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Economic Feasibility Study of Colorado Anaerobic Digester Projects ...

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6.0 <strong>Economic</strong> Analysis: Budgeting and Sensitivity Analysis.<br />

6.1 Summary. This section presents an economic analysis <strong>of</strong> AD projects in <strong>Colorado</strong>. The<br />

economic analysis is comprised <strong>of</strong> an enterprise budget, a sensitivity analysis, and a<br />

summary/interpretation <strong>of</strong> findings.<br />

In summary, there is potential for a positive rate <strong>of</strong> return on co-digestion projects in the<br />

state <strong>of</strong> <strong>Colorado</strong>. Values used in the enterprise budget reflect a 3.66% annual return on<br />

investment. However, in order to achieve a positive return on investment, several key<br />

assumptions must be met, including $5.50/tonne carbon credits and controlled production<br />

costs. At present, conditions required for a positive AD project return are not favorable.<br />

Furthermore, due to the very small number <strong>of</strong> AD projects in the region, variations in the<br />

data may be observed when more AD units have been installed. To address this, three<br />

budgetary conditions have been proposed:<br />

• A baseline <strong>of</strong> “expected” economic conditions, showing a positive annual return on<br />

investment.<br />

• A budget modeling an approximate 20% reduction in each <strong>of</strong> the variables (unless<br />

otherwise specified) and a negative annual return on investment <strong>of</strong> -30.78%.<br />

• A budget modeling a 20% increase in each <strong>of</strong> the variables (unless otherwise<br />

specified) and a 46.45% return on investment.<br />

The enterprise budget and the accompanying financial assumptions for each <strong>of</strong> the<br />

conditions are discussed in Section 6.2.<br />

The sensitivity analysis measures the responsiveness <strong>of</strong> income to a 1% change in<br />

operational variables. In other words, the sensitivity analysis effectively accounts for price<br />

volatility and models how these price changes affect the viability <strong>of</strong> a project. Operational<br />

variables selected for the sensitivity analysis were identified through interviews with<br />

technology providers, agricultural operations managers, and academic and trade<br />

publications. In summary, operational income was most sensitive to changes in production<br />

costs. A 1% change in production costs resulted in a 14.54% change in income. Examples<br />

<strong>of</strong> production costs might include unplanned AD maintenance and increases in labor.<br />

Operational income was also sensitive to energy production. A 1% change in energy<br />

production capacity (which is a function <strong>of</strong> engine efficiency and energy prices) yielded an<br />

11.14% change in operational income. The results <strong>of</strong> the sensitivity analysis are consistent<br />

with anecdotal reports from agricultural producers, who report that changes in costs and<br />

energy production have a significant impact on project returns. An in-depth discussion <strong>of</strong><br />

the sensitivity analysis is presented in Section 6.3<br />

<strong>Economic</strong> <strong>Feasibility</strong> <strong>Study</strong> <strong>of</strong> <strong>Colorado</strong> <strong>Anaerobic</strong> <strong>Digester</strong> <strong>Projects</strong><br />

Prepared by Dr. Catherine Keske, <strong>Colorado</strong> State University<br />

August 2009<br />

Page 44 <strong>of</strong> 79

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