Dynamic Resource Management in Microgrids: Optimizing Efficiency Through Renewable Penetration and Resource Allocation With C-CMRFO

Abstract

Sustainable microgrids (MGs) provide a decentralized and environmentally sustainable solution to contemporary energy challenges, offering improved resilience and reduced carbon emissions. The effective optimization of renewable energy-based MGs requires the precise calibration of energy generation, storage, and distribution systems to maximize efficiency, reliability, and sustainability. This research presents a priority-based renewable energy system with a backup supply designed for grid-tied operation, aiming to optimize renewable resource utilization while ensuring system reliability and contributing to grid stability. The primary objective of this study is to develop an advanced optimization algorithm tailored to renewable energy-based MGs, with the goals of enhancing energy efficiency, maintaining grid stability, and minimizing operational costs. We introduce the Compact Cyclone-Based Manta Ray Foraging Optimization (C-CMRFO) algorithm, specifically designed for application in sustainable MGs to improve energy distribution efficiency, optimize resource allocation, and facilitate the integration of renewable energy sources. The proposed algorithm ensures precise voltage and frequency regulation, thereby supporting grid stability, and is characterized by rapid convergence, allowing for quick adaptation to dynamic grid conditions and efficient real-time operations. The effectiveness of the C-CMRFO algorithm is validated through extensive MATLAB/Simulink simulations, which demonstrate significant improvements in energy distribution efficiency, optimized resource utilization, and accurate voltage and frequency tracking. Additionally, the algorithm’s fast convergence rate is confirmed, enabling swift response to fluctuating grid conditions. Practical validation on a test bed further corroborates the consistency and reliability of the proposed control strategy in optimizing energy management and enhancing power distribution system performance. The close alignment between experimental results and simulation outcomes underscores the robustness and dependability of the proposed approach.

Keywords

• Manta ray foraging optimization
• cyclone foraging
• chain foraging
• somersault foraging
• iterative trajectory
• sustainable microgrid