Simona Ruggeri

Multi-agent control system for increasing hosting capacity in active distribution networks with EV

Electrical mobility is based on the usage of electric vehicle (EV) as the main future technology to combat greenhouse gas emissions. Detailed knowledge about the future charging profiles of EVs appears to be missing in Literature. Slow chargers will be spread in the LV network or concentrated in some parking lots and connected to the LV or MV network. In the paper, an intelligent and decentralized Multi-Agent System (MAS) for handling EV charging control and management in the LV distribution networks is proposed. The MAS optimization algorithm proposed allows designing a valid and effective EVs charging system, able to analyse and meet the EV charging needs to contribute to the voltage control of the distribution network.

Co-simulation of distribution active management and distribution state estimation to reduce harmful effects of inaccuracies

Active networks are distribution networks with generators, storage devices, and flexible loads subject to control. Distribution Management System (DMS) needs to know the state of the network to coordinate distributed energy resources and manage and control the system economically and safely. The distribution systems have a very large number of nodes but few measurements points. Ad hoc Distribution System State Estimators (DSSEs) are needed to provide to the DMS the estimated status of the network (starting from real measurements and historical data, e.g. pseudo-measurements). The quality of the estimates can seriously affect the system management. In this paper, co-simulation of DMS and DSSE is presented. The impact of the uncertainty of the DSSE results on DMS operation is investigated by applying the proposed procedure to representative examples derived from ATLANTIDE project.

Application of ATLANTIDE models to harmonic penetration studies

This paper presents some of the results of a three-year research project entitled ATLANTIDE, which is aimed at developing a comprehensive digital archive of reference models of Italian distribution networks, including forecasted load and generation development evolving towards future smart grid scenarios. The paper focuses on the models developed for harmonic penetration studies and on how the results of these models can be included in the multi-objective optimization approach used by the Distribution Management System model developed in ATLANTIDE.

Impact of measurement accuracy in a multi-agent control system for active distribution networks

The control of active demand, electric vehicles, distributed generation and storage devices is the key to offer services that increase security and quality of supply of power systems, improve energy efficiency and reduce the cost for energy. Decentralised control systems have the merit to allow the operation of many small customers with a reduced information flow by exploiting local information gathered from the field with intelligent meters. Smart metering and ICT are the enabling technologies to offer market opportunities to the consumers, and to provide the Distribution System Operator (DSO) information regarding the behaviour of the prosumers. In this paper, an accurate Multi-Agent System (MAS) for the direct control of active demand in the distribution networks has been carried out. In particular, different levels of knowledge regarding the load behaviour have been considered. The impact of such knowledge in the optimal pattern of load demand that minimizes costs and improves the Power Quality of the distribution system has been evaluated. The discussed results prove the utility of the proposed analysis for the optimal design of MAS control.

Exploiting distributed energy storage to increase network hosting capacity with a Multi-Agent control system

Due to the increasing presence of renewable energy sources connected to the distribution network, new issues concerning the electrical systems balancing and safety are spreading. Using network solution, these issues can be solved only by reinforcing grid assets or preventing the connection of new power plants. On the contrary, Energy Storage Systems (ESS) are one of the no network solutions identified to solve the technical issues raised in distribution network, to increase the hosting capacity, without using costly solutions. Consequently, several countries (e.g. Italy, Germany, Spain, Japan) defined technical rules regarding connection, prescription and network support functions for ESS in distribution networks. In the paper, an intelligent and decentralized Multi-Agent System (MAS) for the direct control of ESS connected with photovoltaic power plants (PV) in the LV distribution networks has been carried out. The effect of the aggregation of small storage systems able to provide grid services will be tested in a typical Italian LV distribution network, underlining the utility of the proposed design of MAS control.

The e-visiØn project: Electric-vehicle integration for smart innovative 0-CO2 networks

The low-carbon society requires significant changes in the operation and planning of distribution systems. In order to exploit existing low voltage systems, Demand Side Integration is essential for offering services that increase security and quality of supply, improve energy efficiency and reduce the energy cost. The paper describes the three-year project e-visiØn, currently under completion, aimed at the integration of plug-in electric vehicles in Smart Grids and the simultaneous better exploitation of renewable energy sources in order to reach zero-CO2 networks and sustainable mobility.