This research directly couples investment decisions on distributed energy resources (DERs) with demand side management (DSM) strategies that can be adopted over time by residential communities. The formulation also takes into account factors that usually contribute to long-term market variations and short-term operational volatilities. This paper uses a high resolution adaptive model (Hi-RAM) for short-term load calculations on a premise that expected dynamical effects due to DSM strategies and their interactions cannot effectively be captured by traditional forecast models. The integration of Hi-RAM into investment formulation allows for certain What-If investment scenario analysis on the use of advanced technologies, new plug-ins, and consumer response to power price fluctuations, and more. To demonstrate the significance of coupling of DER investment decisions and DSM strategies, three scenarios are presented. The base scenario (Mode I) results can be reproduced using traditional forecast models and is included for baseline analysis and benchmarking. In Mode II, new load patterns for plug-in electric vehicles are introduced. Mode III is an extended version of Mode II, where smart devices are used within households. The comparison of investment decisions from the three modes clearly demonstrate that interaction effects of DSM strategies matter.