Adaptive Control of Grid-Connected Solar, Wind, and Battery Systems for Enhanced Stability and Power Quality in AC-DC Loads and EV Charging Applications
This paper presents an advanced control strategy for a grid-connected DC/AC microgrid system integrating solar, wind, and battery storage to support AC/DC loads and electric vehicle (EV) charging stations. A major focus is on maintaining DC bus voltage stability and efficient power sharing among distributed energy resources (DERs), especially under transient disturbances. The proposed system features a layered control strategy: the primary control regulates DC bus voltage via the grid-connected converter (GCC), while the secondary control leverages an energy storage system to maintain voltage stability during grid disturbances. A Maximum Power Point Tracking (MPPT) algorithm optimizes energy extraction from solar photovoltaic (PV) and wind sources. Additionally, an energy management algorithm governs power injection to the grid, generating dynamic current references for the GCC. Adaptive control techniques are employed to manage real-time power flow between the grid, renewables, storage, and hybrid AC/DC loads, significantly enhancing power quality by reducing Total Harmonic Distortion (THD) and improving power factor. MATLAB/Simulink-based simulations of a 15.8 kW microgrid validate the proposed approach, revealing faster transient response, reduced oscillations, and robust performance under varying environmental and load conditions. The proposed strategy enables scalable and flexible microgrid operation, ensuring reliable energy delivery and supporting modern smart grid applications with integrated EV charging.
Institutions
- Institute of Technology Management (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-04-14
- DOI
- https://doi.org/10.5281/zenodo.15212331
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00