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Volume 2 Number 1 2024

Article Contents

RESEARCH ARTICLE   (Open Access)
Contents Vol 3 (1)

AI-Powered Energy Forecasting and Control for Smart Rural Energy Infrastructure

Md. Jobayer Ahmed1*, Ashok Kumar Chowdhury2

+ Author Affiliations

Applied IT & Engineering 3 (1) 1-6 https://doi.org/10.25163/engineering.3110315

Submitted: 06 May 2025 Revised: 11 July 2025  Published: 12 July 2025 

Abstract

It is at the center of such a critical transition that Bangladesh is currently involved in through a rural electrification-led transition to power agriculture, health, education and livelihoods. Despite over 95% grid penetration in rural areas, the energy availability is only between 18-22% owing largely to intermittent n renewable sources, inadequate infrastructure and seasonal demand. Artificial Intelligence (AI), specifically under the disciplines of machine learning (ML) and deep learning (DL) are transforming rural energy systems by providing more accurate forecasts, enabling intelligent control and improving energy efficiency. In this cross-cutting review, we consider how AI is being integrated into rural energy systems in Bangladesh, with a specific focus on energy forecasting, smart microgrids, and adaptive load management. Artifact observations in districts such as Gaibandha, Patuakhali and Kumigram demonstrated how AI-based systems can improve forecasting accuracy to over 92% reduce system down-time to 80%, and improve battery storage by 30-35%. The paper discussed additionally, coupling AI with IoT for real-time controls, GIS with 47% more efficient renewable site optimization for solar siting, and block chain with decentralized energy transactions that reduced the average household cost of energy by 11%. The study ended with some important recommendations that detailed how AI can be an enabler for sustainable and equitable rural energy development in Bangladesh, assuming it is deployed on an inclusive and context specific platform.

Keywords: Artificial Intelligence, Smart Microgrids, Renewable Energy, Rural Electrification, Bangladesh

References

Abdullah, M. S., Tasnim, K., Karim, M. Z., & Hasan, R. (2025). Improving Market Competitiveness using the Use of Artificial Intelligence in Strategic Business Decisions. Business & Social Sciences, 3(1), 1-9.

Ali, S. S., & Choi, B. J. (2020). State-of-the-Art Artificial Intelligence Techniques for Distributed smart grids: A review. Electronics, 9(6), 1030. https://doi.org/10.3390/electronics9061030

Arévalo, P., & Jurado, F. (2024). Impact of artificial intelligence on the planning and operation of distributed energy systems in smart grids. Energies, 17(17), 4501. https://doi.org/10.3390/en17174501

Arfanuzzaman, M. (2021). Harnessing artificial intelligence and big data for SDGs and prosperous urban future in South Asia. Environmental and Sustainability Indicators, 11, 100127. https://doi.org/10.1016/j.indic.2021.100127

Choksi, K. A., Jain, S., & Pindoriya, N. M. (2020). Feature based clustering technique for investigation of domestic load profiles and probabilistic variation assessment: Smart meter dataset. Sustainable Energy Grids and Networks, 22, 100346. https://doi.org/10.1016/j.segan.2020.100346

Da, L., Chen, T., Li, Z., Bachiraju, S., Yao, H., Li, L., Dong, Y., Hu, X., Tu, Z., Wang, D., Zhao, Y., Zhou, B., Pendyala, R., Stabler, B., Yang, Y., Zhou, X., & Wei, H. (2025, March 10). Generative AI in Transportation Planning: a survey. arXiv.org. https://arxiv.org/abs/2503.07158

Hasan, R., Tasnim, K., Karim, M. Z., & Abdullah, M. S. (2024). Transforming the Digital Landscape: Analyzing the Role of Artificial Intelligence in Contemporary Marketing Strategies. Business & Social Sciences, 2(1), 1-10.

Hossain, A. K., & Badr, O. (2006). Prospects of renewable energy utilisation for electricity generation in Bangladesh. Renewable and Sustainable Energy Reviews, 11(8), 1617–1649. https://doi.org/10.1016/j.rser.2005.12.010

Hossain, M. M., Roy, A., & Nahiduzzaman, M. (2025). Modernizing Textile Industry Operations with Artificial Intelligence. Applied IT & Engineering, 3(1), 1-8.

Hussain, M. N., Zaman, M. R., Halim, M. A., Ali, M. S., & Khan, M. Y. A. (2024c). A Comprehensive Review of Renewable and Sustainable Energy Sources with Solar Photovoltaic Electricity Advancement in Bangladesh. Control Systems and Optimization Letters, 2(1), 1–7. https://doi.org/10.59247/csol.v2i1.59

Jalal, M., Khalil, I. U., & Haq, A. U. (2024). Deep learning approaches for visual faults diagnosis of photovoltaic systems: State-of-the-Art review. Results in Engineering, 23, 102622. https://doi.org/10.1016/j.rineng.2024.102622

Karim, M. Z., Hasan, R., Abdullah, M. S., & Tasnim, K. (2023). AIs Exceptional Potential to Significantly Improve the Profitability of Social Media Influencer Marketing. Business & Social Sciences, 1(1), 1-8.

Kaygusuz, K. (2010). Energy services and energy poverty for sustainable rural development. Renewable and Sustainable Energy Reviews, 15(2), 936–947. https://doi.org/10.1016/j.rser.2010.11.003

Khalid, M. (2024). Energy 4.0: AI-enabled digital transformation for sustainable power networks. Computers & Industrial Engineering, 193, 110253. https://doi.org/10.1016/j.cie.2024.110253

Khan, M. R., Haider, Z. M., Malik, F. H., Almasoudi, F. M., Alatawi, K. S. S., & Bhutta, M. S. (2024). A comprehensive review of microgrid energy management strategies considering electric vehicles, energy storage systems, and AI techniques. Processes, 12(2), 270. https://doi.org/10.3390/pr12020270

Maarif, M. R., Saleh, A. R., Habibi, M., Fitriyani, N. L., & Syafrudin, M. (2023). Energy usage Forecasting model based on Long Short-Term Memory (LSTM) and eXplainable Artificial intelligence (XAI). Information, 14(5), 265. https://doi.org/10.3390/info14050265

Mimmo, S. S., Roy, A., & Billal, S. A. (2025). Integrating Artificial Intelligence Across the Fashion Value AI Transforming Design, Production, and Consumer Experience. Applied IT & Engineering, 3(1), 1-10.

Miskat, M. I., Sarker, P., Chowdhury, H., Chowdhury, T., Rahman, M. S., Hossain, N., Chowdhury, P., & Sait, S. M. (2023). Current scenario of solar energy applications in Bangladesh: Techno-Economic perspective, policy implementation, and possibility of the integration of artificial intelligence. Energies, 16(3), 1494. https://doi.org/10.3390/en16031494

Nicolini, E. (2024). Climate change adaptation and mitigation and historic centers preservation. Underway and repeatable technological design solutions. Cities, 152, 105174. https://doi.org/10.1016/j.cities.2024.105174

Niu, T., Lei, B., Guo, L., Fang, S., Li, Q., Gao, B., Yang, L., & Gao, K. (2023). A review of Optimization Studies for system appointment scheduling. Axioms, 13(1), 16. https://doi.org/10.3390/axioms13010016

Nkandu, G. (2024). A study of the viability of Zambia co-operative federation (ZCF) installed solar milling plants in Zambia (Doctoral dissertation, The University of Zambia).

Paul, J. (2024). AI-powered micro solar power grid systems for isolated communities.

Qudrat-Ullah, H. (2025). A Thematic Review of AI and ML in Sustainable Energy Policies for Developing Nations. Energies, 18(9), 2239. https://doi.org/10.3390/en18092239

Rahman, A., Hossain, M. S., Muhammad, G., Kundu, D., Debnath, T., Rahman, M., Khan, M. S. I., Tiwari, P., & Band, S. S. (2022). Federated learning-based AI approaches in smart healthcare: concepts, taxonomies, challenges and open issues. Cluster Computing, 26(4), 2271–2311. https://doi.org/10.1007/s10586-022-03658-4

Rahman, S., Sharmin, N., Rahat, A., Rahman, M., & Rahman, M. (2024). Tropical cyclone warning and forecasting system in Bangladesh: challenges, prospects, and future direction to adopt artificial intelligence. Computational Urban Science, 4(1). https://doi.org/10.1007/s43762-023-00113-x

Rane, N. L., Choudhary, S. P., & Rane, J. (2024). Artificial intelligence and Machine Learning in Renewable and Sustainable Energy Strategies: A Critical review and Future Perspectives. puiij.com. https://doi.org/10.5281/zenodo.12155847

Roy, A. (2024). Artificial Intelligence in Advanced Manufacturing: Opportunities, Applications, and Challenges in the Context of Bangladesh. Applied IT & Engineering, 2(1), 1-8.

Roy, A. (2024). Fashion Innovation Driven by AI: Transforming Design, Manufacturing, and Customer Experience. Applied IT & Engineering, 2(1), 1-8.

Roy, A., & Ahmed, M. J. (2025). Tech-Driven Fashion Navigating the Opportunities and Challenges of Digitalization. Applied IT & Engineering, 3(1), 1-10.

Shahen, M. A., & Momen, M. N. (2025). Irrigation project and education: A study on Teesta Barrage Irrigation Project area of Nilphamari, Bangladesh. World Water Policy. https://doi.org/10.1002/wwp2.12265

Shoeb, M., & Zillul, M. (2025). Artificial Intelligence in Digital Marketing Enhancing Personalization and Consumer Engagement. Business & Social Sciences, 3(1), 1-9.

Sikder, A. S. (2023). Artificial Intelligence-Enabled Transformation in Bangladesh: Overcoming Challenges for Socio-Economic Empowerment. International Journal of Imminent Science and Technology., 1(1), 77–96. https://doi.org/10.70774/ijist.v1i1.7

Tasnim, K., Abdullah, M. S., Karim, M. Z., & Hasan, R. (2025). AI-Driven Innovation, Privacy Issues, and Gaining Consumer Trust: The Future of Digital Marketing. Business & Social Sciences, 3(1), 1-7.

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