The effect of biomass raw material collection distance on energy surplus factor

Study of the differences in collection scope of raw materials of biomass CHP plants caused by regional factors

Combined heat and power (CHP) plants fueled by biomass can collect and utilize waste straw resources in a productive way. This paper considers the impact of regional factors on biomass energy potential and the energy needs of the population, so as to study the differences in construction of biomass CHP plants and the collection scope of raw materials, and proposes evaluating suitability for biomass energy development based on scope of resource collection. Taking five counties in China as its study areas, this paper assesses biomass energy potential. A topology system of biomass CHP plants has been reasonably established in different counties through ArcGIS, the required installed capacity has been calculated according to the number of persons served by such plants. Finally, the collection length and corresponding value range of raw materials of CHP plants along roads has been obtained based on biomass energy potential and energy demand. The result shows that the differences in area, straw yield and biomass fuelization rate depending on regions have a great impact on biomass energy potential, while the residue-to-product ratio of straw and biomass calorific value have less of an impact. When the biomass energy per capita of a region reaches 9.75GJ/person, it is suitable for biomass energy development. The installed capacity in the biomass CHP plant system of each study area is mostly within the scope of 3-59 MW, and the collection length of corresponding biomass resources of such plants along roads is mostly within the scope of 5.09-25.23 km.

Regional bioethanol supply chain optimization with the integration of GIS-MCDM method and quantile-based scenario analysis

This study presents a novel decision-support framework for the bioethanol supply chain network planning and management under uncertainties. Under the holistic framework, the most suitable sites for biorefineries are first screened out by adopting a GIS-based multi-criteria decision-making approach. Then, a mixed-integer linear programming model combined with quantile-based scenario analysis is developed to determine the strategic planning (i.e. locations and size of biorefineries) and tactical management (i.e. biomass purchasing, feedstock transportation, bioethanol production, and product delivery) under uncertainties. The model can effectively search for reliable solutions under uncertainties and achieve tradeoff solutions with the consideration of decision makers' risk tolerance. The proposed framework is demonstrated through a case study in China. It is suggested to build seven biorefineries with a capacity of 100 million liters in Zhumadian city. Utilizing 41% of local agricultural residues could satisfy the bioethanol requirement in the transportation sector under the E20 policy. However, the estimated production cost of bioethanol in Zhumadian is very high, about 1.11 $/L, which makes it lose cost advantage in the fuel market. Thus, currently, effective subsidies, mandatory energy substitution policies, along other environmental regulatory measures are desired to promote the bioethanol industry development.

A method for determining the optimal number and location of biomass energy facilities

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.