การพัฒนาตัวแบบการหาค่าที่เหมาะสมที่สุดสำหรับการผลิตพลังงานทางเลือกจากชีวมวลเศษวัสดุการเกษตร

Abstract

Open burning of agricultural residues as a means of disposal causes massive atmospheric air pollution especially in northern Thailand. Converting this agricultural residual biomass to biomass energy can help reduce this problem. Cost is one of the major factors that aflect long-term success in the use of biomass energy. This research aims to develop a cost optimization model for electricity and heat energy production from agricultural residual biomass. Cost analysis of ten potential biomass materials which were the most abundant in Thailand was taken into account. They were analyzed by considering two parts of total cost; biomass and transportation costs. For transportation cost, K-means clustering was applied to group a number of demands via Orange Data Mining software and to identify centroids of each cluster using them as representatives in calculating transportation cost from a supply to a demand representative. Each kind of biomass was gathered into six different types of plant source. It was transported by 10 wheel-trucks. Then, a mathematical model was developed to find the optimal cost. The decision platform was built as a tool to evaluate cost via Excel Solver. From the findings in biomass electricity power plant (an electricity demand representative) and dried longan factory (a heat demand representative) case study, it was found that more than 40% total cost reduction could be achieved. From sensitivity analysis of biomass price to electricity generation and biomass sources to heat energy production, it was found that the biomass price and distance changes affected the answer of the program. Therefore, the users should consider other current and limited factors before using the tool to help in making decision for gaining the best results.