output current for grid connection. The proposed control scheme is validated through simulations in PLECs software, demonstrating its performance in managing a PV panel. The results show good tracking of inductor current references and compliance with the standards for grid connection.

Universidad Andrés Bello (CL), San Sebastián University (CL)
Affordable and clean energy
Openalex Percentile: Top 72%
Advanced DC-DC Converters
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.