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This paper presents the specification of an architecture for self-organizing scheduling systems. The proposed architecture uses learning by observing the experts and interpretation of scheduling experience. The design of intelligent systems that learn with experts is a very hard and challenging domain because current systems are becoming more and more complex and subject to rapid changes. In this work, different areas as Intelligent and Adaptive Human-Machine Interfaces, Metacognition and Learning from Observation, Self-managed Systems, amongst others, are joint together resulting in a global fully integrated architecture for self-organizing scheduling systems.

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Power systems have been through deep changes, with their operation in the scope of competitive electricity markets (EM) and the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities. Virtual Power Players (VPPs) are a new player type which allows aggregating a diversity of players (distribution Generation, storage units, electrical vehicles, and consumers) to participate in the markets and to provide a set of new services promoting generation and consumption efficiency and to improving players’ benefits. A major task of VPPs is the remuneration of generation and of the services (e.g. market operation costs, and energy reserves) as well as charging energy consumption. This PhD research will contribute by developing fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in EM. © Springer International Publishing AG 2018.

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This paper presents a teaching/learning experiment running in the laboratorial curricular unit Project I of the 4th year of the Integrated Master in Industrial Electronics and Computers Engineering at the University of Minho. Project specifications were defined by the three teachers involved in the experience and students were encouraged to look on different solutions for a real-word problem. In a concurrent way, students designed, developed and implemented didactic rigs to control a gantry crane system. The control was performed in open-loop, based on the Posicast feedforward technique, and in closed-loop, using a two-degrees of freedom configuration. The experiment procedure and the project outcomes of two solutions proposed by the students are presented.