Design, Assessment and Implementation of Fuzzy Logic for DC Voltage in Microgrid
This research examines the optimisation of hybrid energy storage systems (HESS) to improve energy management in microgrids. Integrating batteries with supercapacitor (SC), HESS provides an efficient solution to several difficulties, including enhancing power quality and stabilizing voltage levels. Nonetheless, attaining effective control continues to be a considerable issue. The study examines traditional control techniques and highlights their shortcomings. A novel control technique that combines fuzzy logic with rule-based structures is suggested to address these challenges. This hybrid approach allows for flexible operation in both grid-connected and isolated conditions, addressing diverse network scenarios and operational requirements. The suggested control method seeks to keep DC bus voltage within reference value 100 v, manage the charge states of batteries and SC, and enhance SC utilization to extend battery lifespan. The simulations used Matlab/Simulink demonstrate the effectiveness of the suggested technique. The results show swift voltage recovery with small overshoot and undershoot, thereby ensuring consistent network performance. Furthermore, the technology greatly enhances the utilization of SC compared to conventional methods, indicating improved system efficiency and increased energy capacity.
Authors
- Mohamed Hasan (ORCID: https://orcid.org/0000-0002-7477-7133)
- Mohammed Abdulelah Albasheri (ORCID: https://orcid.org/0000-0002-1964-3183)
- Sofiane Khechafi
- Ouahid Bouchhida
- Youcef Soufı (ORCID: https://orcid.org/0000-0002-0251-6567)
- Abderrezzak Cherifi (ORCID: https://orcid.org/0000-0003-4740-5219)
Institutions
- Université de Versailles Saint-Quentin-en-Yvelines (FR)
- Polytechnic School of Algiers (DZ)
- Handicap neuromusculaire : Physiopathologie, Biothérapie et Pharmacologie appliquées (FR)
Publication Details
- Published
- 2025-02-17
- DOI
- https://doi.org/10.1109/ssd64182.2025.10989848
- Citations
- 1
- Primary Topic
- Smart Grid Energy Management
- Type
- article
- Field-Weighted Citation Impact
- 0.73