Engineering Science and Technology, an International Journal (Feb 2022)
Forecasting the biomass-based energy potential using artificial intelligence and geographic information systems: A case study
Abstract
To meet the energy demand in a sustainable way, fossil fuels must be substituted with alternative resources and technologies. This transformation is encouraged to reduce greenhouse gases using environmental-friendly practices. Although our country is rich in biomass resources due to climate, land conditions, agriculture and animal husbandry activities, the installed power is quite below its potential. Focusing on this point, the aim of this study is to propose a forecasting method that determines the quantities, distributions, production amounts, waste amounts and energy potential of various biomass resources consistently. The integrated method used in the solution utilizes statistical data and consists of artificial intelligence and geographic information systems. First of all, various bioenergy sources that can be used as energy resources have been determined, and the amount, yield, and energy potential of animal and agricultural wastes expected to occur in the following years have been estimated using an artificial intelligence-based method, support vector regression. Then, spatial analysis has been carried out using geographic information systems, and the distribution of existing and possible agricultural lands has been determined. Finally, the amount of energy that can be obtained using wastes from different biomass sources under various scenarios has been calculated and solutions have been compared. To the best of our knowledge, this study is the first proposing an integrated method consisting of support vector regression and geographic information systems to forecast the biomass-based energy potential in Turkey. The integrated method was applied to Acıpayam district in Denizli. Among the various scenario approaches, the cultivation of rapeseed (canola) plants on non-utilized arable land and the use of its wastes in bioenergy production have been found to yield the highest energy potential. The results showed that approximately 29,2%, 27,8%, and 27,6% energy increase could be obtained from agricultural residues of rapeseed in the next three years if it was planted on the quarter of the idle land. Besides, under this scenario, the total annual electricity demand of 6972, 6663 and 6545 houses could be met from agricultural residues in a sustainable and clean manner. The proposed method can be applied to different regions, various biomass resources and used to make strategic decisions in this field.
