Consumer Perceptions of Artificial Intelligence (AI)-Driven Smart Grids and Energy Efficiency in Northwest Nigeria’s Power Distribution Sector: A Multi-State Case Study of Sokoto, Kebbi, and Zamfara
- Authors
-
-
Victor A. NSABA
Technical Education Department, Federal College of Education, Gidan Madi, Sokoto State, Nigeria; Department of Electrical and Electronic Engineering, University of Jos, Jos, Nigeria
Author
-
Sabiu B. YUSUF
Technical Education Department, Federal College of Education, Gidan Madi, Sokoto State, Nigeria; Department of Mechatronics and Systems Engineering, Abubakar Tafawa Balewa University, Bauchi, Nigeria
Author
-
Kafayat A. IBRAHIM
Technical Education Department, Federal College of Education, Gidan Madi, Sokoto State, Nigeria; Department of Electrical and Electronic Engineering, Abubakar Tafawa Balewa University, Bauchi, Nigeria
Author
-
- Keywords:
- Automated fault detection, Energy efficiency, Renewable energy integration, Smart grids, Smart metering.
- Abstract
-
This study examines consumer perceptions of Artificial Intelligent driven smart grid technologies and their implications for energy efficiency in Northwest Nigeria’s power distribution sector, with specific focus on Sokoto, Kebbi and Zamfara States. The study investigates the impact of smart metering technology, automated fault detection and restoration systems and AI-driven renewable energy integration on perceived energy efficiency. A quantitative survey design was adopted and data were collected from 100 electricity consumers across the three selected states. The data were analyzed using descriptive statistics, Bayesian correlation and multiple regression techniques. The findings reveal that smart metering technology has the strongest positive influence on perceived energy efficiency (β = 0.636, p < .001). Automated fault detection and restoration systems also demonstrate a significant positive effect (β = 0.375, p < .001), while AI-driven renewable energy integration significantly enhances perceptions of grid stability and efficiency (β = 0.414, p < .001). The regression model shows strong explanatory power (R = .865, F (3,97) = 96.086, p < .001). The study concludes that AI-driven technologies play an important role in shaping consumer confidence in electricity distribution within the selected case study states. Strengthening consumer awareness, improving infrastructure, and ensuring effective implementation of smart grid solutions will be essential for achieving sustainable improvements in Nigeria’s power sector.
- References
- Downloads
- Published
- 23-03-2026
- Section
- Articles
- License
-
Copyright (c) 2026 FUDMA Journal of Engineering and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
Similar Articles
- Sirajo ALHASSAN, Abdullahi A. ADAMU, Mohammed T. JIMOH, Experimental Characterization and Seasonal Energy Potential Assessment of Municipal Solid Waste in Kano City, Nigeria , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Olusola K. AKINDE, Abolaji O. ILORI, Habeeb A. ARIKEWUYO, Development of a Wearable Fall Sensing Device for Enhanced Independent Living Among the Elderly , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Muhammad M. HAMIDU, Abubakar M. EL-JUMMAH, Muhammad SHUWA, An Assessment of Power Sources for Improved Energy Supply in University of Maiduguri , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Benjamin T. ABUR, Abubakar A. WARA, David ISAH, Mary D. IGBUR, Catherine N. KWAGHMANDE, Co-Gasification of Sugarcane Bagasse and Coal: A Study on Thermal Characteristics and Efficiency , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Oluyemi S. ONIFADE, Olusegun O. AJIDE, Development and Performance Evaluation of a Semi-Automated Impact Fracture Tester , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Benedict O. EDENSETING, Innocent O. OBOH, Alexander A. JOCK, Effective Food Waste Utilization: A Veritable Source of Biofuel for Nigerian Economic Sustenance and Development - A Review , FUDMA Journal of Engineering and Technology: Vol. 1 No. 1 (2025): July 2025
- Olawale J. OLALUYI, Johnson O. ADEOGO, Adeniyi O. AJIBOYE, Mayowa O. ORESELU, Olarewaju T. OGINNI, Application of Machine Learning for Enhancing Fake Logo Detection , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Gbenga G. OSEKE, Chisom S. AMADI, Abubakar U. RAJI, Hydrogen Production from Flare Gas via Steam Methane Reforming: A Simulation-Based Approach , FUDMA Journal of Engineering and Technology: Vol. 2 No. 2 (2026): December 2026
- Damilare L. ADEKEYE, Uche M. IROKA, A Microcontroller-Based Intelligent Electricity Theft Detection and Prevention System , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Tunji J. ERINLE, Daniel C. UGURU-OKORIE, Abiodun M. ADEBIMPE, Adeolu A. ADEDIRAN, Hilary U. EZEA, A Comprehensive Review of In-Situ Monitoring and Post-Process Defect Detection in Additive Manufacturing , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
You may also start an advanced similarity search for this article.
