Performance Analysis of a Dual Buck-Boost Grid-Connected Photovoltaic Inverter System under Mismatched Environmental Conditions
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- 12 hours ago
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Abstract
This research presents a comprehensive performance analysis of a dual buck-boost based grid-connected photovoltaic (PV) inverter system designed to mitigate the deleterious effects of mismatched environmental conditions. In multi-panel PV arrays, non-uniform irradiance significantly compromises power extraction and grid stability. This study proposes a dual-stage architecture where each PV source is regulated by an independent buck-boost converter stage, enabling independent Maximum Power Point Tracking (MPPT) before centralized inversion. Using a MATLAB/Simulink environment, the system's dynamic response was evaluated under step-variable irradiance. The control framework integrates a precise transition logic between buck and boost modes, utilizing PI controllers to regulate inductor current references derived from instantaneous power demands. The findings demonstrate that the proposed dual buck-boost architecture effectively decouples the PV sources, optimizing power yield from each module independently. Furthermore, the implementation of a Phase Locked Loop (PLL) ensures robust grid synchronization, maintaining an in-phase relationship between grid voltage and current, thereby achieving near-unity power factor despite rapid environmental fluctuations.
Keywords
Dual Buck-Boost Converter, MPPT, Grid-Connected Inverter, Mismatched Irradiance, Power Electronics
2. I. Introduction
The strategic integration of high-penetration renewable energy into the utility grid necessitates advanced power electronic topologies capable of maintaining high efficiency and power quality. A critical challenge in photovoltaic (PV) system design is mismatched environmental conditions, where individual panels within an array experience disparate irradiance level due to localized shading, debris, or varying orientations. Such discrepancies lead to non-linearities in the P–V characteristics, which conventional single-stage conversion architectures struggle to resolve, often resulting in significant power loss and suboptimal resource utilization.
Single-stage systems typically impose a uniform voltage constraint across the PV string, failing to account for the unique Maximum Power Point (MPP) of individual modules under mismatch. The dual buck-boost topology serves as a critical differentiator by providing independent DC-DC regulation for each PV source. This configuration effectively decouples the control of the PV interface from the grid-side requirements, ensuring that each source is regulated at its specific MPP. Furthermore, this architecture facilitates DC-link stabilization and harmonic minimization, enhancing the overall reliability of the power injection.
The objective of this paper is to mathematically formalize and validate a dual buck-boost control logic optimized for grid-connected operations. Through rigorous simulation, the interleaving of MPPT, PI current regulation, and PLL synchronization is demonstrated to mitigate environmental mismatch and optimize system-wide energy yield.
3. II. System Configuration and Proposed Methodology
The structural necessity of the dual buck-boost topology stems from the requirement to manage two distinct PV sources (PV1 and PV2) with non-identical characteristics. The architectural flow originates at the PV panels, which feed into independent buck-boost converter stages. These stages are connected to a common DC-link, which subsequently supplies a single-phase H-bridge inverter for grid connection.
System Components
The architectural framework consists of the following primary functional blocks:
· PV Sources (PV1 & PV2): Independent solar modules providing variable DC inputs based on irradiance levels.
· Dual Buck-Boost Stage: Two independent converters utilizing switches S1 through S4, designed to step the voltage up or down to satisfy MPPT requirements and maintain the DC-link.
· Single-Phase H-Bridge Inverter: A bridge topology using switches S5–S8, responsible for modulating the DC output into a high-quality AC waveform for grid injection.
· Integrated Control Layer: A control interface comprising MPPT algorithms, PI controllers for current and power regulation, and synchronization logic.
The dual buck-boost stage decouples the PV source control from grid-side demands, enabling independent optimization of each panel’s duty cycle. As a result, irradiance fluctuations in PV1 do not adversely affect power extraction from PV2.
A robust mathematical control layer is required to coordinate these stages during variable atmospheric conditions.
4. III. Control Strategy and Mathematical Modeling
The control system coordinates the interleaving of the MPPT loops and the dual-mode (Buck/Boost) converter logic. The primary objective is to regulate the inductor current to match a reference derived from instantaneous power and threshold voltages.
PV Interface and Reference Generation
The MPPT algorithm identifies the optimal power and and corresponding voltage references. These values are processed to calculate the control thresholds and equivalent resistance . The control sequence is:
MPPT → PI Controller → Power Reference → Calculation
The inductor current reference is derived as:
Where represents the panel voltage and represents the control threshold.
Operating modes are determined as follows:
· Buck Mode:
· Boost Mode:
Duty Cycle Generation
The duty cycles and are generated by comparing the actual inductor current with using a PI controller. Let be the PI controller output:
· For : ,
· Otherwise (Boost Mode): ,
Inverter Control Strategy
The H-bridge inverter (S5–S8) is controlled using a Phase Locked Loop (PLL) for grid synchronization. The PLL tracks the grid voltage and extracts the phase angle , generating a unit sine wave synchronized with the utility.
This ensures that the injected current remains perfectly in-phase with the grid voltage, achieving unity power factor and minimizing reactive power circulation. This framework ensures stability during mode transitions.
5. IV. Simulation Model and Parameters
MATLAB/Simulink was used to validate the proposed topology and evaluate the dynamic response of the control loops under non-linear operating conditions.
Simulation Parameters
The model evaluates resilience to environmental mismatch by maintaining PV2 at constant irradiance while subjecting PV1 to a stepped irradiance profile.
Parameter | Value / Description |
PV2 Irradiance | Fixed at 1000 W/m² |
PV1 Irradiance | Step-variable (500 → 600 → 700 → 800 → 900 → 1000 W/m²) |
Controller | PI-based current and power regulation |
Modulation | SPWM via PLL |
Converter Switches | S1, S2, S3, S4 |
Inverter Switches | S5, S6, S7, S8 |
The control blocks utilize the error between MPPT-generated and actual to drive the PI controllers, ensuring accurate power tracking throughout the simulation.
6. V. Results and Discussion
Performance evaluation focused on DC-link stability and grid current quality during irradiance transients applied to PV1.
PV Output Analysis
Analysis of PV power , voltage , and current confirms the effectiveness of the decoupling stage. PV2 maintained constant output at 1000 W/m², while PV1 exhibited synchronized step increases in power and current as irradiance increased from 500 W/m² to 1000 W/m². Seamless transitions between voltage levels were observed without perturbing the adjacent PV stage, indicating high tracking accuracy.
Grid-Side Performance
Grid-side waveforms demonstrate successful SPWM and PLL synchronization. Grid voltage and current remain perfectly in-phase, confirming high power factor operation and effective DC-link regulation for high-quality AC injection.
The results confirm that the dual-mode control strategy effectively mitigates environmental mismatch and ensures optimized energy yield with robust grid interaction.
7. VI. Conclusion and Future Scope
This study validates the dual buck-boost topology as an effective solution for grid-connected PV systems operating under mismatched environmental conditions. Independent converter stages and current-mode control overcome the limitations of single-stage architectures, providing enhanced power extraction and DC-link stability.
Key contributions include the formulation of based on power demand, seamless buck–boost transitions, and near-unity power factor operation using PLL synchronization. Simulation results confirm stable performance under rapid irradiance variations.
Future work will focus on integrating AI-based MPPT methods such as Fuzzy Logic and Particle Swarm Optimization to improve tracking speed under partial shading. Hardware-in-the-Loop (HIL) testing is also proposed to validate real-time controller robustness.
VII. YouTube Video
VIII. Purchase link of the Model
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