Scheduling maintenance activities of electric power transmission networks using an hybrid constraint method

In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

Energy resource management in smart grids considering an Intensive use of electric vehicles

The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.

Support System for Rational Use of Electric Energy

This paper presents the system developed to promote the rational use of electric energy among consumers and, thus, increase the energy efficiency. The goal is to provide energy consumers with an application that displays the energy consumption/production profiles, sets up consuming ceilings, defines automatic alerts and alarms, compares anonymously consumers with identical energy usage profiles by region and predicts, in the case of non-residential installations, the expected consumption/production values. The resulting distributed system is organized in two main blocks: front-end and back-end. The front-end includes user interface applications for Android mobile devices and Web browsers. The back-end provides data storage and processing functionalities and is installed in a cloud computing platform - the Google App Engine - which provides a standard Web service interface. This option ensures interoperability, scalability and robustness to the system.

RemoteLabs Platform

This paper reports on a first step towards the implementation of a framework for remote experimentation of electric machines ? the RemoteLabs platform. This project was focused on the development of two main modules: the user Web-based and the electric machines interfaces. The Web application provides the user with a front-end and interacts with the back-end ? the user and experiment persistent data. The electric machines interface is implemented as a distributed client server application where the clients, launched by the Web application, interact with the server modules located in platforms physically connected the electric machines drives. Users can register and authenticate, schedule, specify and run experiments and obtain results in the form of CSV, XML and PDF files. These functionalities were successfully tested with real data, but still without including the electric machines. This inclusion is part of another project scheduled to start soon.

A Hybrid Simulated Annealing approach to handle Energy Resource Management considering an intensive use of Electric Vehicles

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.

Energy Resource Management under the Influence of the Weekend Transition Considering an Intensive use of Electric Vehicles

Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with their owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps. The full AC power flow calculation included in the model takes into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33-bus distribution network and V2G is used to illustrate the good performance of the proposed method.

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

Electric vehicles in urban areas: test cases using a scenario simulator

Electric vehicles introduction will affect cities environment and urban mobility policies. Network system operators will have to consider the electric vehicles in planning and operation activities due to electric vehicles’ dependency on the electricity grid. The present paper presents test cases using an Electric Vehicle Scenario Simulator (EVeSSi) being developed by the authors. The test cases include two scenarios considering a 33 bus network with up to 2000 electric vehicles in the urban area. The scenarios consider a penetration of 10% of electric vehicles (200 of 2000), 30% (600) and 100% (2000). The first scenario will evaluate network impacts and the second scenario will evaluate CO2 emissions and fuel consumption.

Electric vehicle scenario simulator tool for smart grid operators

This paper presents a simulator for electric vehicles in the context of smart grids and distribution networks. It aims to support network operator´s planning and operations but can be used by other entities for related studies. The paper describes the parameters supported by the current version of the Electric Vehicle Scenario Simulator (EVeSSi) tool and its current algorithm. EVeSSi enables the definition of electric vehicles scenarios on distribution networks using a built-in movement engine. The scenarios created with EVeSSi can be used by external tools (e.g., power flow) for specific analysis, for instance grid impacts. Two scenarios are briefly presented for illustration of the simulator capabilities.

Oxidative Leaching of metals from electronic waste with solutions based on quaternary ammonium salts

The treatment of electric and electronic waste (WEEE) is a problem which receives ever more attention. An inadequate treatment results in harmful products ending up in the environment. This project intends to investigate the possibilities of an alternative route for recycling of metals from printed circuit boards (PCBs) obtained from rejected computers. The process is based on aqueous solutions composed of an etchant, either 0.2 M CuCl2.2H2O or 0.2 M FeCl3.6H2O, and a quaternary ammonium salt (quat) such as choline chloride or chlormequat. These solutions are reminiscent of deep eutectic solvents (DES) based on quats. DES are quite similar to ionic liquids (ILs) and are used as well as alternative solvents with a great diversity of physical properties, making them attractive for replacement of hazardous, volatile solvents (e.g. VOCs). A remarkable difference between genuine DES and ILs with the solutions used in this project is the addition of rather large quantities of water. It is shown the presence of water has a lot of advantages on the leaching of metals, while the properties typical for DES still remain. The oxidizing capacities of Cu(II) stem from the existence of a stable Cu(I) component in quat based DES and thus the leaching stems from the activity of the Cu(II)/Cu(I) redox couple. The advantage of Fe(III) in combination with DES is the fact that the Fe(III)/Fe(II) redox couple becomes reversible, which is not true in pure water. This opens perspectives for regeneration of the etching solution. In this project the leaching of copper was studied as a function of gradual increasing water content from 0 - 100w% with the same concentration of copper chloride or iron(III) chloride at room temperature and 80ºC. The solutions were also tested on real PCBs. At room temperature a maximum leaching effect for copper was obtained with 30w% choline chloride with 0.2 M CuCl2.2H2O. The leaching effect is still stronger at 80°C, b ut of course these solutions are more energy consuming. For aluminium, tin, zinc and lead, the leaching was faster at 80ºC. Iron and nickel dissolved easily at room temperature. The solutions were not able to dissolve gold, silver, rhodium and platinum.

On the robustness of the slotine-Li and the FPT/SVD-based adaptive controllers

A comparative study concerning the robustness of a novel, Fixed Point Transformations/Singular Value Decomposition (FPT/SVD)-based adaptive controller and the Slotine-Li (S&L) approach is given by numerical simulations using a three degree of freedom paradigm of typical Classical Mechanical systems, the cart + double pendulum. The effects of the imprecision of the available dynamical model, presence of dynamic friction at the axles of the drives, and the existence of external disturbance forces unknown and not modeled by the controller are considered. While the Slotine-Li approach tries to identify the parameters of the formally precise, available analytical model of the controlled system with the implicit assumption that the generalized forces are precisely known, the novel one makes do with a very rough, affine form and a formally more precise approximate model of that system, and uses temporal observations of its desired vs. realized responses. Furthermore, it does not assume the lack of unknown perturbations caused either by internal friction and/or external disturbances. Its another advantage is that it needs the execution of the SVD as a relatively time-consuming operation on a grid of a rough system-model only one time, before the commencement of the control cycle within which it works only with simple computations. The simulation examples exemplify the superiority of the FPT/SVD-based control that otherwise has the deficiency that it can get out of the region of its convergence. Therefore its design and use needs preliminary simulation investigations. However, the simulations also exemplify that its convergence can be guaranteed for various practical purposes.

Veículo ZEV (sem emissões)

A crescente dependência energética do Petr óleo e o impacto ambiental daí resultante, tanto como as excessivas autonomias e desempenho dos veículos perante as nossas necessidades, leva a que Portugal, a Europa, o Mundo, necessitem de apostar em inovar e alterar costumes, de forma a que o nosso planeta se mantenha sustentável e de maneira a aumentar a qualidade de vida de todos nós. As emissões proveniente dos veículos representam uma excessiva parcela na poluição atmosférica causada pela queima dos derivados do petróleo. Uma das soluções mais viáveis para a redução de emissões, passaria pela implementação de leis que fomentassem a compra dos veículos ZEV. Este trabalho pretende provar a inviabilidade do uso contínuo de combustíveis fósseis, destaca as principais características dos veículos eléctricos e os benefícios destes quando comparados com os veículos convencionais, descreve as características dos veículos eléctricos comercializados em Portugal e apresenta a sugestão, com base no estudo elaborado, de um veículo ZEV que se adapte às necessidades do cidadão europeu.

Real-Time Tariffs for Electric Vehicles in Wind Power based Power Systems

The use of Electric Vehicles (EVs) will change significantly the planning and management of power systems in a near future. This paper proposes a real-time tariff strategy for the charge process of the EVs. The main objective is to evaluate the influence of real-time tariffs in the EVs owners’ behaviour and also the impact in load diagram. The paper proposes the energy price variation according to the relation between wind generation and power consumption. The proposed strategy was tested in two different days in the Danish power system. January 31st and August 13th 2013 were selected because of the high quantities of wind generation. The main goal is to evaluate the changes in the EVs charging diagram with the energy price preventing wind curtailment.

Controlo da velocidade e posição de um tapete rolante

A utilização eficiente da energia é essencial para a competitividade económica de um país. Sendo a intensidade energética de Portugal elevada, onde a utilização de motores elétricos, absorve cerca de metade da energia elétrica consumida na indústria, a utilização de conversores eletrónicos de potência permite obter economias de energia. Nesta tese pretende-se controlar a velocidade e o posicionamento de um tapete rolante através da utilização de um conversor eletrónico de potência. Na fundamentação teórica são referidos os conceitos de variação da tensão e frequência, controle escalar e vetorial, modelação por largura de pulso (PWM) assim como a retificação e ondulação da tensão de um variador de velocidades. Na parte prática será utilizado um servo motor, controlado por um variador eletrónico de velocidades, para efetuar o referido projeto. É ainda objeto desta tese o estudo dos parâmetros fundamentais assim como a pesquisa dos parâmetros a utilizar para o desempenho pretendido.

Convergence of Smart Grid ICT architectures for the last mile

The evolution of the electrical grid into a smart grid, allowing user production, storage and exchange of energy, remote control of appliances, and in general optimizations over how the energy is managed and consumed, is also an evolution into a complex Information and Communication Technology (ICT) system. With the goal of promoting an integrated and interoperable smart grid, a number of organizations all over the world started uncoordinated standardization activities, which caused the emergence of a large number of incompatible architectures and standards. There are now new standardization activities which have the goal of organizing existing standards and produce best practices to choose the right approach(es) to be employed in specific smart grid designs. This paper follows the lead of NIST and ETSI/CEN/CENELEC approaches in trying to provide taxonomy of existing solutions; our contribution reviews and relates current ICT state-of-the-art, with the objective of forecasting future trends based on the orientation of current efforts and on relationships between them. The resulting taxonomy provides guidelines for further studies of the architectures, and highlights how the standards in the last mile of the smart grid are converging to common solutions to improve ICT infrastructure interoperability.