Improving Load Frequency Control in Renewable Rich Grid Using ANN Based ULTRACAPACITOR

Authors

Akaninyene M. Joshua

Department Electrical and Electronic Engineering, Enugu State University of Science and Technology (Nigeria)

Chukwuagu M. Ifeanyi

Department of Electrical and Electronic Engineering Caritas University Amorji-Nike, Emene, Enugu State (Nigeria)

Article Information

DOI: 10.47772/IJRISS.2026.100600690

Subject Category: Computer Science

Volume/Issue: 10/6 | Page No: 9832-9841

Publication Timeline

Submitted: 2026-05-20

Accepted: 2026-05-25

Published: 2026-07-02

Abstract

The persistent power failure that had crippled business activities were caused by the following factors that could not attain their respective thresholds. System Frequency Deviation, Rate of Change of Frequency Steady-State Frequency Error, Area Control Error Tie-Line Power Deviation, Frequency Recovery Time, Inertia Constant, Primary Frequency Reserve Margin, Secondary Reserve Availability that did not attain threshold, Renewable Power Forecast Error, Automatic Generation Control Delay, Governor Dead Band and Damping Ratio of Frequency Oscillations. This constant power failure in the country was subdued by introducing improving load frequency control in renewable rich grid using ANN based ULTRACAPACITOR. To perfectly achieve this, it was done in this manner, load frequency control in renewable rich grid was characterized and causes of poor load frequency control in renewable rich grid were established and a conventional SIMULINK model for load frequency control in renewable rich grid was designed. Then, ANN was trained in the causes of poor load frequency control in renewable rich grid for effective reduction of causes of poor load frequency control in renewable rich grid was designed, ANN was trained in the causes of poor load frequency control in renewable rich grid for effective reduction of causes of poor load frequency control in renewable rich grid and a SIMULINK model for ULTRACAPACITOR was designed. Later, algorithm that would implement the process was developed, a SIMULINK model for improving load frequency control in renewable rich grid using ANN based ULTRACAPACITOR was designed and the results were validated and justified. The results obtained were the conventional System Frequency Deviation that caused poor load frequency control in renewable rich grid was0.4 Hz. On the other hand, when an ANN based ULTRACAPACITOR was input into the system, it instantly reduced it to 0.2 Hz and the conventional Renewable Power Forecast Error that that caused poor load frequency control in renewable rich grid was18%. meanwhile, when an ANN based ULTRACAPACITOR was integrated into the system, it instantly reduced to13%. With these results obtained, the percentage improvement in load frequency control in renewable rich grid when an ann based ULTRACAPACITOR was input into the system was 5%.

Keywords

Improving, load, frequency, control, renewable, rich, grid, ANN, based, ULTRACAPACITOR

Downloads

References

1. Bevrani, H. (2014). Robust power system frequency control. Springer. [Google Scholar] [Crossref]

2. Bevrani, H., Ghosh, A., & Ledwich, G. (2019). Renewable energy sources and frequency regulation: Survey and new perspectives. IET Renewable Power Generation, 4(5), 438–457. [Google Scholar] [Crossref]

3. Haykin, S. (2009). Neural networks and learning machines (3rd ed.). Pearson Education. [Google Scholar] [Crossref]

4. Kundur, P., Balu, N. J., & Lauby, M. G. (2004). Power system stability and control. McGraw-Hill Education. [Google Scholar] [Crossref]

5. Milano, F., Dörfler, F., Hug, G., Hill, D. J., & Verbič, G. (2018). Foundations and challenges of low-inertia systems. Proceedings of the IEEE, 106(9), 1634–1653. [Google Scholar] [Crossref]

6. Miller, J. R., & Simon, P. (2008). Electrochemical capacitors for energy management. Science, 321(5889), 651–652. https://doi.org/10.1126/science.1158736 [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles