Abstract
In recent years, we have been witnessing a real explosion of information, due in large part to the development in Information and Knowledge Technologies (ICTs). As in-formation is the raw material for the discovery of knowledge, there has been a rapid growth, both in the scientific community and in ICT itself, in the approach and study of the phenomenon called Big Data (BD) [1]. The concept of Smart Grids (SG) has emerged as a way of rethinking how to produce and consume energy imposed by economic, political and ecological issues [2]. To become a reality, SGs must be sup-ported by intelligent and autonomous IT systems, to make the right decisions in real time. Knowledge needed for real-time decision-making can only be achieved if SGs are equipped with systems capable of efficiently managing all the information sur-rounding their ecosystem. Multi-Agent systems have been increasingly used from this purpose. This work proposes a system for the management of information in the context of agent based SG to enable the monitoring, in real time, of the events that occur in the ecosystem and to predict upcoming events.

Abstract
The penetration of micro-generation brings complex problems to the energy field. In this way, various simulators were designed to give decision support for the stakeholders, however, they intent to solve very specific problems. The proposed tool enables the interoperability between heterogeneous simulators, to simulate more complex problems.

Abstract
One of the main challenges in power & energy systems is the development of decision support tools which approach the problem as a whole. In this scope, this work contributes to the increase of the interoperability between heterogeneous agent based systems through the use of ontologies, enabling semantic communications.

Abstract
Electricity markets are not only a new reality but also a constantly evolving sector, due to the high frequency of changes in their rules. Simulation tools combined with Artificial Intelligence techniques, particularly multi-agent simulation, can result in a sophisticated and very useful tool in this context.

Abstract
This work proposes a organization-based Multi-Agent System that models Local Electricity Market (MASLEM). A bottom-up approach is implemented to manage energy in this work. In this context, agents are able to connect to each other and the power grid to transact electrical energy, and manage their inside electrical energy independently. A Demand Response Program (DRP) based on Indirect Load Control (ILC) method is also used. The performance of our work is evaluated through an Agent Based Modeling (ABM) implementation.

Abstract
Currently, it is possible to find various tools to deal with the unpredictability of electricity markets. However, they mainly focus on spot markets, disfavouring bilateral negotiations. A multi-agent decision support tool is proposed that addresses the identified gap, supporting players in the pre-negotiation and actual negotiation phases.