With a community model consisting of three typical types of users and an LSE, we presented a complementarily-based model for determining the dynamic prices. Our present study is confined under the following assumptions:
� The supplies to meet the community demand are only from the facilities that the community owns.
� Out of the two timescale aspects of the LSE's management, our study focused on the part of a day in advance planning .
� LSE has the information of the demand response curves of the typical user groups .
The model and numerical examples in this paper have shown that the dynamic pricing provides an effective instrument for efficient coordination of energy management. In this scheme, all the agents, type A, B, C user groups and LSE, responding to the price, behave driven by their own incentives. Our paper introduced only a simple example of uncertainty by including renewable generations as part of the energy sources. The risk caused by the uncertain renewable generation sources presents a challenge to energy management of the community. More general models accommodating such risk factors are yet to be developed.