Abstract
Co-firing from woody biomass feedstock is one of the alternatives toward increased use of renewable feedstock in existing coal power plants. However, the economic level of co-firing at a particular power plant depends on several site-specific factors. Torrefaction has been identified recently as a promising biomass pretreatment option to lead to reduction of the feedstock delivered cost, and thus facilitate an increase in the co-firing ratio. In this study, a mixed integer linear program (MILP) is developed to integrate supply chain of co-firing and torrefaction process and find the optimal level of biomass co-firing in terms of minimized transportation and logistics costs, with or without tax credits. A case study of 26 existing coal power plants in three Great Lakes States of the US is used to test the model. The results reveal that torrefaction process can lead to higher levels of co-firing, but without the tax credit, the effect is limited to the low capacity of power plants. The sensitivity analysis shows that co-firing ratio has higher sensitivity to variation in capital and operation costs of torrefaction than to the variation in the transportation and feedstock purchase costs.
Highlights
We extend production tax credit (PTC) to support biomass co-firing with existing coal power plants in the Great Lakes States area and estimate the impacts on co-firing ratios
This section describes the case study used to test the model. It estimates the optimal level of woody biomass co-firing and related logistics for existing 26 coal power plants in three Great Lakes States; Michigan (MI), Wisconsin (WI), and Minnesota (MN)
Four scenarios aretax developed, basedtoonsupport the biomass co-firing with existing coal power plants
Summary
Burning coal produces many gases and heavy metals, which affect the environment and human health [1]. Biomass transportation is often considered a competitive, low-margin business, as the inherent features of the feedstock result in a low-efficiency transportation enterprise [8] These features include a large number of points of origin for loads, often with limited accessibility, needs for specialized equipment that lessen opportunities for product backhauls, and a significant portion of operating hours spent loading and unloading the product [9]. We develop mathematical model to integrate supply chain of co-firing and torrefaction process and find the optimal level of biomass co-firing in terms of minimized transportation and logistics costs. The first section reviews past literature related to biomass co-firing ratio, torrefaction process, and transportation logistics, followed by introduction of methodology, including the mathematical model developed to estimate the cost minimized co-firing ratio.
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