AI-Enhanced Load Frequency Control in Multi-Area Power Systems via a Self-Tuning PIDF with ANN-Based NMPC and Hybrid Cat-Pikas Optimization

Dataset Description: Table 1. ANN and training hyperparameters Table 2. System information under study Table 3. Optimized controller coefficients in Strategy 1 Table 4. Optimized controller coefficients for four other strategies Table 5. Quantitative results obtained from comparing the performance of control strategies for a 1% load disturbance in area 1 Table 6. Quantitative performance metrics for Scenario 2 Table 7. Quantitative performance metrics for Scenario 3 Table 8. Quantitative performance metrics for Scenario 4 Table 9. Sensitivity Analysis of the Proposed Controller Strategy Table 10. Quantitative results obtained from comparing the performance of various algorithms Acknowledgement: This article is supported with Ongoing Research Funding program, (ORF-2025-258), King Saud University, Riyadh, Saudi Arab; also, the authors declare that This article has been produced with This article has been supported by EU funds under the project "Increasing the resilience of power grids in the context of decarbonisation, decentralisation and sustainable socioeconomic development", CZ.02.01.01/00/23_021/0008759, through the Operational Programme Johannes Amos Comenius.