Abstract
The government's new electric power development plan (PDP2018) focuses on developing renewable energy to the fullest potential in each area. One of the most valuable renewable energy sources in Thailand is biomass from the agricultural sector. Thailand has a target of 3,496 MW of electricity generated from biomass fuel, with the focus on the development of community biomass power plants. The main objectives of this research are to analyse the potential of energy generation from the harvesting of biomass residuals and to analyse the optimal locations for constructing a biomass power plant using multiple criteria analysis, Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and Geographical Information System (GIS) in Nakhon Ratchasima province, Thailand. The results indicate that the study site had a total area of 12,876.01 km2 of rice, cassava, sugarcane and maize planting areas in 2015, which resulted in a total crop production of 21.195 Mt, with an estimated total biomass residual of 9.098 Mt/y. Some portions of this biomass are used for existing electrical generation and other usages, totaling 4.889 Mt or equivalent to 53.7 % of the total estimated biomass residual. The remaining biomass residual is 4.209 Mt or 46.3 %, which can be used to generate electricity of 386.2 MW per year Land suitability evaluation is based on relevant physical and environmental indicators with specific criteria, as well as the government policy, law regulations, existing land use and the remain potential of crop residuals used as a fuel. It can be concluded that 5,284.85 km2 or 26.8 % of a total area are assessed as being best suitable for constructing the biomass power plant. Land suitability is mostly located in the western and southeastern regions of the province. The results of the evaluation of multiple crop biomass power generation potential with pixel-based data structure provide a map of biomass fuel source distribution and power generation potential. The potential shows the amount of electricity that is expected to be produced per unit area which is more accurate in terms of spatial than statistic approach. In addition, the spatial accuracy of electricity production potential data is also an important factor in determining which areas are suitable for a power plant, especially for small power producers (SPPs) such as villages or sub-district level communities.
