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Updated: Jul 13, 2025

Evaluation of Integrated Anaerobic Digestion and Hydrothermal Carbonization for Bioenergy Production
Published on: June 15, 2014
A method for determining the optimal number and location of biomass energy facilities
Chenshuo Ma1, Yifei Zhang1, Keni Ma2
1School of Architecture, Harbin Institute of Technology, Harbin, 150090, Heilongjiang, China; Key Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology, Ministry of Industry and Information Technology, Harbin, 150001, Heilongjiang, China.
Abstract:
The site selection of biomass energy facilities has always been a key part of energy spatial planning. The site suitability evaluation criteria of the existing studies are not comprehensive. On the other hand, most of the existing studies are to determine the only site, while less research on the multiple-facility planning. The aim of this paper is to identify the most effective number and location for biomass energy facilities. To achieve this objective, the Geographic Information System (GIS) is utilized to perform the following tasks: Generate a site suitability map for potential biomass energy facilities and identify suitable site candidates. The standardization of site suitability evaluation indicators is based on fuzzy logic, and indicator weights are determined based on the Analytic Hierarchy Process (AHP) evaluation of experts' opinions. 2. Develop planning schemes for biomass energy facilities for various number of proposed facilities, and subsequently determine the optimal scheme using multi-objective fuzzy comprehensive evaluation. The weight of each indicator is again determined using the AHP method. Following the analysis, it was found that in the case study of Fuxin City, the plans of 1 and 40 biomass energy facilities can achieve the lowest cost and the highest energy self-sufficiency level. However, both options have potential drawbacks that must be considered. The plan of 30 energy facilities has the highest comprehensive benefits, corresponding to the 30,919.75 yuan of transport cost (3748 yuan lower than the average transport cost) and 75.49% of energy self-sufficiency (67.21% of the average value). This work maximizes the comprehensive positive impacts in economic, environmental and social aspects.
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