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Microgrid confrontations and smart resolution Modi, Sangeeta; Usha, Pasumarthi
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i3.pp1446-1455

Abstract

Hybrid microgrids are emerging as an alternate solution for connecting distributed AC/DC energy resources. Effective fault detection and response are highly essential for the microgrid controller (MGC) for protection of the microgrid. The conventional schemes of protection cannot be applied in microgrid because of dynamic conduct and unconventional topology of the microgrids. It is highly essential to develop an appropriate scheme for detection and classification of faults for the effective protection of microgrids. In this paper, a novel and smart solution based on the application of an intelligent machine learning (ML) fine tree algorithm is applied to the hybrid microgrid controller. This algorithm resulted in effective detection & classification of faults which in turn was used for separation of faulty segment. The intelligent model obtained with the proposed algorithm performed well and fault detection accuracy has been showcased for various fault scenarios. The overall fault detection accuracy obtained is 98%. Severity of faults and associated confrontations are also discussed in this work. Performance efficacy of the proposed ML based protection algorithm for MGC is substantiated in MATLAB environment.
Advanced multi-source converters for DC microgrids: integrating photovoltaic, wind, and hybrid storage systems Neelagiri, Suganthi; Usha, Pasumarthi
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i2.pp1261-1273

Abstract

This paper presents a new configuration for integrating multi-source and hybrid energy storage (HES) systems tailored for a direct current (DC) microgrid. Unlike conventional multi-input converters, the proposed design features a hybrid energy storage system combining ultracapacitors and batteries. The proposed system is intended to effectively manage power variations from wind, photovoltaic (PV) sources, and abrupt load changes. The inclusion of ultracapacitors addresses high-frequency fluctuations, thereby extending battery life and reducing the overall size of the storage unit. The control framework is designed to maintain power balance within the system, ensuring that renewable energy sources operate at their maximum power points and that energy storage is efficiently charged and discharged based on power availability. The main advantages of this configuration include: i) a reduced number of switches, ii) built-in voltage boosting and regulation for the ultracapacitor, and power-sharing between the battery and ultracapacitor, and iii) a streamlined control system with fewer components. The paper details the investigation, modeling, and design of the planned system, supported by MATLAB simulation results.
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.