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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 2 - DREAM-GO (Enabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach)

Teaser

Summary

DREAM-GO had as main objective to conceive, develop, implement, and validate models enabling Demand Response (DR) for short and real-time efficient and market based smart grid operations. DREAM-GO activities and results have been planned so as to significantly advance the state of the art by developing: business models for short and real-time DR in smart grids; models and methods to simulate and assess the use of short and real-time DR in smart grids; and specifications for the communications, devices, and methods to enable Direct Load Control (DLC) of consumersâ€™ loads.
DREAM-GO identified new opportunities for short and real-time demand response and innovative contracts. The DR programs already implemented in practice as well as the newly designed DR programs have been organized, and computationally implemented serving as the basis for a Demand Response Registration Digital (D2RD) framework.
DREAM-GO approach considers that power system operation and management and the electricity market operation are strongly connected. Missing an adequate modelling of their interrelationships is a strong limitation in the present state of the art. DREAM-GO succeeded in significantly contributing to overcome that limitation.
A complex multiagent based simulation infrastructure has been developed in the scope of the Project. This infrastructure includes a community of multi-agent systems, putting together computationally simulated elements, emulated elements, and real-world elements (namely, real buildings, loads, photovoltaic panels, etc.) of smart grids.
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.

Work performed

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.

Final results

EUâ€™s huge investment on distributed energy resources with renewable based electricity generation has made European researchers advance on its management and control. As competitive markets have been consolidating their operation throughout Europe, market aspects and simulation are also strong topics of European research. By raising knowledge on the Demand Response approach in the EU, DREAM-GO results can significantly contribute to increase smart grid efficiency and consumers active participation.
DREAM-GO significantly contributed to the advancement of the state of the art namely in what regards short and real-time demand response namely concerning business models, real-time simulation, and technologic infrastructure.