Multi-Renewable Source Integrated Microgrid System with Advanced Power Management Algorithm for Enhanced Power Distribution
Multi-Renewable Source Integrated Microgrid System with Advanced Power Management Algorithm for Enhanced Power Distribution |
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| © 2025 by IJETT Journal | ||
| Volume-73 Issue-3 |
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| Year of Publication : 2025 | ||
| Author : Pradeep Mogilicharla, B. Sirisha, J. Upendar |
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| DOI : 10.14445/22315381/IJETT-V73I3P124 | ||
How to Cite?
Pradeep Mogilicharla, B. Sirisha, J. Upendar, "Multi-Renewable Source Integrated Microgrid System with Advanced Power Management Algorithm for Enhanced Power Distribution," International Journal of Engineering Trends and Technology, vol. 73, no. 3, pp. 324-334, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I3P124
Abstract
Integrating multiple renewable energy sources into a three-phase grid introduces complex power quality challenges that impact the loads connected to the system. The power generated from renewable sources must be optimally utilized to ensure stable voltage levels. Energy storage systems, such as batteries and SCs, are incorporated alongside these renewable sources to stabilize voltage fluctuations. For this analysis, a microgrid system is designed, incorporating a PV source, an FC, a battery pack, and an SC, all connected to the grid. Each energy source is integrated with its power circuit to facilitate power exchange or maximum power extraction at elevated voltage levels. A central intelligent PMA controls the power flow direction of each module, ensuring efficient operation. To maximize power extraction from the PV source at higher voltage levels, a Quadratic Boost Converter is employed. The battery pack and SC utilize traditional bidirectional converters to manage the charging and discharging of the energy storage elements. The FC is connected to a conventional boost converter, enabling power sharing at medium gain voltage levels. The intelligent PMA optimizes the utilization of power from the PV source and FC while managing the charging control of the energy storage systems based on power availability. The performance of the PMA is evaluated under dynamic conditions within the microgrid system. The analysis and testing are conducted using MATLAB Simulink tools, with measured graphs plotted against time as the reference. This approach ensures a comprehensive evaluation of the system's stability and efficiency under varying operational scenarios.
Keywords
Photovoltaic (PV), Fuel Cell (FC), Super Capacitor (SC), Power Management Algorithm (PMA), MATLAB, Simulink.
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