A decentralized resource allocation approach for sharing renewable energy among interconnected smart homes

The paper deals with the scheduling of energy activities of a group of interconnected users that buy energy from a producer and share a renewable energy source. The scheduling problem is stated and solved with a twofold goal. First, the model is formulated to ensure social welfare-optimal allocation of the energy produced from the shared renewable energy generator. Second, the model aims at cost-optimal planning of users' controllable appliances taking into account a realistic time-varying quadratic pricing of the energy bought from the distribution network. The solution approach relies on a decentralized optimization algorithm that is composed by a two-level iterative procedure combining Gauss-Seidel decomposition with competitive game formulation. A case study simulated in different scenarios demonstrates that the approach allows exploiting the potential of renewable energy sources' sharing to reduce individual users' energy consumption costs, limiting the peak average ratio of energy profiles and complying with the customer's energy needs.