Bayesian network development for depots location selection with biomass supply system excellence

The renewable energy of the wood pellet market has taken great attention over the last few periods. However, the returns from the pellet business depend largely on how well the quality of biomass. The objective is to economically harvest pellets matching pellet standards set forward by the U.S. markets. The single-mindedness of this study is to develop a Bayesian network model to ensure a high-quality flow through the supply chain of the pallet industry in the top ten counties in Mississippi state. Multiple critical decisions (harvesting, storage, transportation, and quality control) of a biomass-to-pellet supply system could potentially affect the supply chain. The biomass-to pellet supply chain is an extremely challenging problem. For Multi-criteria Decision Making,we have developed criteria and sub-criteria associated with biomass-to pellet supply chain pellet. Experimental results specify that the biomass-to-pellet stream system is complex to the biomass quality parameters especially ash and moisture contents. Fifty were studied and ten locations were recommended and ranked based on affordability and resiliency of the availability of both corn stover and forest residues in the depot facilities. There are several anticipated and unpredicted energy turbulence in the Depots property. Pellets have been recognized as an alternative power approach to managing risk throughout power generation. These prospective users from using alternative power. This research proposes a solid foundation for in-depth future research to acquire detailed insights into how the Pellets depots location works in practice in Mississippi state to give a more substantial basis for strategic, tactical, and operational levels of possible risk profiles in Mississippi state