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AI-Enhanced Battery Monitoring and Control in Standalone Solar Power Systems
Authors
1 2 3 4 UG Scholar, Department of Electrical and Electronics Engineering, Holy Mary Institute of Technology and Science, Hyderabad, Telangana, India. 5 Assistant Professor, Department of Electrical and Electronics Engineering, Holy Mary Institute of Technology and Science, Hyderabad, Telangana, India.
Article Information
- DOI
- No Doi
- Published In
- Year 2026 · Volume 3 · Issue 1
- Published Online
- January-April 2026
- Pages
- 18-20
- Article Type
- Review Article
- Check for updates
-
References
1. Zhang, Y., Lin, X., & Wang, J. (2023). Machine learning for Battery State of Charge estimation: A review. Renewable Energy Journal,
15(2), 101–119.
2. Kumar, A., & Singh, P. (2022). Predictive maintenance of solar battery systems using AI algorithms. International Journal on Energy
Systems, 27(4), 385–402.
3. Li, D., & Chen, H. (2021). Reinforcement learning in energy storage control for standalone photovoltaic systems. IEEE Transactions on
Sustainable Energy, 12(1), 25–34.
4. Mahmood, F., & Malik, K. (2020). Hybrid fuzzy-AI based controllers for battery management. Journal of Intelligent Systems, 34(9), 1137–
1155.
5. Patel, R., & Sharma, V. (2023). Digital twin applications in renewable energy storage systems. Energy Informatics Review, 8(1), 45–63.
6. Santos, J., & Pereira, L. (2021). IoT enabled battery monitoring for decentralized solar installations. Sensors and Systems Journal, 19(3),
248–267.
7. Lee, S., & Kim, J. (2022). AI-based thermal management in lithium-ion batteries for solar applications. Journal of Thermal Engineering,
16(7), 890–906.
8. Cheng, Z., & Wu, Q. (2020). Solar irradiance forecasting using deep learning for energy storage optimization. Renewable Forecasting Letters,
11(5), 76–92.
9. Roy, M., & Das, R. (2023). Fault diagnosis in solar battery systems using classification algorithms. Journal of Power and Energy
Engineering, 10(2), 55–69.
10. Oliveira, T., & Silva, M. (2021). Adaptive load management for enhanced battery life in off-grid systems. Energy and Buildings, 224, 110–
124.
11. Nguyen, H., & Tran, T. (2022). Neural network approaches for state of health monitoring in photovoltaic battery systems. Energy Reports,
8, 1450–1462.
12. Gupta, S., & Shah, R. (2020). A comparison of AI models for standalone solar energy optimization. International Journal of Renewable
Energy Research, 10(1), 54–63.
13. Fernández, P., & García, L. (2023). Data-driven analytics for battery health prediction. Sustainable Energy Analytics, 5(1), 23–47.
14. Hussein, A., & Youssef, M. (2021). IoT and AI integration for decentralized energy storage systems. Journal of Distributed Energy Systems,
7(4), 97–115.
15. Dutta, K., & Pal, S. (2022). Intelligent control strategies for off-grid solar storage: A review. Journal of Clean Energy Technologies, 10(3),
232–249.
15(2), 101–119.
2. Kumar, A., & Singh, P. (2022). Predictive maintenance of solar battery systems using AI algorithms. International Journal on Energy
Systems, 27(4), 385–402.
3. Li, D., & Chen, H. (2021). Reinforcement learning in energy storage control for standalone photovoltaic systems. IEEE Transactions on
Sustainable Energy, 12(1), 25–34.
4. Mahmood, F., & Malik, K. (2020). Hybrid fuzzy-AI based controllers for battery management. Journal of Intelligent Systems, 34(9), 1137–
1155.
5. Patel, R., & Sharma, V. (2023). Digital twin applications in renewable energy storage systems. Energy Informatics Review, 8(1), 45–63.
6. Santos, J., & Pereira, L. (2021). IoT enabled battery monitoring for decentralized solar installations. Sensors and Systems Journal, 19(3),
248–267.
7. Lee, S., & Kim, J. (2022). AI-based thermal management in lithium-ion batteries for solar applications. Journal of Thermal Engineering,
16(7), 890–906.
8. Cheng, Z., & Wu, Q. (2020). Solar irradiance forecasting using deep learning for energy storage optimization. Renewable Forecasting Letters,
11(5), 76–92.
9. Roy, M., & Das, R. (2023). Fault diagnosis in solar battery systems using classification algorithms. Journal of Power and Energy
Engineering, 10(2), 55–69.
10. Oliveira, T., & Silva, M. (2021). Adaptive load management for enhanced battery life in off-grid systems. Energy and Buildings, 224, 110–
124.
11. Nguyen, H., & Tran, T. (2022). Neural network approaches for state of health monitoring in photovoltaic battery systems. Energy Reports,
8, 1450–1462.
12. Gupta, S., & Shah, R. (2020). A comparison of AI models for standalone solar energy optimization. International Journal of Renewable
Energy Research, 10(1), 54–63.
13. Fernández, P., & García, L. (2023). Data-driven analytics for battery health prediction. Sustainable Energy Analytics, 5(1), 23–47.
14. Hussein, A., & Youssef, M. (2021). IoT and AI integration for decentralized energy storage systems. Journal of Distributed Energy Systems,
7(4), 97–115.
15. Dutta, K., & Pal, S. (2022). Intelligent control strategies for off-grid solar storage: A review. Journal of Clean Energy Technologies, 10(3),
232–249.
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