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International Conference on European Electricity Market, EEM

作者： Luís Rodrigues Kamalanathan Ganesan Fábio Retorta Fábio Coelho João Mello José Villar Ricardo Bessa Technology and Science INESC TEC - Institute for Systems and Computer Engineering Faculdade de Engenharia da Universidade do Porto Universidade do Minho Portugal

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

The European Union is pushing its members states to implement regulations that incentivize distribution system operators to procure flexibility to enhance grid operation and planning. Since flexibility should be obtained using market-based solutions, when possible, flexibility market platforms become essential tools to harness consumer-side flexibility, supporting its procurement, trading, dispatch, and settlement. These reasons have led to the appearance of multiple flexibility market platforms with different structure and functionalities. This work provides a comprehensive description of the main flexibility platforms operating in Europe and provides a concise review of the platform main characteristics and functionalities, including their user segment, flexibility trading procedures, settlement processes, and flexibility products supported.

关键词： Procurement technological innovation Reviews Terminology Europe Regulation Planning

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A Multi-User Multi-Robot Collaboration through Augmented Reality

A Multi-User Multi-Robot Collaboration through Augmented Rea...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： João G. Martins Gabriel M. Costa Marcelo R. Petry Paulo Costa António Paulo Moreira CRIIS – Centre for Robotics in Industry and Intelligent Systems INESC TEC – Institute for Systems and Computer Engineering Technology and Science Porto Portugal Faculty of Engineering University of Porto (FEUP) Porto Portugal

ISBN: (数字)9798350352344

ISBN: (纸本)9798350352351

Current industrial environments have multiple robots working alongside humans, thus providing an operator the ability to perceive the robot’s workspace correctly and to anticipate its intentions and movements through the visualization of the robot’s digital twin is of utmost importance for safe and productive human-robot collaboration scenarios. Much has been studied regarding single human-single robot collaborative scenarios, but few address multi-user multi-robot scenarios. To this end, this paper presents a multi-robot multi-operator architecture, where the users’ awareness is enhanced through an augmented reality head-mounted display. A multi-robot, multi-user collaborative scenario is presented in a laboratory environment with two industrial robots. Besides being able to interact with both robots in the system, each user becomes more aware of the robot’s workspace and its pre-defined trajectories. Furthermore, it presents how fiducial markers can help to establish the relation between the different coordinate frames.

关键词： Visualization Service robots Robot kinematics Scalability Collaboration User interfaces Trajectory

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A New Approach for Long-Term Demand Forecasting

SSRN

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SSRN 2024年

作者： Paulos, José Pedro Azevedo, Filipe Fidalgo, José Nuno INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal The Department of Electrical Engineering ISEP IPP - School of Engineering Polytechnic Institute of Porto Portugal The Department of Electrical Engineering and Computers of the Faculty of Engineering of the University of Porto Portugal INESC TEC Porto Portugal

The methodology adopted in this article is based on the principle that load diagrams to be forecasted have two distinct components: shape and magnitude. The present work was focused on the shape component, which was essentially defined by historic data and calendar information. The implemented approach was applied to five European countries using four years for training and one year for testing. The goal was to forecast the hourly demand diagram for an entire future year. The forecasting models were based on three forecasting techniques: General Regression Neural Networks (GRNN), Multiple Linear Regression (MLR), and Artificial Neural Networks (ANN). The performance analysis showed a mean absolute percentage error roughly between 2% and 6%, depending on the country and year being forecasted. Investigating the effect of temperature on predictions was the aim of a second study, which allows us to define uncertainty margins around the forecasted demand curve. This outcome is an essential element for power system planning. © 2024, The Authors. All rights reserved.

关键词： Multiple linear regression

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Case studies of development of verified programs with Dafny for accessibility assessment

arXiv

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arXiv 2023年

作者： Faria, João Pascoal Abreu, Rui Faculty of Engineering of the University of Porto Porto Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal INESC ID Lisbon Portugal

Formal verification techniques aim at formally proving the correctness of a computer program with respect to a formal specification, but the expertise and effort required for applying formal specification and verification techniques and scalability issues have limited their practical application. In recent years, the tremendous progress with SAT and SMT solvers enabled the construction of a new generation of tools that promise to make formal verification more accessible for software engineers, by automating most if not all of the verification process. The Dafny system is a prominent example of that trend. However, little evidence exists yet about its accessibility. To help fill this gap, we conducted a set of 10 case studies of developing verified implementations in Dafny of some real-world algorithms and data structures, to determine its accessibility for software engineers. We found that, on average, the amount of code written for specification and verification purposes is of the same order of magnitude as the traditional code written for implementation and testing purposes (ratio of 1.14) – an "overhead" that certainly pays off for high-integrity software. The performance of the Dafny verifier was impressive, with 2.4 proof obligations generated per line of code written, and 24 ms spent per proof obligation generated and verified, on average. However, we also found that the manual work needed in writing auxiliary verification code may be significant and difficult to predict and master. Hence, further automation and systematization of verification tasks are possible directions for future advances in the field. Copyright © 2023, The Authors. All rights reserved.

关键词： Formal verification

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Deep Reinforcement Learning Framework for UAV Indoor Navigation

Deep Reinforcement Learning Framework for UAV Indoor Navigat...

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Iberian Robotics Conference (ROBOT)

作者： João J. Martins Alexandre Amaral André Dias INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal FEUP - Faculdade de Engenharia da Universidade do Porto Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

Unmanned Aerial Vehicle (UAV) applications, particularly for indoor tasks such as inventory management, infrastructure inspection, and emergency response, are becoming increasingly complex with dynamic environments and their different elements. During operation, the vehicle's response depends on various decisions regarding its surroundings and the task goal. Reinforcement Learning techniques can solve this decision problem by helping build more reactive, adaptive, and efficient navigation operations. This paper presents a framework to simulate the navigation of a UAV in an operational environment, training and testing it with reinforcement learning models for further deployment in the real drone. With the support of the 3D simulator Gazebo and the framework Robot Operating System (ROS), we developed a training environment conceivably simple and fast or more complex and dynamic, explicit as the real-world scenario. The multi-environment simulation runs in parallel with the Deep Reinforcement Learning (DRL) algorithm to provide feedback for the training. TD3, DDPG, PPO, and PPO+LSTM were trained to validate the framework training, testing, and deployment in an indoor scenario.

关键词： Training Three-dimensional displays Operating systems Inventory management Inspection Autonomous aerial vehicles Deep reinforcement learning Vehicle dynamics Robots Testing

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Design and Development of a Fixed-Wing Tail-Sitter Tethered VTOL Drone with Custom Autopilot and Robust Control techniques 16th

Design and Development of a Fixed-Wing Tail-Sitter Tether...

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16th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2024

作者： Safaee, Ahmad Aguiar, A. Pedro Santos, Filipe Neves Moreira, Antonio Paulo SYSTEC-ARISE Research Center for Systems and Technologies Faculty of Engineering University of Porto Porto4200-465 Portugal INESC-TEC-Institute for Systems and Computer Engineering Technology and Science CRIIS-Centre for Robotics in Industry and Intelligent Systems Porto4200-465 Portugal INESC-TEC-Institute for Systems and Computer Engineering and DEEC/FEUP - Department of Electrical and Computer Engineering Faculty of Engineering of the University of Porto Porto4200-465 Portugal

ISBN: (纸本)9783031817236

The need for aerial platforms capable of sustained operation is critical in fields such as surveillance, agricultural monitoring, disaster response, and temporary telecommunication systems. Traditional unmanned aerial vehicles (UAVs) are hampered by limited battery capacity and inefficient energy utilization. This paper introduces an autonomous vertical flight drone tethered to a ground-based platform, which overcomes these limitations. The drone is designed to optimize its position and energy usage by harnessing wind currents, functioning similarly to a kite when conditions permit. This is enabled by a custom-designed autopilot system comprising both hardware and software tailored for this application. We detail the model identification process for three vertical take-off and landing (VTOL) drone systems, employing authentic data that measures lateral positional errors from the tether. Robust mixed sensitivity controllers are developed and implemented. The effectiveness of these controllers is validated through simulations showing their capability to handle uncertainties. Furthermore, the practical application and robust performance of the system are confirmed by a real-world case study, highlighting its potential in real operational environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： VTOL/STOL aircraft

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Deep Learning Strategies For Rare Drug Mechanism of Action Prediction

Deep Learning Strategies For Rare Drug Mechanism of Action P...

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International Joint Conference on Neural Networks (IJCNN)

作者： Gonçalo Ferreira Marco Teixeira Raquel Belo Wilson Silva Jaime S. Cardoso FEUP - Faculty of Engineering University of Porto Porto Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal

The application of machine learning algorithms to predict the mechanism of action (MoA) of drugs can be highly valuable and enable the discovery of new uses for known molecules. The developed methods are usually evaluated with small subsets of MoAs with large support, leading to deceptively good generalization. However, these datasets may not accurately represent a practical use, due to the limited number of target MoAs. Accurate predictions for these rare drugs are important for drug discovery and should be a point of focus. In this work, we explore different training strategies to improve the performance of a well established deep learning model for rare drug MoA prediction. We explored transfer learning by first learning a model for common MoAs, and then using it to initialize the learning of another model for rarer MoAs. We also investigated the use of a cascaded methodology, in which results from an initial model are used as additional inputs to the model for rare MoAs. Finally, we proposed and tested an extension of Mixup data augmentation for multilabel classification. The baseline model showed an AUC of 73.2% for common MoAs and 62.4% for rarer classes. From the investigated methods, Mixup alone failed to improve the performance of a baseline classifier. Nonetheless, the other proposed methods outperformed the baseline for rare classes. Transfer Learning was preferred in predicting classes with less than 10 training samples, while the cascaded classifiers (with Mixup) showed better predictions for MoAs with more than 10 samples. However, the performance for rarer MoAs still lags behind the performance for frequent MoAs and is not sufficient for the reliable prediction of rare MoAs.

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Characterization of an hollow core PCF for endoscopy applications: A proof concept

Characterization of an hollow core PCF for endoscopy applica...

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2021 Telecoms Conference, ConfTELE 2021

作者： Marques, Joao Novais, Susana Silva, Susana Frazao, Orlando Faculty of Sciences University of Porto Inesc Tec Department of Physics and Astronomy Porto Portugal Inesc Tec Institute for Systems and Computer Engineering Technology and Science Porto Portugal

ISBN: (纸本)9781665415880

Two distinct optical fibers for endoscope-based configurations are demonstrated and studied in this work. The fibers used for the experiment consist of: a conventional singlemode fiber (SMF 28e) and a hollow core photonic crystal fiber (HC-PCF) based on silica. Two studies that allowed the characterization of these fibers, according to their optical output power and when subjected to curvature, were carried out. The intensity power profile was also analysed in relation to the propagation distance, transversal displacement and incidence angle. After this study it can be concluded that the most suitable solution for the endoscope is the HC-PCF fiber working as a transmission probe. For the proof of concept of the fiber-based endoscope, a cleaved multimode fiber (MMF) tip was used as a reception probe and its reflection efficiency was also analysed. © 2021 IEEE.

关键词： Endoscopy

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Building Flexibility Bidding Curves for Energy Communities

Building Flexibility Bidding Curves for Energy Communities

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International Conference on European Electricity Market, EEM

作者： Luís Rodrigues João Mello Kamalanathan Ganesan Ricardo Silva José Villar INESC TEC - Institute for Systems and Computer Engineering Technology and Science Faculdade de Engenharia da Universidade do Porto R&D Nester Portugal

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

The integration of renewable generation requires new sources of flexibility, including the flexibility from distributed resources that can be unlocked via local flexibility markets (LFMs). In these markets, aggregators (AGGs) offer the flexibility from their portfolios to the flexibility requesting parties (FRP), i.e. system operators or other balancing requesting parties. To bid in LFMs and manage market uncertainty, AGGs must compute the flexibility they are willing to offer at each possible flexibility market price, by optimizing their portfolios. This paper proposes a 2-stage methodology to compute the flexibility bidding curve that an energy community can send to a LFM when behaving as an AGG of its members resources. At stage 1, the energy community (EC) manager computes the optimal EC operation without flexibility provision, minimizing the EC energy bill, and serving as the baseline to verify the flexibility provision. Then, at stage 2, for each possible flexibility price, the EC manager computes the optimal flexibility to be offered, minimizing the EC energy bill but including the flexibility provision incomes, to build the flexibility bidding curve.

关键词： Renewable energy sources Uncertainty Optimization models Europe Pricing Electric vehicles Regulation

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Enhancing Mobile Robot Navigation: A Graph Decomposition Submodule for TEA*

Enhancing Mobile Robot Navigation: A Graph Decomposition Sub...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Filipe Cardoso Diogo Miguel Matos Marina Brilhante Pedro Costat Héber Sobreira Carlos Silva CRIIS - Centre of Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Faculty of Engineering University of Porto Porto Portugal Flowbotic Mobile Systems SA Mangualde Portugal

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

Rising industrial complexity demands efficient mobile robots to drive automation and productivity. Effective navigation relies on perception, localization, mapping, path planning, and motion control, with path planning being key. The Time Enhanced A * (TEA *) algorithm extends A * by adding time as a dimension to resolve temporal conflicts in multi-robot coordination. However, inconsistencies in edge lengths within the graph can hinder optimal path calculation. To address this, a Graph Decomposition submodule was developed to standardize edge lengths and temporal costs. Integrated into a ROS-based fleet coordination system, this approach significantly reduces execution time and improves coordination capacity.

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