SmarterEMC2 implemented ICT tools that support the integration of consumers through Demand Response services and the integration of DG/RES through Virtual Power Plants. The realization of the DR pilots with residential, commercial and industrial customers, provided solid indications that such schemes have an added value for DSOs and other parties such as electricity customers, retailers, aggregators for which international experience also indicates promising results. The key metrics of the pilot indicated that customers actively participated in the DR actions by reducing their load during the events scheduled by the DSO, whilst the impact, particularly for the C&I DR (commercial and industrial) pilot is plausible in terms of both economic efficiency and sustainability. The VPP management solution implemented in the project was used primarily to explore the feasibility of leveraging VPP settings in voltage support services requested by a DSO. The outcome of the executed scenarios showcased the feasibility of voltage control scenarios (i.e. voltage was restored within the safety margins), while for a significant percentage of tests along with the primary objective that was achieved, other secondary objectives, such as reduction of active power losses was also achieved. As far as the market participation case was concerned, the accuracy and general effectiveness of this VPP functionality have produced exceptional behaviour when it comes to achieving the promised flexibility. The project also explored via simulations, whether the existing telecommunication infrastructure is sufficient to support in mass scale the emerging business models and Smart Grid services. The most promising finding on this is that smart data aggregation systems could fully exploit Radio Frequency (RF) bandwidth by opportunistically accessing licensed bandwidth, leading to low-latency and reliable communication links in smart grid communication networks, which can bring many benefits to power system measurement, control and operation, such as phasor measurement, voltage control, and state estimation. Moreover, the simulations showcased that a smart data aggregation system can have very low requirements on the resources of computation and memory.