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Advances in information technology, ubiquitous communications, and distributed generation and storage reveal new opportunities for the participation of demand-side resources in balancing the physical and economic operation of electric power systems. To better understand the potential impact of this participation, accurate, detailed energy resource models are necessary at the distribution feeder level. This presentation describes a detailed approach to residential energy resource modeling that preserves the individual characteristics of major residential appliances and human behavior patterns so that their contribution to energy efficiency schemes and intelligent demand curtailment algorithms is properly portrayed. These models are derived from previous analyses of residential and commercial building systems supported by data collected from the end-use load and consumer assessment program (ELCAP) undertaken by the Bonneville power administration from 1983 to 1990. Preliminary results of using these models in distribution system simulations indicate that non-obvious, complex behavior patterns can emerge when consumers are confronted with varying price signals.