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Über dieses Buch

This book constitutes the refereed proceedings of the 10th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2019, held in Costa de Caparica, Portugal, in May 2019.

The 36 revised full papers presented were carefully reviewed and selected from 73 submissions. The papers present selected results produced in engineering doctoral programs and focus on technological innovation for industry and serivce systems. Research results and ongoing work are presented, illustrated and discussed in the following areas: collaborative systems, collaboration and resilient systems, decision and optimization systems, assistive systems, smart environments, smart manufacturing, water monitoring systems, communication systems, and energy systems.

Inhaltsverzeichnis

Frontmatter

Correction to: Integration of Renewable Energy in Markets: Analysis of Key European and American Electricity Markets

The original version of this chapter starting on p. 321 was revised. The year mentioned in the funding information was incorrect. The original chapter has been corrected.

Hugo Algarvio, Fernando Lopes, João Santana

Collaborative Systems

Frontmatter

A Model to Assess Collaboration Performance in a Collaborative Business Ecosystem

In a Collaborative Business Ecosystem, Performance Indicators are a useful mechanism to assess collaboration performance, inducing self-adjustment in organization’s profile, thereby improving the sustainability of the ecosystem. Using system dynamics and agent-based modelling, a simulation model is assembled to show organizations’ self-adjustment by improving their profile in response to an assessment through a chosen set of performance indicators, such as innovation indicator, contribution indicator and prestige indicator. The natural reaction of organizations (similar to individuals) towards improving their performance according to the way they are evaluated, is modelled considering different enterprise profiles categorized into various classes of responsiveness, to better simulate the diversity in a real collaborative business ecosystem. Preliminary results of this approach are presented and discussed.

Paula Graça, Luís M. Camarinha-Matos, Filipa Ferrada

Organizational Structure for Mass Collaboration and Learning

The rapid emergence of collaborative communities supported by Internet has led to unprecedented waves of novelty in the ways people create and share knowledge. In this framework, the notion of mass collaboration has opened new windows of opportunity for collective learning. Mass collaborative learning is a new paradigm, through which large numbers of people engage in collaborative initiatives to learn from each other and alter the nature of formal education. Even though mass collaboration opens up an apparently limitless field for promoting social inclusion in effective learning, not all aspects, features, and characteristics of this phenomenon such as the organizational structures are quite clear at present. Therefore, this study is conducted to review the organizational structures of 14 real examples of mass collaboration. Through the analysis of the most suitable features of those structures we expect to be able to propose a general organizational structure for mass collaborative learning purpose. It is expected that such organizational structure could help developing a better insight into this field of study.

Majid Zamiri, Luis M. Camarinha-Matos

Emerging Community Energy Ecosystems: Analysis of Organizational and Governance Structures of Selected Representative Cases

The quest to decarbonize and decentralize the current power grid has enabled high penetration of Distributed Energy Resources at the edge of the distribution network. The diversity, complexity and growing numbers of these energy resources currently pose a challenge to managing them. This has resulted in the emergence of various energy ecosystems which use diverse community-based organizational strategies and initiatives as forms of management techniques. There are also corresponding business models and governance structures that are innovative and technologically disruptive to the operations of the current grid. An analysis of five representative cases of these Renewable Energy Communities is performed using real-life projects as case studies. The focus areas considered in this study included organizational and governance structures, roles, and the relationship between key stakeholders/owners, how these ecosystems interact with the power grid, and the role of collaborations. The outcome of the study revealed that each category of ecosystem has similar organizational and governance structures although they may differently be constituted. In terms of ownership, energy cooperative, municipalities, and communities were found to own a greater share of these energy resources. Furthermore, most of these ecosystems were found to interact with the grid by supplying excess energy from the community to the power grid whilst others operate in isolation from the grid. Apart from one case, all the others showed elements of collaborations as an integral component of their mode of operations.

Kankam O. Adu-Kankam, Luis M. Camarinha-Matos

Collaboration and Resilient Systems

Frontmatter

Novel Approaches to Handle Disruptions in Business Ecosystems

Today’s business world is continuously challenged by unexpected disruptive events, which are increasing in their frequency and effects. As a consequence, it is plausible to foresee future scenarios in which turbulence and instability are no longer considered as episodic crises, but rather somewhat the “norm” or the default status. This trend naturally raises the question of how organizations can strive and even gain in such disruptive environments, and which characteristics are required for combating disruptions. Resilience and antifragility are two emerging approaches to handle disruptions. Through a literature review, this paper identifies several strategies that contribute to business ecosystem’s resilience or antifragility. Furthermore, it is also shown that contributions from a number of disciplinary areas, including Collaborative Networks, Systems Thinking, Thermodynamics, Management science, and ICT, can provide complementary views and support. A set of promising examples of applications of the discussed approaches are presented and briefly analyzed. Finally, a number of open questions and directions for further research are presented.

Javaneh Ramezani, Luis M. Camarinha-Matos

Proposing a Risk Management Model in Construction of Combined-Cycle Power Plant Projects

Companies are increasingly focusing on identifying risks and managing them even before they affect project executing. Risk management can play a key part in identifying problems and taking preventive measures in this regard. This research focused on risk management in the implementation of a combined cycle power plant project. This paper aims at exploring the role of risks and risk management practices in construction of this type of projects by considering how they can impact the project’s time, quality, and cost. First, the project risk types were identified. The extent to which the project’s objectives were achieved was then considered on the basis of three criteria: time, cost, and quality. Next, the risks were categorized and prioritized through a risk breakdown structure. The obtained results revealed the most influential risks in the project. Finally, the proposed risk management model was used in the project which led to strengthening the performance impact of risk management practices in the risky project environment.

Shakib Zohrehvandi, Alexandra Tenera

voteChain: Community Based Scalable Internet Voting Framework

Most democratic countries still use the traditional systems of paper ballots and voting boxes. As technology develops, new electronic voting systems have been proposed to modernize and facilitate the voting process. Most e-voting systems are based on centralizing models, i.e. client-server structures, which have been proved to be unreliable and prone to be affected by the same problems of any centralized computer system: Denial of Service attacks, server hacking, etc. The advent of cryptocurrencies in recent years has shed light on their underlying technology – blockchain – as a powerful decentralizing technological paradigm that keeps finding new areas of application outside this implementation, such as electronic voting. In this paper, we present a proposal for a voting framework based on blockchain technology and analyze its potential to improve current voting systems as well as the implementation drawbacks.

Ricardo L. Almeida, Laura Ricci, Luis M. Camarinha-Matos

Decision Systems

Frontmatter

UAV Downwash-Based Terrain Classification Using Wiener-Khinchin and EMD Filters

Knowing how to identify terrain types is especially important in the autonomous navigation, mapping, decision making and detect landings areas. A recent area is in cooperation and improvement of autonomous behavior between robots. For example, an unmanned aerial vehicle (UAV) is used to identify a possible landing area or used in cooperation with other robots to navigate in unknown terrains. This paper presents a computer vision algorithm capable of identifying the terrain type where the UAV is flying, using its rotors’ downwash effect. The algorithm is a fusion between the frequency Wiener-Khinchin adapted and spatial Empirical Mode Decomposition (EMD) domains. In order to increase certainty in terrain identification, machine learning is also used. The system is validated using videos acquired onboard of a UAV with an RGB camera.

João P. Matos-Carvalho, André Mora, Raúl T. Rato, Ricardo Mendonça, José M. Fonseca

A Markov Process-Based Approach for Reliability Evaluation of the Propulsion System in Multi-rotor Drones

Autonomous multirotor drones as a popular type of Unmanned Aerial Vehicles (UAVs) have a tremendous potential to facilitate activities such as logistics, emergency response, recording video, capturing special events, and traffic management. Despite the potential benefits the possibility of harming people during operation should be considered. This paper focuses on modeling the multirotor drones’ propulsion system with Markov chains. Using the proposed model, both reliability and Mean Time To Failure (MTTF) of the propulsion system are evaluated. This study proposes a fault detection and recovery system based on a Markov Model for mission control of multirotor drones. Concretely, the proposed system aims to reduce potential injuries by increasing safety.

Koorosh Aslansefat, Francisco Marques, Ricardo Mendonça, José Barata

A New Approach for Crop Rotation Problem in Farming 4.0

Technology and innovations have long improved farming over the world and, as Industry 4.0 quickly spread, farmers have embraced high-level automation and data exchange, driving a transformation called Farming 4.0. Consequently, precise and even real-time field information have become easily accessible. Though, analyzing all this information requires great skills and tools, like mathematical knowledge and powerful computational algorithms to reach farmers expectations. This research explores the Crop Rotation Problem (CRP) and its relevance for the integration of Precision Agriculture (PA) and farm management. This paper presents a new mathematical approach for the CRP based on the nutrient balance and crop requirements, increasing the sustainable appealing of the problem. A real-encoded genetic algorithm (GA) was developed for optimization of the CRP. The results indicate good performance in mid and long-term crop scheduling.

Bruno S. Miranda, Akebo Yamakami, Priscila C. B. Rampazzo

Optimization Systems

Frontmatter

Application of Monte Carlo Methods in Probability-Based Dynamic Line Rating Models

Due to the growing demand for electrical energy, the use of alternative transfer capacity-enhancing methods such as Dynamic Line Rating (DLR) become more and more significant. However, there are some challenges regarding the prediction of the DLR value, which are still unresolved. In the last few years several DLR pilot projects have been constituted resulting a big database of the measured environmental and load parameters. One aim of this article is to introduce how different Monte Carlo methods could be applied in probability-based DLR models to predict the DLR value and the operational safety risk factor. Based on simulations, it is possible to implement a smart DLR system in the future, which will be able to set the model parameters from time to time using big data. In order to demonstrate the advantages, relevance and limitations of the Monte Carlo simulations, a case study is presented for a genuine transmission line.

Levente Rácz, Dávid Szabó, Gábor Göcsei, Bálint Németh

Theory of Constraints Thinking Processes on Operational Lean Programs Management Improvement: An Energy Producer Company Case

Several theories and associated models are arising in the field of systems’ continuous improvement, focused on structured solutions to face the internal or external factors that affect them. Within these theories stands out Theory of Constraints (TOC), proposed to manage the most relevant constraints that exist within an organization. In this case study, the TOC Thinking Processes approach will be applied to the Management of Operational Lean Programs, on a pilot investigation at the organization were the Case Study took place. This application aims to analyze their Lean Program’s Management in order to find the constraint that inhibits the system to reach its best level of performance, in order to support the development of robust improvement solutions that can solve the identified restrictions and sustain the proposed changes over time reaching a process of ongoing improvement.

Margarida Gaspar, Luis Cristovão, Alexandra Tenera

Dynamic Search Tree Growth Algorithm for Global Optimization

This paper presents dynamic version of the tree growth algorithm. Tree growth algorithm is a novel optimization approach that belongs to the group of swarm intelligence metaheuristics. Only few papers addressed this method so far. This algorithm simulates the competition between the trees for resources such as food and light. The dynamic version of the tree growth algorithm introduces dynamical adjustment of exploitation and exploration search parameters. The efficiency and robustness of the proposed method were tested on a well-known set of standard global unconstrained benchmarks. Besides numerical results obtained by dynamic tree growth algorithm, in the experimental part of this paper, we have also shown comparative analysis with the original tree growth algorithm, as well as comparison with other methods, which were tested on the same benchmark set. Since many problems from the domains of industrial and service systems can be modeled as global optimization tasks, dynamic tree growth algorithm shows great potential in this area and can be further adapted for tackling many real-world unconstrained and constrained optimization challenges.

Ivana Strumberger, Eva Tuba, Miodrag Zivkovic, Nebojsa Bacanin, Marko Beko, Milan Tuba

Assistive Systems

Frontmatter

Intelligent HCI Device for Assistive Technology

This paper presents a new intelligent Human-Computer Interaction (HCI) device for Assistive Technology. The developed device can be used as a mouse or as a gamepad, moving a part of the human body, typically the head, for hands-free computer access tasks. The state-of-the-art hardware uses an Advanced RISC Machine 32-bit microcontroller and a microelectromechanical 9-degree motion sensor, including a System-in-Package (SiP) accelerometer, gyroscope and magnetometer. The hardware/software device with a human-in-the-loop controller can be identified as a Cyber-Physical intelligent system to be incorporated in the “Industry 4.0” trend. Results reveal that the embedded controller of the HID device allows the improvement of the user’s performance, decreasing the effort and the execution time of the hands-free computer tasks.

Rui Azevedo Antunes, Luís Brito Palma, Hermínio Duarte-Ramos, Paulo Gil

Real-Time Human Body Pose Estimation for In-Car Depth Images

Over the next years, the number of autonomous vehicles is expected to increase. This new paradigm will change the role of the driver inside the car, and so, for safety purposes, the continuous monitoring of the driver/passengers becomes essential. This monitoring can be achieved by detecting the human body pose inside the car to understand the driver/passenger’s activity. In this paper, a method to accurately detect the human body pose on depth images acquired inside a car with a time-of-flight camera is proposed. The method consists in a deep learning strategy where the architecture of the convolutional neural network used is composed by three branches: the first branch is used to estimate the confidence maps for each joint position, the second one to associate different body parts, and the third branch to detect the presence of each joint in the image. The proposed framework was trained and tested in 8820 and 1650 depth images, respectively. The method showed to be accurate, achieving an average distance error between the detected joints and the ground truth of 7.6 pixels and an average accuracy, precision, and recall of 95.6%, 96.0%, and 97.8% respectively. Overall, these results demonstrate the robustness of the method and its potential for in-car body pose monitoring purposes.

Helena R. Torres, Bruno Oliveira, Jaime Fonseca, Sandro Queirós, João Borges, Nélson Rodrigues, Victor Coelho, Johannes Pallauf, José Brito, José Mendes

Treatment of Ventricular Assist Device Test Bench Data for Prediction of Failures and Improved Intrinsic Reliability

This article regards over analytics of reliability of ventricular assist devices (VAD) used as therapy for advanced heart failure conditions in the face of malfunction related adverse events. This question directs research and the search for a solution proposal, even if prospective, but that promotes the longevity of these devices, increasing the intrinsic reliability. An “In Vitro” test bench is used to obtain variations of dynamic behavior over time; by means of a set of variables and the deviations (failures) compared between the standard and tested devices; since these devices are systems that vary in time. An intelligent systematics obtained through the automation of the test bench, using sensors and actuators to control the independent variables, and the data collection and analysis using the technologies present in the industry 4.0 completes the increase of the reliability of the VAD.

Jeferson C. Dias, Jônatas C. Dias, Edinei Legaspe, Rodrigo Lima Stoeterau, Fabrício Junqueira, Newton Maruyama, Lucas Antônio Moscato, Paulo E. Miyagi, Diolino J. Santos Filho

Smart Environments

Frontmatter

Basis for an Approach to Design Collaborative Cyber-Physical Systems

Nowadays Cyber-Physical Systems gain more and more attention in regard to the Industry 4.0 or Digital Transformation in general. These systems imply the tight integration of physical and software components and are becoming more complex, forming highly inter-connected systems-of-systems. Furthermore, as components and subsystems are becoming more intelligent, there is a need for a paradigm shift towards considering them as ecosystems of collaborative entities with growing levels of autonomy. There is, however, the lack of proper methodologies and support frameworks for the design of such systems. In this context a contribution to an approach for the development of Collaborative Cyber-Physical Systems is proposed. It introduces some core definitions, organizational and architectural aspects. The proposed approach is in line with the design science research methodology and is illustrated with some examples.

Artem A. Nazarenko, Luis M. Camarinha-Matos

A Group Evacuation Method for Smart Buildings

Mass evacuation of people in buildings during emergencies is still a burning question regarding safety and reliability. Due to lack of information, crowd prefers to evacuate in the form of random groups. This random grouping increases the possibility of panic among evacuees due to human behavioral factors like herding and stampeding. As a result, congestion may occur resulting in unnecessary casualties. For this purpose, we propose a multi-agent evacuation architecture, that not only collects all the information from evacuees and events occurring in the building on a real-time basis but also provides the evacuation routes to evacuees. In this paper, we discuss a group formation module of our proposed architecture and use an example as a test case to check the functionality of our proposed group formation approach.

Qasim Khalid, Alberto Fernández, Marin Lujak, Arnaud Doniec

Optimized Electrification of Subsea Oil & Gas Infrastructures Based in Genetic Algorithm

Offshore field development relies on multiple optimization techniques targeting a feasible and cost-effective production solution yet are focused on the field itself. While so, advancements in offshore engineering bring increasingly complex subsea infrastructures to depths in the excess of 3,500 m. Many offshore production topsides which currently rely on costly and harmful onboard thermal-based power generation are turning to high voltage power-from-shore electrification solutions to cope with the challenges being brought by subsea infrastructures. An optimal electrification of these subsea templates is a challenge on its own as the seafloor morphology and well distribution is far from consistent. This paper presents a combined k-means and genetic-algorithm optimization to assess how the combined deployment of high voltage umbilical, wellheads and subsea substations can be optimized for the lowest cost possible. Results show a significant improvement in optimization of the total umbilical length as well as the substation positioning on the seabed.

Tiago A. Antunes, Rui Castro, P. J. Santos, A. J. Pires, Matthias Foehr

Smart Manufacturing

Frontmatter

Production Scheduling Requirements to Smart Manufacturing

The production scheduling has attracted a lot of researchers for many years, however most of the approaches are not targeted to deal with real manufacturing environments, and those that are, are very particular for the case study. It is crucial to consider important features related with the factories, such as products and machines characteristics and unexpected disturbances, but also information such as when the parts arrive to the factory and when should be delivered. So, the purpose of this paper is to identify some important characteristics that have been considered independently in a lot of studies and that should be considered together to develop a generic scheduling framework to be used in a real manufacturing environment.

Duarte Alemão, André Dionísio Rocha, José Barata

Open Modular Components in the Industry Using vf-OS Components

The increasing complexity in industrial and information technology in the last decades forced the manufacturing process to adapt to these new evolution trends. Factories are using the advancement of the Internet of Things (IoT) to have multiple platforms with sensorial information into their factory processes, to improve and reduce the costs of their products and increase their profit. To address these complexes and useful computations, the vf-OS (Virtual Open Operating System) aims to facilitate the development of applications using their individual components as well as FIWARE enablers.

Joao Giao, Joao Sarraipa, Ricardo Jardim-Gonçalves

Big Data on Machine to Machine Integration’s Requirement Analysis Within Industry 4.0

One of the foundations for Industry 4.0 is the integration of various industrial elements (i.e. sensors, machines, and services) so that these devices can decide in a relatively autonomous way the level of integration which will be adopted. Thus, it is important to understand how the communication Machine to Machine is effectively realized and how these data can be explored and used to enhance the manufacturing process. The exchange of information between machines in the industrial process represents a potential to acquire and analyze a mass of data characterized as “big data”, which can be perceived as an opportunity to discuss the paradigms of the industrial systems. Therefore, the purpose of this research is to identify the requirements for the Machine to Machine communication and the use of this data/information for more complexes analyzes using big data and analytics techniques. The KAOS methodology was utilized to model these requirements.

Felipe A. Coda, Rafael M. Salles, Henrique A. Vitoi, Marcosiris A. O. Pessoa, Lucas A. Moscato, Diolino J. Santos Filho, Fabrício Junqueira, Paulo E. Miyagi

Water Monitoring Systems

Frontmatter

Artificial Neural Networks Application to Support Plant Operation in the Wastewater Industry

This communication presents the main aim, contextual and development framework of the PhD that is being conducted by the first author. In this PhD, main aim is the application of data driven methods to industrial processes in order to improve and support industrial operations. In this case, Wastewater Treatment Plants (WWTPs) are adopted as the industry where data driven methods will be applied. WWTPs are industries devoted to managing and process residual water coming from urban and industrial areas. Those type of industries apply highly-complex and nonlinear processes to reduce the contamination of water. Therefore, among the different data driven methods, in this PhD we will focus on the application of Artificial Neural Networks (ANNs) in order to improve and support the operations performed in this type of industries. ANNs are considered due to their ability in the modeling of highly-complex and nonlinear processes such as the WWTPs processes.

Ivan Pisa, Ramon Vilanova, Ignacio Santín, Jose Lopez Vicario, Antoni Morell

Towards a Practical and Cost-Effective Water Monitoring System

In recent years, there has been increasing awareness of the preservation, protection and sustainable use of natural resources. Water resources, being one of the most important, face major threats due to contamination by pollutants of various types and origins. Maintaining the quality of water resources requires more robust, reliable and more frequent monitoring than traditional data collection techniques based on manual sampling methods. This article, which is the result of ongoing research, proposes a practical and cost-effective solution for a surface water monitoring system, using a robotics platform and cloud services. The proposed solution allows for scalability and will accommodate a wide range of end-user specifications. To allow for continuous operation in longer activities, the design of a versatile real-time water quality monitoring system should also take into consideration the question of its energy requirements and self-sufficiency.

João Marques, Brígida Lopes, Carlos Ferreira, Henrique Pinho, Manuel Barros, Pedro Granchinho, Pedro Neves

Smart Cities: Non Destructive Approach for Water Leakage Detection

Natural resources management is essential, especially of water distribution within cities. In Brazil, water losses in distribution systems go up to around 38%. In the context of “Smart Cities”, technologies that use “The Internet of Things” can be applied to reduce such losses. The present article shows that leakages produce distinctive noise ranging from 100 Hz to 1000 Hz. Through digital signal processing techniques, such as the Discrete Fourier Transform and Goertzel Transform, the spectral signals are decomposed, revealing their components of frequency such as the intensity. An architecture that performs the communication between slave nodes through a TCP/IP network is then proposed. The slave nodes are responsible for data collection for leakage identification. The collected data is then sent to the data master where there is greater computing power. The data master will perform the processing according to the paradigm of edge computing, thus obtaining frequency responses and the identification of the leakage itself. It will also make data available through OPC-UA, a standard “Internet of Things” communication protocol widely used in the industrial context.

Lucas Nunes Monteiro, Felipe Crispim da Rocha Salvagnini, Edinei Peres Legaspe, Sidney José Montebeller, Andréa Lucia Braga Vieira Rodrigues, Fernando Garcia Deluno, Diolino J. Santos Filho

Communication Systems

Frontmatter

Energy Efficient Massive MIMO Point-to-Point Communications with Physical Layer Security: BPSK vs QPSK Decomposition

Massive multiple-input multiple-output systems (mMIMO) are the most prevalent candidates for the next generation of wireless communication. Yet even with mMIMO systems the joint optimization of spectral and energy efficiencies can be only attained by combining high order signal constellations and efficient power amplification. In order to push this limitation, the transmitter can spread the information into several amplification branches, which are the result of the decomposition of multilevel constellation symbols into quasi constant envelope signals. Nevertheless, the high number of antennas involved in this type of communication leads to an increase of the channel matrix’s size and therefore the complexity of the equalization process can create drawbacks for the power consumption and latency. In this paper we will study the combination of a multi-layer transmitter with a low complexity receivers based on an iterative block decision feedback equalizer (IB-DFE). These receivers avoid the matrix inversion operation in the equalizer the feed-forward by replacing it with an equal gain combiner (EGC) or a maximum ratio combiner (MRC) module. Results show that can be used without penalties on performance provided that the number of antennas involved is high.

David Borges, Paulo Montezuma, Rui Dinis, Pedro Viegas

V-GRADIENT: A Density-Aware Geocast Routing Protocol for Vehicular Delay-Tolerant Networks

Vehicular Delay-Tolerant Networks (VDTNs) are networks of vehicles that communicate wirelessly, where there are no permanent end-to-end connections. VDTNs have a highly variable topology, with frequent partitions, and possibly low node density. Thus, delay-tolerant routing adopts a store-carry-and-forward message transfer paradigm, where messages have a useful Time To Live (TTL) and are stored until a good contact opportunity arises. Multiple message replicas can be generated to improve delivery probability at the cost of increasing network congestion. In this paper, we propose the V-GRADIENT geocast routing protocol that monitors node density and buffer occupancy, to adapt dynamically the forwarding techniques used to disseminate messages within the geographic region of interest. Simulation results show that V-GRADIENT is capable of controlling network congestion and efficiently deliver messages resulting in better delivery ratios (13–99%) and lower latencies when compared with existing protocols.

Henrique Nascimento, Paulo Rogério Pereira

Simulation of an Early Warning Fire System

In this paper, we will be using separate software tools (wireless network and Finite Differences Time Domain based simulators) to simulate the implementation of a wireless sensor network model based on low-rate/power transmission technology. The system operates in an unlicensed frequency range and the sensing nodes rely on surface plasmon resonance phenomenon for the detection of combustion by-products. More specifically, our simulations contemplate a system for early detection of fire in densely forested areas, which will then issue a warning in an automated way. As late detection of these events usually leads to severe flora, terrain, wild life and societal impact, an early warning system will provide better event assessment conditions, thus enabling efficient resources allocation, adequate response and would certainly be a promising improvement in minimizing such disruptive impairments.

Paulo Lourenço, Alessandro Fantoni, Manuela Vieira

Energy Markets

Frontmatter

Integration of Renewable Energy in Markets: Analysis of Key European and American Electricity Markets

Electricity markets are systems for affecting the purchase and sale of energy. Most existing markets are built on well-established principles of competition and transparency. However, their designs are based on centralized power plants with a small participation of end-use customers. During the past years, the share of electricity produced by renewable sources increased significantly. This paper analyses the structure and operation of two European markets and two American markets. The analysis highlights that the design, rules and characteristics of most markets are still not completely adapted to power systems with high levels of variable renewable energy. Accordingly, the paper proposes some recommendations to foster the integration of renewable generation.

Hugo Algarvio, Fernando Lopes, João Santana

A New Approach to Provide Sustainable Solutions for Residential Sector

An energy-efficient appliance normally presents a lower energy consumption compared to a less efficient one, with a higher initial investment, although this not always happens. Additionally, each appliance, presents very different features, leading to some difficulties on its choice by the consumer (decision-agent).On the other hand, each consumer, has specific and distinguished needs from other consumers, namely of social, economic or environmental nature. Even by adopting these criteria, this is not an isolated guarantee of an optimal solution for the consumer. It is then necessary to complement this approach with multicriteria, combined with optimization techniques. Evolutionary Algorithms (EA), could be used as an optimization technique, to provide sustainable solutions to the consumer, from the market. In this paper, it’s presented an approach that integrates both concepts, where at the end, it shall be presented a case study, to demonstrate the application of the proposed method.

Ricardo Santos, João C. O. Matias, Antonio Abreu

Electric Vehicles Aggregation in Market Environment: A Stochastic Grid-to-Vehicle and Vehicle-to-Grid Management

This paper addresses a development of a support management system for a power system aggregator managing a fleet of electric vehicles and bidding in a day-ahead electricity market. The support management system is modeled by stochastic mixed integer linear programming approach. The charge and discharge of the batteries of the fleet of vehicles are brought about to a convenient contribution for the maximization of the expected profit of the aggregator. The optimization takes into consideration the profiles of usage of the vehicle owners and the battery degradation of the vehicles. The vehicles are assumed as bidirectional energy flow units: allowing grid-to-vehicle or vehicle-to-grid operation modes. A strong interaction of information exchange is assumed between the aggregator and vehicle owners. A set of scenarios is created by a scenario generation method based on the Kernel Density Estimation technique and are subjected to a reduction by a K-means clustering technique. A case study with data of Electricity Market of Iberian Peninsula is presented to drive conclusion about the support management system developed.

Isaias L. R. Gomes, Rui Melicio, Victor M. F. Mendes

Energy Control

Frontmatter

Integrated System for Traction and Battery Charging of Electric Vehicles with Universal Interface to the Power Grid

This paper proposes an integrated system for traction and battery charging of electric vehicles (EVs) with universal interface to the power grid. In the proposed system, the power electronics converters comprising the traction drive system are also used for the battery charging system, reducing the required hardware, meaning the integrated characteristic of the system. Besides, this interface is universal, since it can be performed with the three main types of power grids, namely: (1) Single-phase AC power grids; (2) Three-phase AC power grids; (3) DC power grids. In these three types of interfaces with the power grid, as well as in the traction drive operation mode, bidirectional operation is possible, framing the integration of this system into an EV in the context of smart grids. Moreover, the proposed system endows an EV with an on-board fast battery charger, whose operation allows either fast or slow battery charging. The main contributes of the proposed system are detailed in the paper, and simulation results are presented in order to attain the feasibility of the proposed system.

Tiago J. C. Sousa, Vítor Monteiro, João L. Afonso

Auxiliary Digital Control Unit for Capacitor Banks

This paper addresses the conception of a prototype based in an implementation of a microcontroller proposed as an alternative solution to programmable logic controllers for controlling a capacitor bank. The control considered is in accordance with the Portuguese Energy Services Regulatory Authority. The prototype uses information concerned with the date and time for the accomplishment of industrial schedules. The equipment for the prototype is implemented on a printed circuit board designed and tested for industrial application and is in accordance to current standards for harmonic disturbances.

Patrícia Nunes, Mafalda Seixas, Rui Melicio, Victor M. F. Mendes

Modeling and Simulation of PV Panel Under Different Internal and Environmental Conditions with Non-constant Load

This paper focuses on PV power conversion under different internal and environmental conditions with non-constant load, connected to a smart grid system. Due to environmental conditions, the PV system is a non-linear system and difficult to predict the power conversion. In the aspect of internal variables, it includes the five parameters of the single diode solar cell model identify their sensitivity through error function. It also identifies the relation between environmental conditions, mainly: irradiance, temperature and wind speed. The modeling and computational simulation with laboratory work identify the effects of internal and environmental effect on the system. The model gives details about the sensitivity of each environmental condition using error function. The work includes the decrease of energy conversion by the solar panel as a function of time due to the shadow effect that affects its performance. Besides these, a smart system is introduced as a DAQ system in laboratory environment to get in real time the power conversion value with the P-V and I-V characteristics of the PV panel.

Masud R. Rashel, Rui Melicio, Mouhaydine Tlemcani, Teresa Goncalves

Power Systems

Frontmatter

Effect of Combined Stresses on the Electrical Properties of Low Voltage Nuclear Power Plant Cables

Energy is the heart of any industry since each industry uses energy. One of the most critical sources for energy generation is the nuclear power plants. The plants building needs a lot of investments and a pivotal role from the financial services sector in providing the necessary finance for the capital works. Control, instrumentation and low voltage power cables have a vital role in the operation, reliability and lifetime of these plants. The performance of these cables has an effect on the energy industry and the industries which use this kind of energy source. During operation, these cables are subjected to different stresses such as thermal, environmental, electrical and mechanical stresses so, condition monitoring of these cables is a must. This paper discusses a combined aging mechanisms effect on the electrical parameters of these cables. The assessment was done by monitoring the capacitance and the loss factor of the cables.

Ramy S. A. Afia, Tamus Zoltán Ádám, Ehtasham Mustafa

Thermal Degradation and Condition Monitoring of Low Voltage Power Cables in Nuclear Power Industry

A strong electric power industry having diverse generation sources is a key for advances in the industry, agriculture, technology and standards of living for any nation. In the last few decades, the nuclear power industry has emerged as a strong competitor in the electric power production market due to its less carbon oxide emission, high capacity, and efficiency. The reliable operation of nuclear power plants is heavily dependent on the safe operation of the low voltage instrumentation and control and power cables, which are mostly installed in the containment area and are under thermal and radiation stresses which may decrease the expected life of the cable. In this research work, the behavior of Choloro-Sulfonated Polyethylene/Cross-Linked Polyethylene based low voltage nuclear power plant power cable samples under thermal stress have been studied with the help of non-destructive extended voltage response method. The effect of the thermal stress on the expected life of the cable are also discussed.

Ehtasham Mustafa, Tamus Zoltán Ádám, Ramy S. A. Afia, Angel Asipuela

Novel Design of the Converter for an Active UPS Application Based on Marx Modulator Concept with Supercapacitors

A new Marx modulator 4-leg multilevel converter is proposed to replace the well-known 4-leg inverter fed from batteries in Uninterruptible Power Supply (UPS) applications. The novel design concept for the Marx modulator based multilevel converter is presented and described. Each leg uses 2 Marx modulator modules, each one using an Electrochemical Double-Layer Capacitor (EDLC) (also known as supercapacitor (SC)) energy storage bank. The new topology concept enables multilevel operation with five voltage level per phase, allowing high quality voltage and current waveforms, distributed supercapacitor storage and reduction of supercapacitor bank voltage. The proposed converter can operate as UPS or as Active Power Filter (APF), powering non-linear or/and unbalanced loads, while balancing each leg supercapacitor voltage. A control strategy to choose the redundant vector configuration to balance the supercapacitor voltages is explained. Simulation results are presented for a Marx modulator based interactive 40 kVA UPS.

Celso Pestana, Hiren Canacsinh, Miguel Chaves, Paulo Gamboa, Armando Cordeiro, Ricardo Luís, Ana Martins, Luís Encarnação, Fernando Pereira, José F. Silva, Nuno Santos

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