Biradar, Siddalingappagouda
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Fuzzy logic-based energy management system for a microgrid with hybrid energy storage: design, control, and comparative analysis Neelagiri, Suganthi; Usha, Pasumarthi; Biradar, Siddalingappagouda
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i3.pp1991-2004

Abstract

This paper presents a fuzzy logic-based energy management controller for a microgrid with a hybrid energy storage system. The microgrid integrates intermittent renewable energy sources. To provide high quality, reliable and sustainable power, the microgrid depends on energy storage devices. The proposed fuzzy logic-based energy management controller controls the energy storage system’s power electronic converters by generating switching pulses based on the generation availability, load requirement, SOCs of battery, and supercapacitor. Additionally, a fuzzy logic-based energy management system is planned in such a way that high power needs are satisfied by supercapacitors and high energy needs are satisfied by batteries. To highlight the key benefits of utilizing a fuzzy logic-controlled hybrid energy storage system over PI -a controller-based cascaded dual loop energy management system, a comparative study is carried out. The results of the same is discussed elaborately in this paper. These studies were simulated using the MATLAB/Simulink software package.
A fuzzy logic approach to sustainable energy management in standalone microgrids Neelagiri, Suganthi; Babu, Srinivas; Biradar, Siddalingappagouda
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i4.pp999-1010

Abstract

The fast development of worldwide energy consumption, driven by industrial growth and increasing dependence on fossil fuels, has led to higher carbon emissions and degradation of the environment. In response, renewable energy sources, such as solar, wind, and hydroelectric power, offer cleaner and sustainable replacements with insignificant carbon emissions. This paper examines the role of artificial intelligence (AI)-based techniques, particularly fuzzy logic, in developing energy management system. A fuzzy logic-based energy management system is proposed for a renewable-powered microgrid that incorporates a hybrid energy storage system. Fuzzy logic-based energy management, due to its capability to manage uncertainty and complexity, offers viable solutions for improving the generation and distribution of energy within microgrid systems. This system is compared to a dynamic cascaded dual-loop proportional-integral (PI) controller-based energy management system in standalone mode. The comparative analysis emphasizes the ability of fuzzy logic-based energy management to improve the efficiency and sustainability of microgrids. The research aims to advance the creation of more intelligent and dependable energy solutions that integrate renewable resources and enhance energy management practices.