Electronic spreadsheets play an indispensable role in the simulation, modeling, and analysis of bioenergy systems, and their results have the ability to affect decision-making significantly. Prior research has shown that spreadsheets are highly error-prone, and that a large percentage of these errors are difficult to detect. To that end, we developed computer code (implemented in Visual Basic for Applications, running under Microsoft Excel) to detect a particularly insidious form of spreadsheet error: the hard-coding error. These errors are defined as the presence of one or more unreferenced numerical values in a cell formula. Hard-coding errors are dangerous because they are a likely source of erroneous constants and/or non-updating assumptions. The code was used to audit six spreadsheets relevant to bioenergy systems, three developed in our lab (and reported on in other sessions at the AIM), and three in the public domain. The preliminary audit results were analyzed to understand the nature and distribution of hard-coding errors. The preponderance and diversity of hard-coding errors in these spreadsheets motivated us to subcategorize them. Together, the hard-coding error detection program and sub-categorization program provide a robust and rapid means of detecting and categorizing multiple types of hard-coding errors. Use of these programs could increase the reliability of spreadsheet software used in simulation, modeling, and analysis of bioenergy systems.