Optimization decision-making for biomass gasification power projects siting considering the economic-environmental trade-off

Under the dual challenges of global fossil fuel depletion and increasing environmental externalities, biomass energy is emerging as a core strategic direction for the global energy transition. To systematically address the multiple uncertainties in the biomass power generation supply chain and the trade-offs between economic and environmental objectives, this study develops a spatial siting optimization framework for biomass gasification power generation (BGPG) projects. This framework integrates multi-criteria decision-making (MCDM) with geographic information systems (GIS) and incorporates type-2 fuzzy programming to quantify supply chain uncertainties and decision-makers' risk preferences. The results indicate that medium-sized BGPG plants, exemplified by a 6 MW capacity, exhibit significant robustness in terms of energy, economic, and environmental feasibility, making them the preferred scale for coping with multi-scenario fluctuations. Meanwhile, there is a notable trade-off relationship between net profit, net power generation, and carbon emission reduction. Furthermore, optimal planning schemes vary considerably across different scenarios: pessimistic scenario favors distributed layouts, whereas technological innovation scenario shows a clear preference for centralized power generation dominated by large-scale plants. This study aims to provide decision support for the utilization of agricultural residue resources in major grain-producing regions and holds positive significance for promoting the low-carbon transformation of energy structures.