Comprehensive review clarifies agricultural energy internet systems, highlighting critical enablers for smart agriculture.
The Agricultural Energy Internet (AEI) represents an emerging systemic paradigm driven by the convergence of intelligent agriculture and rural energy transformation. It is not a simple extension of agricultural informatization or rural electrification; rather, it redefines agricultural processes—such as irrigation, greenhouse environmental control, supplementary lighting, cold-chain logistics, and agricultural machinery—as perceptible, computable, and schedulable energy-related processes, thereby enabling the deep integration of agriculture, energy, environmental management, and intelligent decision-making. This review systematically examines the evolutionary trajectory of AEI, from early agricultural digitalization and Internet of Things (IoT)-based monitoring to edge intelligence and digital twin technologies, and ultimately to the coordinated optimization of agriculture–energy–environment systems. A comprehensive technical framework is established, encompassing physical energy coupling, multi-source sensing and actuation, interconnection and interoperability, edge–cloud collaborative control, data governance, digital twin modeling, artificial intelligence-enabled optimization, and application-oriented decision-making. The review further highlights that high-quality data governance, edge–cloud collaboration, and digital twin calibration are critical enablers of the transition from visualization-oriented management to closed-loop intelligent operation. In addition, this study clarifies the complementary relationship between agricultural informatization and electrification: the former provides capabilities for perception, prediction, optimization, and coordination, whereas the latter provides a controllable execution chain. Together, they constitute the foundation of a cyber-physical agricultural energy system. Finally, frontier research directions are identified, including high-temperature solid oxide electrolysis for hydrogen production, edge AI–IoT-enabled closed-loop agricultural operation, and privacy, security, and trust mechanisms in federated edge intelligence. The findings suggest that AEI can serve as a strategic technological framework for supporting the next generation of smart agriculture toward low-carbon, resilient, and collaborative operation.
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Wu et al. (2026) studied this question.
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