I3RES project

"ICT-based Intelligent management of Integrated RES for the smart grid optimal operation" (I3RES) is a project of the Framework Programme for Research and Technological Development (FP7), whose objectives are the integration of renewable energy sources into the distribution network, optimization energy flows entering the network, using the latest generation of storage systems to reduce fluctuations and the definition of processes between the different actors involved in an energy micro grid, the Consumer, the Distributor System Operator (DSO) and the 'AGGREGATOR'.
Whitin this project KES realized a monitoring infrastructure for energy microgrids, an implementation of forecasting algorithms based upon the integration of historical data, real time data and meteorological data for the determination of the most convenient network configuration integrated with RES and the realization of data mining and artificial intelligence techniques to analyze the consumers behavior and therefore the demand and production in the distribution network.

      

i3RES involved the construction of a modular, scalable and interoperable software infrastructure, middleware based and responsive to the SOA paradigm (Service Oriented Architecture) for monitoring and management of the electrical network elements.
KES designed and implemented Demand Side Management algorithms to support the Aggregator in the demand management on the base of historical data from the DSO and of the data from renewable energy sources with the identification and the definition of all the information exchange and energy processes that will occur in micro grids of the future in which the impact of RES will be increasing and the role of the Aggregator increasingly crucial.
For the optimal definition of power injection on the network, KES studied Optimal power flow algorithms and data mining techniques that would allow to obtain in a dynamic and evolutionary way the best configuration of the network, in terms of loads and storage, in relation to the energy produced from renewable energy sources and to that consumed by all devices.
In order to reduce electrical fluctuations by putting on the network a random amount of energy produced by RES, KES has been developed forecasting algorithms for the generation from wind and solar sources based on stochastic techniques and on the use of neural networks trained  with data obtained from production series and weather forecasts.

Are part of the partnership: European universities such as the Universidad Politecnica de Madrid and the University of Sannio, companies operating in both the production of electrical devices and in the production of new generation storage systems, as the Spanish company Installaciones Inabensa and the Estonian Skelethon Tech. It was also involved the Norwegian utility Nord-Trondelag Elektrisitetsverk AS, the Norwegian town Demo Steinkjer that represents a living lab for micro-grid energy and international research institutions such as the Norwegian Sintef and the Spanish Tecnalia. The activities carried out by KES are: the design and realization of a communication Gateway and of a single sign-on system that, through a GUI, integrates all project applications, the implementation of algorithms of generation from wind and solar sources, the creation of a communication infrastructure between the different actors involved, the implementation of the Optimal Power Flow  algorithm made by the university of Sannio and implementation of a Validation Tool to show the informational and economic processes between all the different actors involved in the energy market (the end customer, the distributor and the Aggregator).