Assessment of energy storage and renewable energy sources-based two-area microgrid system using optimized fractional order controllers

• Main Authors: Peddakapu, K., Mohd Rusllim, Mohamed, Srinivasarao, P., Arya, Yogendra
• Format: Article
• Language: English; English
• Published: Elsevier Ltd 2024
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/41074/1/Assessment%20of%20energy%20storage%20and%20renewable%20energy%20sources.pdf; http://umpir.ump.edu.my/id/eprint/41074/2/Assessment%20of%20energy%20storage.pdf; http://umpir.ump.edu.my/id/eprint/41074/; https://doi.org/10.1016/j.est.2024.111191; https://doi.org/10.1016/j.est.2024.111191

The stability of modern power systems faces significant challenges due to intermittent renewable generation and fluctuating load demands, resulting in excessive frequency variations. To address this issue and prevent potential blackouts, implementing a robust control strategy is crucial. This study introduces a cascaded control system, combining a novel fractional order integral derivative (FOID) with a fractional order proportional integral derivative with filter (FOPIDN) controllers, denoted as CFOID-FOPIDN. The gain parameters for CFOID-FOPIDN are determined using the Archimedes optimization algorithm (AOA). The proposed two-area microgrid system incorporates various power-generating sources, including solar, wind turbine generators, fuel cells, micro-turbines, and battery energy storage technologies. To assess the AOA-tuned CFOID-FOPIDN controller's effectiveness, the system is tested under five different conditions: load fluctuations, changes in wind speed, variations in irradiance, combined wind and irradiance variations, and comprehensive changes across all conditions. Simulation results reveal that the AOA-based CFOID-FOPIDN outperforms other existing algorithms, such as particle swarm optimization (PSO), bat algorithm (BAT), moth flame optimization (MFO), and whale optimization algorithm (WOA). In dynamic variations across all sources, the AOA-tuned strategy demonstrates shorter settling times in area-1 (2.5 s), area-2 (2.2 s), and tie-line power (2.1 s) compared to PSO (3.5 s, 3.8 s, 3.4 s), WOA (3.2 s, 3.4 s, 3.1 s), BA (3.0 s, 3.1 s, 3.0 s), and MFO (2.9 s, 2.8 s, 2.9 s). Across all five scenarios, the AOA-tuned CFOID-FOPIDN strategy consistently demonstrates superior performance compared to the other strategies under consideration.