Evolution of the Agricultural Energy Internet

In smart agriculture, core functions such as agricultural machinery automation, intelligent environmental sensing, and precision crop management rely heavily on continuous, high-quality energy supply. Intelligent power systems tailored to agricultural scenarios are essential to realizing unmanned farms. Moreover, as a result of rural revitalization strategies and national programmes such as China's dual carbon goals, rural areas and agriculture are no longer merely energy consumers. Agricultural and rural zones are increasingly becoming important providers of distributed renewable energy and suitable deployment sites for energy infrastructure. As such, the agricultural energy internet is now entering a critical stage of rapid development and engineering transformation.

Evolution of the Agricultural Energy Internet: Modeling, simulation and engineering practice focuses on the field of agricultural energy and falls under the discipline of agricultural electrification and automation. The book systematically elaborates on the principles and applications of the agricultural energy internet through theoretical modelling, simulation techniques and engineering case studies - especially in response to the growing demand for clean, reliable, and intelligent power supply systems that enable the future development of unmanned and smart agriculture.

A key feature of this book lies in its integrated structure combining theoretical analysis, code implementation, and real-world engineering cases. Chapters offer a systematic overview of modelling and simulation, methods for agricultural energy internet systems, provide reproducible code implementations, and present in-depth case studies based on projects including the aqua photonics-based agricultural energy internet at the Smart Farm in Zhuoxhou, Hebei Province, China, and the agricultural park in Langyatai, Qingdao, China.

The closed-loop content design - from theory to simulation to engineering validation - makes the book suitable both for researchers developing algorithms and models, and for engineers seeking practical guidance in system deployment.