Title: Forecasting future demand for coal, oil and gas: application with related to smart cities

Authors: Ravi Kumar

Addresses: Department of ECE, Jaypee University of Engineering and Technology, Guna, 473226, Madhya Pradesh, India

Abstract: Forecasting future demand for coal, oil, and gas is essential for ensuring energy security, optimising resource allocation, and supporting strategic planning - particularly in the context of developing smart cities. This study explores advanced forecasting techniques to predict the consumption patterns of fossil fuels, using a data-driven framework that integrates historical consumption trends, economic indicators, and environmental policies. The objective is to enable policymakers and urban planners to make informed decisions that balance energy needs with sustainability goals. By applying machine learning algorithms and time-series models, the analysis offers insights into future energy demand under different scenarios. The results highlight the ongoing importance of coal, oil, and gas in urban infrastructures, while also emphasising the need for a gradual transition to renewable sources. This research provides a valuable tool for smart cities to plan their energy mix, reduce emissions, and align with global climate objectives through proactive energy demand forecasting. [Received: January 20, 2025; Accepted: July 23, 2025]

Keywords: smart meter data: communication: data pre-processing: benchmark models: natural gas: smart meter dataset.

DOI: 10.1504/IJOGCT.2026.153881

International Journal of Oil, Gas and Coal Technology, 2026 Vol.40 No.1, pp.86 - 109

Received: 14 Jan 2025
Accepted: 23 Jul 2025
Published online: 29 May 2026 *

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