Diversification of energy sources optimization in greenhouses with linear programing method

Greenhouses are plant production facilities created with special cover elements and climate control systems, providing suitable environmental conditions are created for the cultivation of plants during periods when meteorological conditions are unfavorable. Heating and electrical energy costs are among the biggest operating costs in greenhouse cultivation. The seasonal changes in energy needs and consumption of greenhouses, and the availability of regionally different and diverse energy sources complicate energy system design and management. Unnecessary initial installation costs and then high operating costs problems arise in an improperly designed greenhouse during the installation phase. It is possible to use various energy sources together in the same ecosystem in an economical, safe and sustainable way, with energy management systems designed with appropriate optimization methods. Today, PV (Photovoltaic) systems and geothermal systems, which are among the renewable energy sources whose use is increasing rapidly, are used in greenhouses as well as classical fossil fuel energy sources. In this study, it is aimed to optimize the energy required for electricity and heating systems in greenhouses in terms of energy diversity, cost and CO2 emissions under the certain constraints such as accessible resources, land size and investment cost by using the DP (Linear Programming) method. Considering the lifetime of the PV system, the total energy amount that can be produced, the depreciation period and the system cost are calculated. The installed power of the PV system has been optimized using the DP method under the area where the panels can be installed, the energy consumption of the facility and the transformer power constraints. As a result of the optimization processes made with different constraint scenarios, PV system suggestions have been made that can meet the needs of the facility and have the optimum cost. In addition, the heat load calculation of the greenhouse planned to be installed was made, and the heating cost and CO2 emission were calculated in case the heat load obtained was met with various fossil fuel types and renewable energy sources. The amount of each heat source used has been optimized with the DP method and an optimal heating system has been designed for the greenhouse to be installed. In addition, the amount of CO2 emission was optimized in the developed application, and it was ensured that the greenhouse to be installed was designed to have a minimum carbon cost while it was still in the project phase. Through this study, an optimization method, which can analyze according to regional climate and geographical data, has been developed for greenhouses established in different sizes and purposes, where various energy sources are used together.