Abstract
The electricity markets environment has changed completely with the introduction of renewable energy sources in the energy distribution systems. With such alterations, preventing the system from collapsing required the development of tools to avoid system failure. In this new market environment competitiveness increases, new and different power producers have emerged, each of them with different characteristics, although some are shared for all of them, such as the unpredictability. In order to battle the unpredictability, the power supplies of this nature are supported by techniques of artificial intelligence that enables them crucial information for participation in the energy markets. In electricity markets any player aims to get the best profit, but is necessary have knowledge of the future with a degree of confidence leading to possible build successful actions. With optimization techniques based on artificial intelligence it is possible to achieve results in considerable time so that producers are able to optimize their profits from the sale of Electricity. Nowadays, there are many optimization problems where there are no that cannot be solved with exact methods, or where deterministic methods are computationally too complex to implement. Heuristic optimization methods have, thus, become a promising solution. In this paper, a simulated annealing based approach is used to solve the portfolio optimization problem for multiple electricity markets participation. A case study based on real electricity markets data is presented, and the results using the proposed approach are compared to those achieved by a previous implementation using particle swarm optimization.

Abstract
The restructuring of electricity markets brought many changes to markets operation. To overcome these new challenges, the study of electricity markets operation has been gaining an increasing importance. With the emergence of microgrids and smart grids, new business models able to cope with new opportunities are being developed. New types of players are also emerging, allowing aggregating a diversity of entities, e.g. generation, storage, electric vehicles, and consumers. The virtual power player (VPP) facilitates their participation in the electricity markets and provides a set of new services promoting generation and consumption efficiency, while improving players' benefits. The contribution of this paper is a customized normalization method that supports a clustering methodology for the remuneration and tariffs definition from VPPs. To implement fair and strategic remuneration and tariff methodologies, this model uses a clustering algorithm, applied on normalized load values, which creates sub-groups of data according to their correlations. The clustering process is evaluated so that the number of data sub-groups that brings the most added value for the decision making process is found, according to players characteristics. The proposed clustering methodology has been tested in a real distribution network with 30 bus, including residential and commercial consumers, photovoltaic generation and storage.

Abstract
The electricity market sector has suffered massive changes in the last few decades. The worldwide electricity market restructuring has been conducted to potentiate the increase in competitiveness and thus decrease electricity prices. However, the complexity in this sector has grown significantly as well, with the emergence of several new types of players, interacting in a constantly changing environment. Several electricity market simulators have been introduced in recent years with the purpose of supporting operators, regulators, and the involved players in understanding and dealing with this complex environment. This paper presents a new, enhanced version of MASCEM (Multi-Agent System for Competitive Electricity Markets), an electricity market simulator with over ten years of existence, which had to be restructured in order to be able to face the highly demanding requirements that the decision support in this field requires. This restructuring optimizes the performance of MASCEM, both in results and execution time.

Abstract
The Arrowhead Framework is a European effort that aims to apply Service Oriented Architecture to the embedded systems' world. The Event Handler system is a component that supports the handling of events, and in that sense it enriches service-oriented applications with the capabilities of interacting via the publish/subscribe paradigm. In fact, the Event Handler system is in charge of the notification of events that occur in a given Arrowhead compliant installation, manages producers and consumers of events, allows filtering of messages, and manages historical data regarding events. This latter capability is performed either on local files, on a database, or through another component of the Arrowhead Framework-the Historian system. The net result of the integration of the Event Handler in an Arrowhead Framework simplifies and empowers the communication of its components, as it is demonstrated in the paper with two examples: the management of application faults, and the support to quality of service of orchestrated services. © 2016 IEEE.

Abstract
The Arrowhead Framework is a European effort that aims to apply Service Oriented Architecture to the embedded systems' world. The Event Handler system is a component that supports the handling of events, and in that sense it enriches service-oriented applications with the capabilities of interacting via the publish/subscribe paradigm. In fact, the Event Handler system is in charge of the notification of events that occur in a given Arrowhead compliant installation, manages producers and consumers of events, allows filtering of messages, and manages historical data regarding events. This latter capability is performed either on local files, on a database, or through another component of the Arrowhead Framework-the Historian system. The net result of the integration of the Event Handler in an Arrowhead Framework simplifies and empowers the communication of its components, as it is demonstrated in the paper with two examples: the management of application faults, and the support to quality of service of orchestrated services. © 2016 IEEE.

Abstract
This paper presents how the ICT infrastructure developed in the European ENCOURAGE project, centered around a message oriented middleware, enabled energy savings in buildings and households. The components of the middleware, as well as the supervisory control strategy, are overviewed, to support the presentation of the results and how they could be achieved. The main results are presented on three of the pilots of the project, a first one consisting of a single household, a second one of a residential neighborhood, and a third one in a university campus.