Abstract
Power systems worldwide are complex and challenging environments. The increasing necessity for an adequate integration of renewable energy sources is resulting in a rising complexity in power systems operation. Multi-agent based simulation platforms have proven to be a good option to study the several issues related to these systems. In a smaller scale, a home energy management system would be effective for the both sides of the network. It can reduce the electricity costs of the demand side, and it can assist to relieve the grid congestion in peak times. This paper represents a domestic energy management system as part of a multi-agent system that models the smart home energy system. Our proposed system consists of energy management and predictor systems. This way, homes are able to transact with the local electricity market according to the energy flexibility that is provided by the electric vehicle, and it can manage produced electrical energy of the photovoltaic system inside of the home. © 2017 IEEE.

Abstract

Abstract
Cyber-Physical Systems (CPS) are creating new market opportunities and business models for all kind of European Industries. CPS-based platforms are increasing in their size and target application areas in a steady manner. However, even if progress is made every day supported by continuous technological advancements, CPS application and deployment is still challenging. Many solutions have been made available or is currently under development in several research projects/initiatives. Typically, these solutions show no interoperability between each other and are tailored to a specific application context. Thus, there is an urgent need for a clear definition of what a CPS-populated system actually is. This will provide a common ground for designing and building interoperable CPS-populated systems. Interoperability represents one of the most challenging problems for such systems essentially due to their intrinsic characteristics: heterogeneity, distribution and networked. These must be addressed to allow the cooperation and collaboration between all the actors of the system. In this landscape, the MANTIS project is aimed to provide a reference model for interoperable and interconnected CPS-populated systems for maintenance-related ecosystems, which is the focus of this paper.

Abstract
Energy management in buildings can provide massive benefits in financial and energy saving terms. It is possible to optimize energy usage with smart grid techniques, where the benefits are enhanced when the energy consumer can trade the energy on energy markets, since it forces energy providers to compete with each other on the energy price. However, two hurdles oppose this approach: the devices providing control over appliances do not interoperate with each other; and energy markets limit trading activities to large quantities of energy, thus impeding access for small consumers. This work considers using the FlexOffer (FO) concept to allow the consumer to express its energy needs, and FO-related mechanisms to aggregate energy requests into quantities relevant for energy markets. Moreover, the presented system, named FlexHousing, is based on the Arrowhead Framework - a framework that simplifies design and implementation of distributed applications by means of normalizing communication via services - and exploits its Service Oriented mechanisms to provide device interoperability. The implemented FlexHousing system uses multi-level FO aggregation to empower either the final user, for example the owner of an apartment, to manage its own energy by defining their flexibilities, or to offload this responsibility to an energy manager who takes care of all the apartments in a building or set of buildings.

Abstract
Nowadays, collecting complex information regarding a machine status is the enabler for advanced maintenance activities, and one of the main players in this process is the sensor. This paper describes modern maintenance strategies that lead to Proactive Maintenance (PM), which is the most advanced one. The paper discusses the sensors that can be used to support maintenance, as pertaining to different categories, spanning from common off-the-shelf sensors, to specialized sensors monitoring very specific characteristics, and to virtual sensors. The paper proceeds then to detail three different real world examples of project pilots that make use of the described sensors, and draws a comparison between them. In particular, each scenario has got unique characteristics and prefers different families of sensors, but on the other hand provides similar characteristics on other aspects. In fact, the paper concludes with a discussion regarding how each scenario can benefit from PM and from advanced sensing.

Abstract
This article discusses how a business model based on traditional maintenance can evolve to generate servitization strategies, with the help of remote maintenance support. The application of cyber-physical systems and cloud technologies play a key role for such maintenance purposes. In fact, the utilization of large quantities of data collected on machines and their processing by means of advanced techniques such as machine learning enable novel techniques for condition-based maintenance. New sensor solutions that could be used in maintenance and interaction with cyber-physical systems are also presented. Here, data models are an important part of these techniques because of the huge amounts of data that are produced and should be processed. These data models have been used in a real case, supported by the Machinery Information Management Open System Alliance Open System Architecture for Condition-Based Maintenance standard architecture, for streamlining the modeling of collected data. In this context, an industrial use case is described, to enlighten the application of the presented concepts in a working pilot. Finally, current and future directions for application of cyber-physical systems and cloud technologies to maintenance are discussed.