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This paper presents a receding horizon optimal control (RHOC) method with an economic objective function for balancing the cost of resources (resource use × cost) with income through yield (yield × product price). This paper considers the two elements that determine the income through yield. The first element is yield and associated fruit development. A new, computationally viable, approach to model the income through yield is proposed and its prediction accuracy with respect to the original model is evaluated. The new approach employs a model that predicts at each time step, the future income through yield based on the assimilates partitioned to the fruits at the current time step. Simulations suggest that the assumptions made to arrive at the model for the new approach, do not significantly affect the accuracy of the predictions. The second element considered in this paper is the product price and the uncertainty inherent in its forecasts. Historical product price data are used to generate artificial product price forecasts. An uncertainty analysis, in combination with the artificial product price forecasts, showed that the product price forecast error does not considerably affect the optimised control strategy. Season-wide simulations with RHOC suggest that the product price forecast error does not considerably affect the value of the economic objective function. • A computationally viable approach to model the income through yield is proposed. • The new approach to model income through yield allows for RHOC with a short horizon. • Historical product price data are used to create artificial product price forecasts. • Product price forecast errors do not considerably affect the control strategy. [ABSTRACT FROM AUTHOR]

LED lighting is appointed as the successor of HPS lighting in greenhouses since it can lead to a more sustainable cultivation, i.e. it converts electrical energy into photosynthetically active radiation more efficiently. To quantify the effect of this more efficient conversion within the operation of the greenhouse system, an optimal controller is proposed to generate optimal control trajectories for the controllable inputs of the greenhouse. The optimal controller makes use of an economic objective function, i.e. the difference between income (y i e l d × p r o d u c t p r i c e) and cost of resources (r e s o u r c e u s e × c o s t). The performance of this optimally controlled greenhouse system is compared with respect to the state-of-the-practice. Simulation experiments suggest optimal control can increase the economic objective by 10 % to 65.14 €. m − 2 compared to 58.96 €. m − 2 for the state-of-the-practice, for tomatoes cultivated in a Dutch weather conditions. The model of the optimally controlled greenhouse is used to compare the performance of different lighting systems, i.e. no lighting, HPS lighting and LED lighting. An increase of 9 % in the operational return is observed for LED lighting compared to HPS lighting. The electricity that is saved due to the more energy-efficient conversion in the LED lighting results in a 30 % decrease in carbon footprint when comparing a greenhouse with LED lighting to a greenhouse with HPS lighting. • A model suitable for the control of the greenhouse climate is developed. • The model allows for the optimization of a purely economic cost function. • Optimal control increases the return by 10% compared to the state-of-practice. • Simulations suggest a 9 % increase in return when using LED lights instead of HPS. • Carbon footprint decreases by 30 % when using LED lights instead of HPS. [ABSTRACT FROM AUTHOR]