Design and Planning of a Smart Distribution Network for Power System Reliability: Case Study of Nigerian University Campuses
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Power system reliability is essential for ensuring consistent and efficient energy delivery in modern distribution networks of Nigerian Universities. This study focuses on designing and planning a smart distribution network to improve the reliability and sustainability of the power system in Nigerian Universities taking Ajayi Crowther University as a case study. The paper addresses existing challenges such as frequent outages, load imbalances, and inefficiencies by integrating renewable energy sources such as solar photovoltaic systems and wind turbines, along with automated fault detection and load management technologies. Intelligent algorithms and real-time energy monitoring enable predictive maintenance, dynamic load optimization, and targeted conservation strategies, such as automated lighting and temperature adjustments. A comprehensive assessment of the University's current energy infrastructure guides the optimization of load distribution, fault tolerance, and energy flow within the network. The design reduces dependence on external grid supply and diesel generators, lowering environmental impact while ensuring seamless power supply for students, staff, and faculty. Reliability measurements, such as the System Average Interruption Duration Index (SAIDI) and the System Average Interruption Frequency Index (SAIFI), evaluate the system’s performance, demonstrating significant improvements in reliability, cost savings, and energy efficiency. This paper provides a roadmap for sustainable energy management and connectivity, establishing a model for similar institutions to address energy challenges and promote sustainable development goals.
Alrasheedi, A., & Almalaq, A. (2022). Hybrid deep learning applied on Saudi smart grids for short-term load forecasting. Mathematics, 10(15), 2666.
Sami Abdou ATTA, Ahmed Sami Abdou ATTA, and Amer Nasr A. ELGHAFFAR. Integration of Smart Grid with the Distribution Network and Renewable Energy Sources, International Conference on Global Practice of Multidisciplinary Scientific Studies-Vii July 04-06, 2024 / Kyrenia, Cyprus.
Kneiske, T. M. (2024). Impact of Multi-Energy System and Different Control Strategies on a Generic Low-Voltage Distribution Grid. Electronics, 13(13), 2545 https://www.mdpi.com/journal/electronic
A li M. Eltamaly, and Amer Nasr A Elghaffar. (2021). Basic Definitions of Smart Grid Technologies and Applications. 2nd INTERNATIONAL BAKU CONFERENCE ON SCIENTIFIC RESEARCH, Baku, AZERBAIJAN. April 2021.
Nureddin, A. A. M., Rahebi, J., & Ab-BelKhair, A. (2020). Power management controller for microgrid integration of hybrid PV/fuel cell system based on artificial deep neural network. International Journal of Photoenergy, 2020(1), 8896412. https://doi.org/10.1155/2020/8896412
Wang, Q., Zhu, X., & Zhou, X. (2024). Two-Layer Optimal Dispatching Strategy of Distribution Network Considering Demand Side Load. In Electronics, Communications and Networks (pp. 318-326). IOS Press.
Yu, C., Ye, B., Wang, X., & Zhao, F. (2019, December). Method for electricity distribution network expansion planning considering opening incremental distribution network. In IOP Conference Series: Materials Science and Engineering (Vol. 677, No. 4, p. 042081). IOP Publishing.
Liming, H., Su, Y., Junming, T., & Haoyuan, Q. (2017). Key Issues for Pilot Reform of Incremental Distribution Network Business. Electric Power, 50(7), 1-4.
Feng, K., Sun, W., Huang, B., Hu, J., Du, D., & Wang, D. (2019, June). Study on the optimal planning of distributed renewable power generation based on long-term sequence simulation in regional distribution network. In IOP Conference Series: Materials Science and Engineering (Vol. 486, No. 1, p. 012061). IOP Publishing.
Alajmi, B. N., AlHajri, M. F., Ahmed, N. A., Abdelsalam, I., & Marei, M. I. (2023). Multi‐objective optimization of optimal placement and sizing of distributed generators in distribution networks. IEEJ Transactions on Electrical and Electronic Engineering, 18(6), 817-833.
Zhang, L., Tang, W., Wang, S., & Zhao, Y. (2011). Distributed generators planning considering benefits for distribution power company and independent power suppliers. Dianli Xitong Zidonghua(Automation of Electric Power Systems), 35(4), 23-28.
