This bibliometric analysis examines the evolution and structural dynamics of scientific knowledge on the application of digital technologies and digital twins in the energy systems of horticultural greenhouses. Within the global context of digital transformation and the urgent need to optimize energy use in protected agriculture, the development of intelligent, efficient, and sustainable greenhouse systems has become a strategic challenge. Nevertheless, the integration of digital twins into greenhouse energy management remains a fragmented and emerging research area. To characterize this field, a comprehensive search was conducted in Scopus (2016–2025) using the following query: TITLE-ABS-KEY (("digital twin" OR "digital design") AND "greenhouse" AND ("energy system" OR "solar energy")) AND NOT ("greenhouse gas*"). The retrieved records were analyzed using Bibliometrix (R) and VOSviewer, enabling the identification of keyword co-occurrence networks, temporal production trends, and international collaboration patterns. The final dataset comprised 19 documents published in 14 sources, authored by 154 researchers none of whom were single authors with an annual growth rate of 24.1% and an international co-authorship rate of 10.5%. The dominant subject areas were Computer Science (15 documents) and Engineering (9), followed by Mathematics and Agricultural and Biological Sciences. The average number of citations per article was 12.2, and the mean document age was 2.37 years, underscoring the novelty and rapid consolidation of the field. The most frequent keywords were energy management, greenhouses, embedded systems, and artificial intelligence, reflecting the convergence between automation, digital design, and energy efficiency. The results suggest that the use of digital twins and intelligent control in greenhouses is primarily directed toward thermal simulation, energy optimization, and solar system integration. The analysis highlights the leadership of Wageningen University & Research and points to significant opportunities for advancing this research within low-cost and tropical agricultural contexts, where digital energy management could enhance both productivity and sustainability.