Efficient resource allocation is an important problem that aims for a “greener” and more environmentally friendly electric power grid. The smart behavior of the newly emerged grid, combined with two-way communication between users and the operator allows for actions like measurement, monitoring, prediction, and control signaling so as to maximize social welfare. We introduce a framework for optimal resource allocation in smart grids that also considers the uncertainty in message signaling. This introduces communication network externalities, added on top of the existing transmission network ones. The task at hand resembles the so called local public goods problem in mathematical economics terminology, a problem impractical to solve using centralized mechanisms. We propose an iterative, decentralized algorithm for its solution. The algorithm is scalable for deployment in large networks since it requires only messages per network user per iteration, where is the number of users. Moreover, it is guaranteed to converge, does not require revelation of private information from each user and all algorithm actions can be realized by programmable smart devices of the grid.