Moya Chavez, Francisco DavidDa Silva, Luiz C. P.Lopez A., Juan C.2020-02-102020-02-102018-01-0117905060https://repositorio.usc.edu.co/handle/20.500.12421/2727This study develops a mathematical model for the optimal scheduling of controllable electrical loads in a smart home - MCELS. The goal of the MCELS is to minimize the total cost of the energy consumed by the smart house while decreasing the power supplied by the distribution network, still respecting requirements stablished by the costumer. To verify the MCELS results, a GRASP algorithm was used to compare both methodologies. A typical residential user in the area of Sao Paulo (Brazil), which has strong solar radiation, is established as a case study. The results show that the GRASP algorithm reduces the energy purchased from the network in approximatively 4%. Meanwhile, the MCELS provides a reduction of 6% on the energy used from the grid. This work also includes simulations where an electrical vehicle equipped with batteries of high storage capacity is recharged. Analysis of the results showed a superior performance of the MCELS if comparison with the GRASP algorithm, in five major aspects: a) lower use of the grid, b) reduction of electricity bill, c) higher use of renewable sources, d) reduction of demand peaks, and e) lower computation timeenSmart HomesControllable Load SchedulingGRASPHome Energy ManagementDemand ResponseArticle