Enhanced load frequency regulation in microgrids with renewable energy sources and electric vehicles

Khan, Imran; Malik, Suheel Abdullah; Daraz, Amil; Bareer, Baitullah · 2025 · Crossref

DOI: 10.1038/s41598-025-10835-z

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study addresses the critical challenge of maintaining frequency stability in microgrids characterized by the intermittent nature of Renewable Energy Sources (RESs) and the stochastic behavior of loads. As global energy systems transition toward RESs like photovoltaics and wind turbines, the reduction in grid inertia leads to significant frequency excursions. The authors propose a novel secondary-level Load Frequency Control (LFC) strategy to mitigate these deviations in both islanded and interconnected microgrids. The system model integrates diverse distributed generation sources, including fuel cells, diesel engine generators, battery energy storage systems, and electric vehicles (EVs), which are utilized as flexible energy storage to enhance system resilience. The core contribution is the design of a cascaded Integral-Proportional-Proportional Derivative with Filter ((I-P)-PDN) controller. To optimize the controller’s parameters, the study employs the Black-winged Kite Algorithm (BKA), a nature-inspired metaheuristic technique modeled after the hunting and hovering behaviors of the black-winged kite bird. The BKA is selected for its superior search efficiency, quick convergence, and ability to balance global exploration with local exploitation. The optimization process aims to minimize frequency deviations and tie-line power fluctuations under dynamic conditions, including worst-case scenarios and communication delays. The proposed approach is benchmarked against existing controllers, such as PID, PI-based models, and fractional-order variants, using standard performance indices. Simulation results demonstrate that the (I-P)-PDN controller significantly outperforms conventional and advanced existing controllers. Specifically, the proposed method achieved a 77% reduction in overshoot and a 52% decrease in undershoot in tie-line power variations. Error indices were substantially minimized, with the Integral Absolute Error (IAE) reduced by 42.3%, the Integral Time weighted Absolute Error (ITAE) by 85%, and the Integral Squared Error (ISE) by 98%. Additionally, the settling time for frequency deviations was markedly improved compared to baseline methods. The study also highlights the effectiveness of EVs in providing virtual inertia and stabilizing the grid during peak loads or renewable intermittency. The significance of this work lies in providing a robust, high-performance control solution for modern microgrids integrating high penetrations of renewables and EVs. By combining a novel cascaded controller structure with an efficient optimization algorithm, the study offers a reliable method for ensuring frequency regulation and power system stability. The findings suggest that this approach enhances the resilience of microgrids against disturbances, supporting the sustainable integration of renewable energy and electric mobility into future power systems.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• steering pattern