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| Tekkaya, A. Erman |
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| Förster, Peter |
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| Mudimu, George T. |
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| Shibata, Lillian Marie |
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| Talabbeydokhti, Nasser |
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| Laffite, Ernesto Dante Rodriguez |
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| Schöpke, Benito |
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| Gobis, Anna |
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| Alfares, Hesham K. |
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| Münzel, Thomas |
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| Joy, Gemini Velleringatt |
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| Oubahman, Laila |
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| Filali, Youssef |
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| Philippi, Paula |
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| George, Alinda |
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| Lucia, Caterina De |
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| Avril, Ludovic |
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| Belachew, Zigyalew Gashaw |
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| Kassens-Noor, Eva | Darmstadt |
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| Cho, Seongchul |
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| Tonne, Cathryn |
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| Hosseinlou, Farhad |
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| Ganvit, Harsh |
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| Schmitt, Konrad Erich Kork |
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| Grimm, Daniel |
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Vale, Z.
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (20/20 displayed)
- 2019Dynamic electricity tariff definition based on market price, consumption and renewable generation patternscitations
- 2019Electric Vehicles' User Charging Behaviour Simulator for a Smart Citycitations
- 2018Energy flexibility assessment of a multi agent-based smart home energy systemcitations
- 2018Day-ahead stochastic scheduling model considering market transactions in smart gridscitations
- 2018Data Mining for Prosumers Aggregation considering the Self-Generationcitations
- 2018Dynamic electricity tariff definition based on market price, consumption and renewable generation patterns
- 2018Customized normalization clustering methodology for consumers with heterogeneous characteristicscitations
- 2018A New Hybrid-Adaptive Differential Evolution for a Smart Grid Application under Uncertaintycitations
- 2017Smart city: A GECAD-BISITE energy management case studycitations
- 2016Real-time simulation of renewable energy transactions in microgrid context using real hardware resourcescitations
- 2016Customized Normalization Method to Enhance the Clustering Process of Consumption Profilescitations
- 2016Scenario generation for electric vehicles' uncertain behavior in a smart city environmentcitations
- 2016A multi-objective model for the day-ahead energy resource scheduling of a smart grid with high penetration of sensitive loadscitations
- 2015Energy resource management under the influence of the weekend transition considering an intensive use of electric vehiclescitations
- 2015Data Mining approach for Decision Support in real data based Smart Grid scenariocitations
- 2015Coalition of distributed generation units to Virtual Power Players - a game theory approachcitations
- 2014Realistic Traffic Scenarios Using a Census Methodology: Vila Real Case Studycitations
- 2014A hybrid simulated annealing approach to handle energy resource management considering an intensive use of electric vehiclescitations
- 2012Intelligent Electric Vehicle Heuristic for Energy Resource Management using Simulated Annealingcitations
- 2012A multi-agent based approach for intelligent smart grid management
Places of action
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document
Realistic Traffic Scenarios Using a Census Methodology: Vila Real Case Study
Abstract
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.
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