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In the future smart grid, both users and power companies can benefit from real-time interactions and pricing methods which can reflect the fluctuations of the wholesale price into the demand side. In addition, smart pricing can be used to seek social benefits and to achieve social objectives. However, the utility company may need to collect various information about users and their energy consumption behavior, which can be challenging. That is, users may not be willing to reveal their local information unless there is an incentive for them to do so. In this paper, we propose an efficient pricing algorithm to tackle this problem. The benefit that each user obtains from each appliance can be modeled in form of a utility function, a concept from microeconomics. We propose a Vickrey-Clarke-Groves (VCG) based mechanism for our problem formulation aiming to maximize the social welfare, i.e., the aggregate utility functions of all users minus the total energy cost. Our design requires that each user provides some information about its energy demand. In return, the energy provider will determine each user's payment for electricity. The payment of each user is structured in such a way that it is in each user's self interest to reveal its local information truthfully. Finally, we present simulation results to show that both the energy provider and the individual users can benefit from the proposed pricing algorithm.