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Abstract

So far there is still no complete solution where a controlled environment-plant production system is integrated to a photovoltaic system with battery energy storage for the implementation of more renewable energy alternatives. Consequently, it is rather difficult to address the optimization of the plant production and to minimize the energy consumption. In a previous work, the authors integrated a climate-controlled greenhouse with a photovoltaic system with battery energy storage to develop an intelligent control system for optimizing the operation of the lighting systems. In addition, the authors implemented a deep-learning algorithm for forecasting solar power production for the battery control purpose. A cost-benefit analysis was carried and it was found an approximate total reduction of electricity cost of about 15.3% during the experiment period. In this work, we proposed to carry out a pilot study, during the period of December 22, 2022 to June 5, 2023, by setting two different light treatments of blue light proportion (2 and 14%, respectively). The cherry tomato cultivar ‘Caprese F1’ was used for this pilot study. Based on the collected data, the ‘Caprese F1’ was not affected by the level of blue light proportion, as the plant height, the plant dry mass, and the total fruit yield did not show a significant difference (p>0.05) between the two light treatments.

Keywords

artificial lighting control; photovoltaic system; battery energy storage; energy consumption; Solanum lycopersicum

Published in

Acta Horticulturae
2025, number: 1433, pages: 19-30
Title: Proceedings of the International Symposium on Robotics, Mechanization and Smart Horticulture
Publisher: ISHS

Conference

EHC2024: International Symposium on Robotics, Mechanization and Smart Horticulture, 2024, 12-16 May, Bucharest, Romania

SLU Authors

UKÄ Subject classification

Control Engineering
Horticulture

Publication identifier

  • DOI: https://doi.org/10.17660/ActaHortic.2025.1433.3
  • ISBN: 978-94-62614-32-1

Permanent link to this page (URI)

https://res.slu.se/id/publ/142671