Nonlinear multi-objective optimization model for a biomass direct-fired power generation supply chain using a case study in China

Using renewable resources to generate electricity is becoming increasingly common all over the world. As the largest energy consumer in the world, China has established many biomass direct-fired power plants in recent years. However, most of these power plants would not survive without government subsidies because of the high cost of fuel. This study focuses on the fuel supply chain of biomass direct-fired power generation, including the collection, transportation, processing, and storage of fuel; the study presents a nonlinear multi-objective optimization model. The purpose of this work is to determine the optimal quantity of electricity generation, as well as the ideal blending ratio, acquisition quantity and price of each kind of fuel so as to maximize the profit margins of biomass power plants and provide the most protection possible of social welfare considering environmental factors. The model we present was applied in a biomass direct-fired power plant in Heilongjiang Province in Northeast China; the subject plant was chosen from 13 biomass power plants that were investigated. Based on the case study, we obtained values for the optimal results and compared them with the actual situation. The optimal results confirmed that under the existing technical conditions, the overall benefit of biomass power generation leaves significant room for improvement, mainly by means of designing a more reasonable fuel supply mode. Finally, a sensitivity analysis showed that the best and most integrated efficiency in biomass power generation was achieved when the biomass electricity on-grid price was approximately 0.65 Yuan/kWh.