New, small-scale electric generation technologies permit utility customers to generate some of their own electric power and to utilize waste heat for space heating and other applications at the building site. This combined heat and power (CHP) characteristic can provide significant energy-cost savings. However, most current US utility regulations leave CHP standby rate specification largely to utility discretion resulting in claims by CHP advocates that excessive standby rates are significantly reducing CHP-related savings and inhibiting CHP diffusion. The impacts of standby rates on the adoption of CHP are difficult to determine; however, because of the characteristically slow nature of new technology diffusion. This study develops an agent-based microsimulation model of CHP technology choice using cellular automata to represent new technology information dispersion and knowledge acquisition. Applying the model as an n-factorial experiment quantifies the impacts of standby rates on CHP technologies under alternative diffusion paths. Analysis of a sample utility indicates that, regardless of the likely diffusion process, reducing standby rates to reflect the cost of serving a large number of small, spatially clustered CHP systems significantly increases the adoption of these technologies.