DREAM-GO addressed incentive-based and price-based demand response programs, covering the multiple possibilities of remunerating DR in the scope of demand response events (automated demand response, DLC) and by means of energy tariffs (time of use, real time pricing). New opportunities for short and real-time demand response and innovative contracts have been identified.
A complex multiagent based simulation infrastructure has been developed. This infrastructure includes a community of multi-agent systems, putting together computationally simulated elements (in particular, all the available intelligent algorithms used by the involved players), emulated elements (for instance wind emulators, industrial loads adapted to represent real load profiles), and real-world elements (namely, real buildings, loads, photovoltaic panels, etc.) that realistically create an augmented reality environment for smart grids. DREAM-GO has designed and produced a TOOls Control Center (TOOCC) that enables the strategic integration of different multi-agent simulation platforms, as well as the definition and simulation of scenarios. TOOCC allows, not only defining the models and setting up all the necessary parameters and definitions, but also executing the system in any domain machine without the need for having all necessary software installed in each machine that is being used for each simulation. DREAM-GO has also produced realistic models integrating detailed modelling of the electric networks and software based models that were used in real-time hybrid simulation supported by hardware-in-the-loop.
The implications of the use of direct load control, in technologic, social and economic terms have been studied, considering the targeted business models and the involved players. Several communication means and protocols have been explored in order to define the requirements for direct load control and communication. An approach has been developed in the scope of the project, which provides an experimental platform that uses several real consumption resources as well as some laboratorial equipment, implemented together with the fundamental concepts of automated DR, using basic hardware elements. Moreover, DREAM-GO outcomes include a large set of methods and technologic implementation, that enable the intelligent use of short and real-time DR programs in the context of real smart grids. These outcomes include: clustering models and methods for aggregation and remuneration of DR; models, methods and techniques for forecasting load, wind generation, and photovoltaic generation; optimization models, methods and techniques for energy resource optimization addressing short and real-time horizons; stochastic models for representing renewable energy resources based generation and consumption; load monitoring; real-time locational system for efficient energy use; models and implementation of embedded software for consumption monitoring and smart meters, enabling DR features with focus on DLC; study and implementation of automated DR schemes.
DREAM-GO largely disseminated its objectives and results, namely through more than 120 scientific publications, 10 special sessions and 12 invited talks in top-level conferences and workshops. DREAM-GO organized more than 130 seminars which worked as an efficient means of knowledge transfer among the partners.
DREAM-GO results are being exploited by the academic partners in subsequent projects and PhD thesis and by the non-academic partners by incorporating the new concepts and functionalities in their products and services.
