Biomass Feasibility Project Final Report - Xcel Energy

Dry Tons = The estimated quantity in dry tons of a given feedstock in each county.
Energy Content = The BTU content of a dry pound of a given feedstock
Technical Biomass Energy Potential
Since Theoretical Biomass Energy Potential does not account for physical factors which reduce
biomass harvests, like inefficient harvest technologies or the need to leave residues on the land
to maintain soil fertility and prevent erosion. We estimate the technical biomass energy
potential of each feedstock using the following equation.
EnergyTechnical = Dry Tons * RP * (1- MR) * Energy ContentBTU/pound* 2000pounds/ton
Where:
1,000,000 BTU/MMBTU
EnergyTechnical = The energy content in MMBTU for a given feedstock in each county that is
available for use as a bio-power feedstock.
Dry Tons = the estimated quantity in dry tons of a given feedstock in each county.
RP = The recoverable portion, expressed as a percentage, of a given feedstock that can
be technically recovered for use as a bio-power feedstock. This value also includes
expected losses due to storage, transportation, etc.
MR = The portion, expressed as a percentage, of a given feedstock that must remain on
the land for reasons of preventing soil erosion, maintaining soil productivity etc.
Energy Content = the BTU content of a dry pound of a given feedstock.
The theoretical potential for wet manures of sheep and beef cattle is further reduced because
they usually are not housed in an enclosure where their manure can be collected for a digester.
(Fehrs, 2000).
Economic Biomass Energy Potential
After we have arrived at an estimate of technical biomass energy potential, we subject
feedstocks to a series of screening criteria to determine which have economic biomass energy
potential for electric generation. Manures, a potentially important feedstock, call for a special
analysis detailed below. Other feedstocks are screened on the bases of price compared to
traditional fuels, and competition from non-energy industrial users.
Manures. To begin the screening of dairy and swine manures, we find in NASS, 2006 county data
that 13% of Minnesota’s cows live in 65 herds of more than 500 head, the smallest herd that can
support an anaerobic digester paired with an electrical generator (DOC, 2003a). Using these
values to calculate the average energy available at large dairy farms, we estimate the
economic potential of dairy manure in each county using the following formula:
Dairy EnergyTechnical= ((EnergyTechnical * 13%)/65) * # Farms
Where:
Dairy EnergyTechnical = The energy content, in MMBTU, of the dairy manure technically
available as a bio-power feedstock in a given county.
13% = The percentage of Minnesota’s dairy cows found in herds greater than 500 head.
65 = The number of dairy farms in Minnesota with herds greater than 500 head.
# Farms = The number of dairy farms in a given county with herds greater than 500 head.
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Identifying Effective Biomass Strategies:
Quantifying Minnesota’s Resources and Evaluating Future Opportunities