A Logistics Management System for a Biomass-to-Energy Production Plant Storage Park

Abstract

The biomass industry is growing due to the current search for greener and more sustainable alternatives to fossil energy sources. However, this industry, due to its singularity, presents several challenges and disadvantages related to the transportation of raw materials, with the large volumes that are usually involved. This project aimed to address this internal logistics situation in torrefied biomass pellets production with two different biomass storage parks, located in Portugal. The main park receives raw material coming directly from the source and stores it in large amounts as a backup and strategic storage park. The second park, with smaller dimensions, precedes the production unit and must be stocked daily. Therefore, a fleet of transport units with self-unloading cranes is required to help to unload the biomass at the main park and transport the raw material from this park to the one preceding the production unit. Thus, the main goal was to determine the dimensions of the fleet used in internal transportation operations to minimize the idle time of the transport units using a methodology already in use in the mining and quarrying industry. This methodology was analyzed and adapted to the situation presented here. The implementation of this study allows the elimination of unnecessary costs in an industry where the profit margins are low.

Risk Assessment and Analysis of Biomass Energy Engineering Project Management under the Concept of Sustainable Development

“…The optimal decision model of each stage is constructed in reverse order, and the optimal value of the corresponding "expected cost" function can be obtained for any one. The specific expression form is shown in formula (11):…”

“…Since the data process is assumed to a Markov process, the "expected cost" function OðY − ZÞ and its expected value function Q + ðY, Z5Þ only depend on ξu rather than the entire time period. When ξ is a special case of stage independence, the conditional expectation in (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) can be replaced by the corresponding unconditional expectation, and the corresponding expectation function Ot + 1ðvzÞÞ does not depend on random input data sequence.…”

“…Chinese per capita energy resources are very limited, only equal to 1/2 of the world's average level; in terms of distribution area, North China and Northeast China have about 80% of mineral resources, and Southwest and Northwest regions have 70% of the country's hydropower resources [10]. Only 20% of the country's total energy resources are concentrated in densely populated areas such as East China, Central China, and South China [11]. In addition, the utilization rate of fossil fuels in my country is very high, and the combustion of fossil fuels will cause serious air pollution and environmental problems [12].…”

Wood Chip Storage in Small Scale Piles as a Tool to Eliminate Selected Risks

“…With a growing share of the use of wood-based renewable energy sources throughout the European Union, the issues of their quality, availability, and solutions to logistical problems are becoming more and more important [1][2][3][4][5][6]. Mass use of wood biomass is usually associated with its long-term, large-scale storage in power plants and heating plants [7][8][9][10][11]. There are a lot of parallels between storing biomass for each of these applications (e.g., chip storage for pulp and paper production) [12][13][14].…”