The distribution of Electric Power (EP) is in an evolving revolution as production is transformed from aggregated into scattered schemes. Those who were once simple consumers today can also be EP producers (prosumers). This revolution is due to the use of Information and Communication Technologies (ICTs) creating smart EP networks (smart-grids), which improve the reliability, efficiency and economy of the electric power market.

However, the new EP distribution landscape, creates a number of problems such as imbalance between supply and demand, voltage instability and supply disruption. Especially important are the impacts on the introduction of Renewable Energy Sources (RES) where Volt / VAr performance and voltage stability are negatively affected, resulting often to disconnection of the RES farms from the grid in order to protect their equipment from overvoltages. Consequently, this leads to greater losses for the System Administrator and eventually to the impossibility of expanding RES and reducing CO₂ emissions.

The solution to address these problems comes through the innovative proposal of this project. Accordingly, this project aims at the development and introduction to the market of a Decision Making Support System (DMSS) in real time (iReact-NG) to achieve optimal operation on EP distribution networks, performing parallel simulations of the smart-grid operational scenarios under consideration, merging historical data (past), current states and automation (present), and co-simulation services (future). The DMSS to be developed will make extensive use of computational intelligence methods, for modelling, as well as optimizing the network. The proposed solution is an improvement of existing technology of EMTech company, called iReact, which already achieves minimization of energy losses and the release of capacity in Electric Power distribution substations.

The targets of the proposed research are as follows:

• Produce reliable short-term predictions of the behavior of a smart-grid using cooperative simulation and machine learning methods 
• Exploit the forecasts for optimal management of the resources
• Development of a smart-grid simulation workshop for studying optimization approaches for load balancing, Volt / VAr control, scheduling of scattered RES, and in general facilitating the investigation of future smart-grid functions through a multidisciplinary virtual cooperative simulation methodology and evolutionary computation methods
• Generate new knowledge
• Improve the competitiveness of the business
• Create new jobs
• Achieve energy efficiency through additional optimization in heat loss reduction and capacity release, reduction of operating and maintenance costs, and increase of RES penetration

The proposed system will incorporate the following technologies:

• iReact
• FusiX
• Generalized EP distribution network model and load prediction algorithms
• Distributed control, network optimization, and RES time scheduling
• Hardware-in-the-Loop/HIL
• Web-GUI

The project comprises 2 partners, namely EMTech (coordinator) and the Laboratory of Telecommunications, Signal Processing and Intelligent Systems of the University of West Attica.