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Volume 2 Number 1 2024

Article Contents

REVIEWS   (Open Access)
Contents Vol 3 (1)

Economic Feasibility of AI-Based Distributed Energy Systems in Agricultural Enterprises

Ashok Kumar Chowdhury1*, Md Rahedul Islam2

+ Author Affiliations

Business & Social Sciences 3 (1) 1-6 https://doi.org/10.25163/business.3110300

Submitted: 08 May 2025 Revised: 16 July 2025  Published: 17 July 2025 

Abstract

The demand for sustainable and decentralized energy solutions is a growing area of interest in agriculture as it relates to Distributed Energy Systems (DES) particularly when combined with Artificial Intelligence (AI). There are many energy-intensive activities in agriculture. For example, if we consider just irrigation and greenhouse climate control systems, along with post-harvest processing, the energy demand for agricultural operations may be impacted by unreliable grid conditions and increased fuel costs.AI, predictive maintenance of DES can be performed, load can be intelligently forecasted, energy resource dispatch can be optimized, resulting in operational efficiencies between 15-30%, energy cost savings between 20-40%, and reduction in downtime by approximately 60%. The review evaluates economic performance indicators, specifically cost variables such as initial capital investment, payback periods years, and Net Present Value (NPV). The results suggest that while AI-based systems are 20-30% costlier as compared to traditional based systems, the payback periods 4-7 years and returns on investment 15-25% are shorter over a 20-year life period. Descriptions of case studies in developing countries, like India, the Netherlands, and Kenya, show an overall cost savings through reduced costs in fuel, water, and labor, while increasing productivity by 10-30%. The review suggests that AI-integrated DES ultimately not only aligned with sustainability goals, but demonstrated real economic value for farmers, especially with strategic policy and investment plans. Future research should be focused on scale-up, low-cost AI and localized implementation plans.

Keywords: Artificial Intelligence, Distributed Energy Systems, Agriculture, Economic Feasibility, Renewable Energy

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