This paper describes the design, implementation, evaluation, and results from energy reduction contests at the University of Dayton in its 350-house student neighborhood.

We describe the lean energy analysis (LEA) methodology for graphically and statistically analyzing a manufacturing plant's energy use. LEA can allow energy end uses such as production, space conditioning, and general facility support to be identified.

We analyze the energy use characteristics of the University of Dayton's 350-house student neighborhood in relation to number of occupants, time of occupancy, weather, house structure quality, and occupant behavior. Using software, we can predict the energy use of a house for typical occupant behavior.

We describe energy reduction studies and contests from the University of Dayton's 350-house student neighborhood from around 2003. We also present results and suggested utility billing policy changes for the university.