Project
Optimal management of energy resources in greenhouse production systems
Greenhouse horticulture is a large consumer of fossil energy. Therefore, targets are set to reduce the use of fossil energy and CO2-emission by 45% in 2020 compared to 1990 (Valk and Poll, 2007). A lot of different conditioning equipment is available for growers to control the greenhouse climate and to produce and store energy. Because of that, the optimal utilization of energy resources has become a complex matter.
The main challenge of this project is to formulate and solve the optimizations problem, which can be characterized as a non-linear dynamic optimization problem with uncertainty in theoutdoor weather. This problem is divided into the following research questions:
How to properly define and solve the optimization problem?
How to deal with uncertainty in the weather?
How much energy conservation is achieved with optimal resource management compared to standard management practice?
How to implement the solution into the currently available ICT environment?
Different studies have clearly demonstrated the potential of model based dynamic optimization in greenhouse climate management. These studies form the basis to formulatethe control problem. A roadmap with five steps is defined to find an answer to the research questions stated before. The focus of this research will be on dealing with uncertainty in the weather during the scheduling and the generation of simplified operating schemes.
The final product will be the core of a control decision support system to help growers making operational decisions. Furthermore, a solution of the optimization problem associated with scheduling of the available energy resources under uncertainty is presented and proven to increase the energy efficiency compared to the current situation. Other results are the control strategies for a wide range of climate conditioning equipment available nowadays. Also insight into and explanation of the particular characteristics of the operating strategies are important for the interpretation of the results and the use of the system by growers.
