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.

Light-emitting diode (LED) based greenhouse lighting systems are energetically more efficient than high intensity discharge lamp systems and are therefore currently replacing those in greenhouses all over the world. However, another interesting feature of LED based systems is the possibility to modify the spectral composition of the light and, thus affect light-dependent physiological reactions in the plants such as photosynthetic activity, floral initiation, and stem elongation. In the present study, the impact on the red/blue balance on growth and development of the horticultural crop Pak Choi was evaluated under greenhouse conditions. The red/blue balance was either R:B 86:14 or 98:2. The fresh- and dry weight was the highest for the treatment with the lower proportion of blue light. Chlorophyll Content Index was higher for the treatment with high proportion of blue light. For the photosynthesis, measured as the yield of photosystem II (Fv/Fm), there were no significant differences between treatments in the present study. Also for plant height, no significant differences were present. It was concluded that increasing the proportion of blue light from 2% to 14% will generally decrease fresh mass production, but not significantly reduce stem elongation.

Our research aims to develop an intelligent control system for optimizing the operation of lighting systems in greenhouses with a high proportion of local renewable energy using adaptive control methods, artificial intelligence algorithms and optimization of built-in lighting control. Through this, lighting systems will be optimized, energy consumption will be minimized and the lighting system will be adapted to be able to handle a larger amount of local renewable energy production. Due to the level of complexity, in this paper, we have focused to integrate a climate controlled greenhouse and the solar energy system. In particular, their respective components were selected and integrated by means of a distributed control architecture. As a first approach, the estimation of the solar power production from the solar cell panels was done based on the solar irradiation registered by the solar irradiation sensor embedded in the outdoor climate sensor system from the greenhouse.