Abstract
The project Viable Alternative Mine Operating System ('VAMOS') develops a novel underwater mining technique for extracting inland mineral deposits in flooded open-cut mines. From a floating launch and recovery vessel a remotely-operated underwater mining vehicle with a roadheader cutting machine is deployed. The cut material is transported to the surface via a flexible riser hose. Since there is no direct intervisibility between the operator and the mining machine, the data of the sensor systems can only be perceived via a computer interface. Therefore, part of the efforts in the project focus on enhancing the situational awareness of the operator by providing a 3D model of the mine combined with representations of the mining equipment and sensor data. We present a method how a positioning and navigation system, perception system and mapping system can be used to create a replica of the physical system and mine environment in Virtual Reality (VR) in order to assist remote control. This approach is beneficial because it allows visualizing different sensor information and data in a consistent interface, and enables showing the complete context of the mining site even if only part of the mine is currently observed by surveying equipment. We demonstrate how the system is used during tele-operation and show results achieved during the field trials of the complete system in Silvermines, Ireland.

Abstract
The maximum mission duration and range of an Autonomous Underwater Vehicle are governed by the amount of energy carried on board and the way it is spent during the mission. While an increase in battery capacity and a decrease in electronics demand yield a direct increase in vehicle range, the impact of velocity variation is not so obvious. With slower velocities, most of the energy will be spent in electronics, not in motion, while for faster velocities a lot of energy will be needed to balance drag. Flying-type AUVs have a minimum velocity for the control surfaces to be effective, reducing the range of values for optimization. Hovering type AUVs, on the other hand, are typically slower moving platforms, able to travel at arbitrarily slow velocities. This paper addresses the analysis of the power consumption of hovering type AUVs, providing guidelines and analytical expressions to compute the optimal velocity when the vehicle travels in a single direction, and also when the trajectory is a combination of horizontal and vertical motion.

Abstract
This paper demonstrates day-ahead operation of power systems in the presence of a Demand Response Program (DRP) for serving exact amounts of demanded energy over the operational horizon. The proposed two-stage model features a here-and-now framework for shaping the aggregated demands during operation. First, the day-ahead scheduling problem is solved by adopting Unit Commitment (UC) to determine the generation level of power generation units as well as the Locational Marginal Prices (LMPs). Afterwards, the obtained LMPs are considered as the Time of Use (ToU) for the second step of the scheduling and reshaping the demanded loads of each aggregator. A new methodology is provided in this paper to estimate the reaction of consumers behavior in terms of encouraging their participation in DRPs. Unlike classical models which adopt load reduction over the operational horizon, this model ensures that the total demanded loads will be served. Therefore, the total supplied energy for the operational period before and after DRP implementation remains unchanged. Meanwhile, the total payment of consumers will be considerably reduced by adopting this strategy. The simulation results on the 6-bus test system clarify that the proposed model can reduce the total operational cost as well as smoothen the load profile and nodal prices over the operational horizon.

Abstract
Computer programming is a difficult subject that can only be mastered with lots of practice. It is therefore of primary importance to rise and retain students' engagement during a programming course, a task in which gamification has been proven as a competent method. Even though there are numerous reports on applying gamification to programming courses, there are no available open resources or dedicated platforms that could be used by programming teachers to gamily their courses, meeting both the requirements of being easy to adopt and leaving the decisions on the scope of the course and the level of gamification to the teachers themselves. In order to fulfill this gap, a consortium of four European institutions initiated a common project to develop open gamified programming exercises and interactive course materials for popular programming languages. In this paper, we report the results of the first stage of this work, which defined the range of gamification concepts to be covered within the developed framework and its evaluation by students.

Abstract
The increasing penetration of Distributed Energy Resources is changing the energy system by empowering consumers with the capacity to generate the electrical energy they need and sell its excess. This trend follows the EU strategy towards increasing competition and flexibility on the electricity market, as well as pushing the role of customers, expanding their rights and their involvement in energy communities (ECMs). Peer-to-Peer (P2P) energy markets appear as one of the possible solutions to accomplish these goals by providing direct energy trading between peers. Although P2P are being extensively addressed in the literature (e.g., market structures and platforms, experimental projects), few works offer a broad perspective of the different aspects involved in the actual implementation of these structures, as well as the real benefits that this type of markets can have for the players and for the system itself. This paper reviews business models related with ECMs and P2P markets, and the system benefits and main regulatory issues.

Abstract
This paper presents a method to identify the status (open or closed) of breakers in network branches, in the absence of status signal or electric measurements on the branch including the breaker. Indirect power measurements from the SCADA are combined to form a 2D image array, which is fed into a Convolutional Neural Network. The image construction is based on ranking measurements with the Cauchy-Schwarz divergence between two signal distributions (for breaker open and closed). The success rate obtained with this technique is close to 100% in the IEEE testbed adopted. © 2019 IEEE.