An Adaptive Control Technique Based Grid Connected Hybrid System Using High Gain Sepic Converter
Abstract
Abstract - For grid-connected hybrid systems, effective power conversion and clever control techniques are essential due to the growing use of renewable energy sources. In order to improve voltage regulation and power quality, this work offers a grid-connected hybrid energy system based on adaptive control techniques that uses a high-gain Single-Ended Primary Inductor Converter (SEPIC). The suggested hybrid system combines a number of renewable energy sources, including solar photovoltaic (PV) and battery energy storage, to provide dependable and continuous power delivery in a range of load and environmental circumstances. Wide voltage conversion ratios are achieved with less switching stress and more efficiency by using the high-gain SEPIC converter. In order to account for system uncertainties, renewable intermittency, and grid disruptions, an adaptive control technique dynamically modifies converter and inverter settings. During grid synchronisation, this control strategy guarantees steady DC-link voltage, efficient power sharing, and unity power factor operation. MATLAB/Simulink is used to model and simulate the system, and its performance is assessed under various operating conditions, such as variations in load, changes in irradiation, and grid failures. In comparison to traditional control techniques, simulation findings show increased grid compliance, lower harmonic distortion, quicker dynamic response, and greater voltage gain. Therefore, for contemporary grid-connected renewable energy applications, the suggested adaptive control-based hybrid system with a high-gain SEPIC converter provides an effective and dependable solution.
Fields of Study & Subjects
Microgrid Control and Optimization
Advanced DC-DC Converters
Multilevel Inverters and Converters
Publication details
- Journal / source
- INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
- Volume
- 10
- Issue
- 02
- Pages
- 1–9
- Publication date
- 11 February 2026
- Language
- EN