Biomass Feasibility Project Final Report - Xcel Energy

In addition, we include in BioPET a special category:
• fossil fuels.
These obviously are not biomass, but we include them for purposes of comparison and for
calculating co-firing applications. Because Minnesota does not have any native fossil fuel
resources, inventories are not included; however general fuel characteristics and prices are.
The other special category which is not included in BioPET but does come up for discussion in the
paper is:
• dedicated energy crops.
Dedicated energy crops are not included in the BioPET tool as a separate category because
thus far they are grown in test plots, not in fields as a commercial crop. But in this written report
we describe research in herbaceous crops, switchgrass, and diverse prairie grasses because
they are more likely to become important biomass energy crops in the near future.
BioPET Assumptions and User-Defined Fields (UDFs)
The BioPET computer tool allows the user to explore volumes of specific biomasses in any county
or combination of counties in the state. We used the same moisture and quality assumptions
consistently across all 87 counties in Minnesota. The user can look up those assumptions in
BioPET.
Although we made every effort to develop a comprehensive list of Minnesota biomass
feedstocks available in quantity, the user may want to research an additional source or a very
specific variation on one of the items listed above. For that reason BioPET is designed to also
accept user inputs. Users can enter and save their own feedstock characteristics in any of the
12 UDFs provided in BioPET.
Assessment
The general categories above define the areas in which we find biomass fuels. Within those
categories lie a wide variety of specific feedstocks which we examine in terms of:
• energy content (millions of BTUs (MMBTUs) per dry ton),
• volumes of biomass by county in Minnesota (dry tons),
• estimated processing costs ($/ton), and
• estimated delivery costs ($/ton/mile).
BioPET presents analyses of these factors in an easy-to- use electronic format. The user of this
computer tool can manipulate various feedstock, delivery and location scenarios in order to
arrive at the optimal cost per MMBTU for fully processed fuel delivered to a power plant at a
particular location in Minnesota.
ESTIMATION OF FEEDSTOCK CHARACTERISTICS
Since statistical information on biomass fuels comes from a variety of sources that use differing
methodologies, we have had to normalize them so their performance in various combustion and
gasification processes can be compared. It should be noted that this still represents an
‘nominal’ value. Values can vary widely across regions and states. It is recommended that
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Identifying Effective Biomass Strategies:
Quantifying Minnesota’s Resources and Evaluating Future Opportunities