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.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Realistic Traffic Scenarios Using a Census Methodology: Vila Real Case Study

This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case study of a Portuguese city, Vila Real, is assessed. For this area the road network was created along with a synthetic population and public transport. The traffic results were obtained and an electric buses fleet was evaluated assuming that the actual fleet would be replaced in a near future. The energy requirements to charge the electric fleet overnight were estimated in order to evaluate the impacts that it would cause in the local electricity network.

Strategic bidding in electricity markets: an agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

MASCEM - an electricity market simulator providing coalition support for virtual power players

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimization techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper details some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study based on real data.

An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

Organisational adaptation of multi-agent systems in a peer-to-peer scenario

Organisations in Multi-Agent Systems (MAS) have proven to be successful in regulating agent societies. Nevertheless, changes in agents' behaviour or in the dynamics of the environment may lead to a poor fulfilment of the system's purposes, and so the entire organisation needs to be adapted. In this paper we focus on endowing the organisation with adaptation capabilities, instead of expecting agents to be capable of adapting the organisation by themselves. We regard this organisational adaptation as an assisting service provided by what we call the Assistance Layer. Our generic Two Level Assisted MAS Architecture (2-LAMA) incorporates such a layer. We empirically evaluate this approach by means of an agent-based simulator we have developed for the P2P sharing network domain. This simulator implements 2-LAMA architecture and supports the comparison between different adaptation methods, as well as, with the standard BitTorrent protocol. In particular, we present two alternatives to perform norm adaptation and one method to adapt agents'relationships. The results show improved performance and demonstrate that the cost of introducing an additional layer in charge of the system's adaptation is lower than its benefits.

Regret theory-based scenario building using an interacttive process

This paper is an introduction of the regret theory-based scenario building approach combining with a modified Delphi method that uses an interactive process to design and assess four different TDM measures (i.e., cordon toll, parking charge, increased bus frequency and decreased bus fare). The case study of Madrid is used to present the analysis and provide policy recommendations. The new scenario building approach incorporates expert judgement and transport models in an interactive process. It consists of a two-round modified Delphi survey, which was answeared by a group of Spanish transport experts who were the participants of the Transport Engineering Congress (CIT 2012), and an integrated land-use and transport model (LUTI) for Madrid that is called MARS (Metropolitan Activity Relocation Simulator).

Remediation Of 17-α-ethinylestradiol Aqueous Solution By Photocatalysis And Electrochemically-assisted Photocatalysis Using Tio2 And Tio2/wo3 Electrodes Irradiated By A Solar Simulator.

TiO2 and TiO2/WO3 electrodes, irradiated by a solar simulator in configurations for heterogeneous photocatalysis (HP) and electrochemically-assisted HP (EHP), were used to remediate aqueous solutions containing 10 mg L(-1) (34 μmol L(-1)) of 17-α-ethinylestradiol (EE2), active component of most oral contraceptives. The photocatalysts consisted of 4.5 μm thick porous films of TiO2 and TiO2/WO3 (molar ratio W/Ti of 12%) deposited on transparent electrodes from aqueous suspensions of TiO2 particles and WO3 precursors, followed by thermal treatment at 450 (°)C. First, an energy diagram was organized with photoelectrochemical and UV-Vis absorption spectroscopy data and revealed that EE2 could be directly oxidized by the photogenerated holes at the semiconductor surfaces, considering the relative HOMO level for EE2 and the semiconductor valence band edges. Also, for the irradiated hybrid photocatalyst, electrons in TiO2 should be transferred to WO3 conduction band, while holes move toward TiO2 valence band, improving charge separation. The remediated EE2 solutions were analyzed by fluorescence, HPLC and total organic carbon measurements. As expected from the energy diagram, both photocatalysts promoted the EE2 oxidation in HP configuration; after 4 h, the EE2 concentration decayed to 6.2 mg L(-1) (35% of EE2 removal) with irradiated TiO2 while TiO2/WO3 electrode resulted in 45% EE2 removal. A higher performance was achieved in EHP systems, when a Pt wire was introduced as a counter-electrode and the photoelectrodes were biased at +0.7 V; then, the EE2 removal corresponded to 48 and 54% for the TiO2 and TiO2/WO3, respectively. The hybrid TiO2/WO3, when compared to TiO2 electrode, exhibited enhanced sunlight harvesting and improved separation of photogenerated charge carriers, resulting in higher performance for removing this contaminant of emerging concern from aqueous solution.

Does Training Laparoscopic Skills in a Virtual Reality Simulator Improve Surgical Performance?

Background and Purpose: Several different methods of teaching laparoscopic skills have been advocated, with virtual reality surgical simulation (VRSS) being the most popular. Its effectiveness in improving surgical performance is not a consensus yet, however. The purpose of this study was to determine whether practicing surgical skills in a virtual reality simulator results in improved surgical performance. Materials and Methods: Fifteen medical students recruited for the study were divided into three groups. Group I (control) did not receive any VRSS training. For 10 weeks, group II trained basic laparoscopic skills (camera handling, cutting skill, peg transfer skill, and clipping skill) in a VRSS laparoscopic skills simulator. Group III practiced the same skills and, in addition, performed a simulated cholecystectomy. All students then performed a cholecystectomy in a swine model. Their performance was reviewed by two experienced surgeons. The following parameters were evaluated: Gallbladder pedicle dissection time, clipping time, time for cutting the pedicle, gallbladder removal time, total procedure time, and blood loss. Results: With practice, there was improvement in most of the evaluated parameters by each of the individuals. There were no statistical differences in any of evaluated parameters between those who did and did not undergo VRSS training, however. Conclusion: VRSS training is assumed to be an effective tool for learning and practicing laparoscopic skills. In this study, we could not demonstrate that VRSS training resulted in improved surgical performance. It may be useful, however, in familiarizing surgeons with laparoscopic surgery. More effective methods of teaching laparoscopic skills should be evaluated to help in improving surgical performance.

A fieldbus simulator for training purposes

This article presents a fieldbus simulation platform and its remote access interface that enables a wide range of experiments, where users can configure operation sequences and procedures typical of Foundation Fieldbus systems. The simulation system was developed using LabVIEW, with requisites of deterministic execution, and a course management work frame web server called Moodle. The results were obtained through three different evaluations: schedule table execution, simulator functionality and finally, simulator productivity and achievement. The evaluation attests that this new tool is feasible, and can be applied for fieldbus automation systems training purposes, considering the robustness and stability in tests and the positive feedback from users. (C) 2008 ISA. Published by Elsevier Ltd. All rights reserved.

Robust Control of Flight Simulator Motion Base

The purpose of this study is to apply robust inverse dynamics control for a six-degree-of-freedom flight simulator motion system. From an implementation viewpoint, simplification of the inverse dynamics control law is introduced by assuming control law matrices as constants. The robust control strategy is applied in the outer loop of the inverse dynamic control to counteract the effects of imperfect compensation due this simplification. The control strategy is designed using the Lyapunov stability theory. Forward and inverse kinematics and a full dynamic model of a six-degree-of-freedom motion base driven by electromechanical actuators are briefly presented. A describing function, acceleration step response and some maneuvers computed from the washout filter were used to evaluate the performance of the controllers.

The importance of the industrialization of Brazilian shale when faced with the world energy scenario

This article discusses the importance of the industrialization of Brazilian shale based on factors such as: security of the national energy system security, global oil geopoliticsl, resources available, production costs, oil prices, environmental impacts and the national oil reserves. The study shows that the industrialization of shale always arises when issues such as peak oil or its geopolitics appear as factors that raise the price of oil to unrealistic levels. The article concludes that in the Brazilian case, shale oil may be classified as a strategic resource, economically viable, currently in development by the success of the retorting technology for extraction of shale oil and the price of crude oil. The article presents the conclusion that shale may be the driving factor for the formation of a technology park in Sao Mateus do Sul, due to the city`s economic dependence on Petrosix.