© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works This study shows the results of the SABINA H2020 project, which analyzes the effect of two level optimization algorithms to increase the consumption of renewable power sources and reduce greenhouse gas emissions. First, at building level, a building algorithm maximizes the self-consumption of generated energy by its own renewable power sources. Second, at district level, a market integrated district algorithm takes into account aspects related to the electricity grid, such as the electricity generation mix and the prices of electricity and ancillary services, and aggregates the energy flexibility forecast of buildings to minimize the overall CO 2 emissions while ensuring a cost reduction to prosumers Peer Reviewed