Hybrid Systems for Energy Distribution and Telecommunication Reliability in Smart Grids
Abstract
The integration of energy distribution systems and telecommunication networks is crucial for improving the reliability, efficiency, and scalability of smart grids. However, challenges such as electromagnetic interference (EMI), latency, and fault tolerance complicate seamless operation. This study proposes a hybrid framework using MATLAB/Simulink to model and simulate energy distribution, real-time monitoring, and fault detection in high-voltage environments. The simulation framework consists of a high-voltage energy distribution network modeled with multiple buses, transformers, and distributed renewable energy sources. IoT-based sensors are strategically placed at critical nodes to collect real-time voltage and current data, which are transmitted via 5G communication protocols using the MQTT messaging standard. Fault detection is performed using an AI-driven Support Vector Machine (SVM) algorithm, trained with historical fault data to detect anomalies and classify fault types with high accuracy. The simulation environment integrates power flow analysis, real-time fault detection mechanisms, and communication latency assessment to evaluate system performance. Key findings demonstrate up to 92.8% energy efficiency with 60% renewable energy penetration, fault recovery times reduced to 35 ms through AI-based detection, and communication latency maintained below 15 ms for IoT-based monitoring. These results validate the proposed framework’s ability to address critical challenges in smart grids, including EMI mitigation, fault tolerance, and system scalability. This research bridges the gap between energy distribution and telecommunication systems, offering a scalable and sustainable solution for smart grid optimization.
Keywords
Full Text:
PDFReferences
J. R. A. Jambi, W. K. Wong, F. H. Juwono, and F. Motalebi, “Smart Energy Meter Implementation: Security Challenges and Opportunities,” 2023 Int. Conf. Digit. Appl. Transform. Econ. ICDATE 2023, pp. 1–7, 2023, doi: 10.1109/ICDATE58146.2023.10248469.
G. Cao, W. Gu, W. Liu, and P. Li, “DGRSS: A Platform for Real-time Simulation of Active Distribution Networks with High Penetration of Distributed Renewable Energy,” Proc. - 2020 Int. Conf. Electr. Eng. Control Technol. CEECT 2020, pp. 53–57, 2020, doi: 10.1109/CEECT50755.2020.9298678.
R. L. Sturdivant and E. K. P. Chong, “Systems Engineering of a Terabit Elliptic Orbit Satellite and Phased Array Ground Station for IoT Connectivity and Consumer Internet Access,” IEEE Access, vol. 4, pp. 9941–9957, 2016, doi: 10.1109/ACCESS.2016.2608929.
E. Avşar and M. N. Mowla, “Wireless communication protocols in smart agriculture: A review on applications, challenges and future trends,” Ad Hoc Networks, vol. 136, no. August, 2022, doi: 10.1016/j.adhoc.2022.102982.
S. N. Mousavi, M. G. Villarreal-Marroquín, M. Hajiaghaei-Keshteli, and N. R. Smith, “Data-driven prediction and optimization toward net-zero and positive-energy buildings: A systematic review,” Build. Environ., vol. 242, no. June, p. 110578, 2023, doi: 10.1016/j.buildenv.2023.110578.
G. Liu, X. Yue, J. Yang, J. Yuan, B. Wen, and W. Gao, “Electromagnetic Environment under Switching Operation in Different High-Voltage Substation,” 6th Int. Conf. Electr. Eng. Green Energy, CEEGE 2023, pp. 91–94, 2023, doi: 10.1109/CEEGE58447.2023.10246708.
S. Akkara and I. Selvakumar, “Review on optimization techniques used for smart grid,” Meas. Sensors, vol. 30, no. April, p. 100918, 2023, doi: 10.1016/j.measen.2023.100918.
J. P. Astudillo León, C. L. Duenas Santos, A. M. Mezher, J. Cárdenas Barrera, J. Meng, and E. Castillo Guerra, “Exploring the potential, limitations, and future directions of wireless technologies in smart grid networks: A comparative analysis,” Comput. Networks, vol. 235, no. April, p. 109956, 2023, doi: 10.1016/j.comnet.2023.109956.
E. Nueve, S. Shahkarami, S. Park, and N. Ferrier, “Addressing the Constraints of Active Learning on the Edge,” 2021 IEEE Int. Parallel Distrib. Process. Symp. Work. IPDPSW 2021 - conjunction with IEEE IPDPS 2021, pp. 845–849, 2021, doi: 10.1109/IPDPSW52791.2021.00126.
P. Beshley, M. Kaidan, B. Strykhalyuk, O. Kochan, S. Mokhun, and O. Fedchyshyn, “IoT Empowered SmartESS Systems for Real-Time Monitoring and Control in Smart Grid,” 5th IEEE Int. Conf. Adv. Inf. Commun. Technol. AICT 2023 - Proc., pp. 97–101, 2023, doi: 10.1109/AICT61584.2023.10452690.
E. Esenogho, K. Djouani, and A. M. Kurien, “Integrating Artificial Intelligence Internet of Things and 5G for Next-Generation Smartgrid: A Survey of Trends Challenges and Prospect,” IEEE Access, vol. 10, pp. 4794–4831, 2022, doi: 10.1109/ACCESS.2022.3140595.
H. M. A. Ahmed, H. F. Sindi, M. A. Azzouz, and A. S. A. Awad, “An Energy Trading Framework for Interconnected AC-DC Hybrid Smart Microgrids,” IEEE Trans. Smart Grid, vol. 14, no. 2, pp. 853–865, 2023, doi: 10.1109/TSG.2022.3197728.
S. Hongtao, L. Chong, G. Juchuan, and W. Hao, “Improving Reliability and Performance of Smart Energy Meters in Complex Electromagnetic Environment,” 2024 IEEE 4th Int. Conf. Electron. Commun. Internet Things Big Data, ICEIB 2024, pp. 711–714, 2024, doi: 10.1109/ICEIB61477.2024.10602579.
T. Lu, X. Chen, M. B. McElroy, C. P. Nielsen, Q. Wu, and Q. Ai, “A Reinforcement Learning-Based Decision System for Electricity Pricing Plan Selection by Smart Grid End Users,” IEEE Trans. Smart Grid, vol. 12, no. 3, pp. 2176–2187, 2021, doi: 10.1109/TSG.2020.3027728.
A. Aleshinloye, M. A. Manzoor, and A. Bais, “Evaluation of Dimensionality Reduction Techniques for Load Profiling Application in Smart Grid Environment,” IEEE Can. J. Electr. Comput. Eng., vol. 44, no. 1, pp. 41–49, 2021, doi: 10.1109/ICJECE.2020.3018433.
J. Liu, F. Qu, X. Hong, and H. Zhang, “A Small-Sample Wind Turbine Fault Detection Method With Synthetic Fault Data Using Generative Adversarial Nets,” IEEE Trans. Ind. Informatics, vol. 15, no. 7, pp. 3877–3888, 2019, doi: 10.1109/TII.2018.2885365.
P. Rujipraparat and S. Kiattisin, “A Case Study of Implementation of Digitalization into Digital Transformation in Clean Energy Hybrid Power Plant,” 5th Technol. Innov. Manag. Eng. Sci. Int. Conf. TIMES-iCON 2024 - Proc., pp. 1–4, 2024, doi: 10.1109/TIMES-ICON61890.2024.10630745.
DOI: https://doi.org/10.33387/ijeeic.v2i1.9520
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
| Journal Policies | Submissions | People | Â Information |
International Journal Of Electrical Engineering And Intelligent ComputingDepartement of Electrical Engineering, Faculty of Engineering, Universitas Khairun,
Address: Yusuf Abdulrahman No. 53 (Gambesi) Ternate City - Indonesia
Email: ijeeic.unkhair@gmail.com
International Journal of Electrical Engineering and Intelligent Computing (IJEEIC), Universitas Khairun This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.