We consider the 0-1 Knapsack Problem with Setups. We propose an exact approach which handles the structure of the ILP formulation of the problem. It relies on partitioning the variables set into two levels and exploiting this partitioning. The proposed approach favorably compares to the algorithms in literature and to solver CPLEX 12.5 applied to the ILP formulation. It turns out to be very effective and capable of solving to optimality, within limited CPU time, all instances with up to 100000 variables.
In this paper, we present a novel distributed framework for real time management and co-simulation of Demand Response (DR) in smart grids. Our solution provides a (near-) real-time co-simulation platform to validate new DR-policies exploiting Internet-of-Things approach performing software-in-the-loop. Hence, the behavior of real-world power systems can be emulated in a very realistic way and different DR-policies can be easily deployed and/or replaced in a plugand-play fashion, without affecting the rest of the framework. In addition, our solution integrates real internet-connected smart devices deployed at customer premises and along the Smart Grid to retrieve energy information and send actuation commands. Thus, the framework is also ready to manage DR in a real-world Smart Grid. This is demonstrated on a realistic smart grid with a test case DR-policy.
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