2014 IEEE International Energy Conference (ENERGYCON)最新文献_第6页

Comparison of the efficiency of drives with different energy sources for small city buses 小型城市客车不同能源驱动效率的比较

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI: 10.1109/ENERGYCON.2014.6850625

F. Pranjić, Z. Praunseis, P. Virtič

引用次数: 1

Multi-functional high power charging stations in weak grids 弱电网多功能大功率充电站

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI: 10.1109/ENERGYCON.2014.6850602

C. Sourkounis, J. Wenske, F. Turki

引用次数: 0

Open-core Power Voltage Transformer: Concept, properties, application 开芯电源电压互感器:概念、特性、应用

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI: 10.1109/ENERGYCON.2014.6850436

I. Žiger, Boris Bojanić, D. Krajtner

引用次数: 8

Utilizing network QoS for dependability of adaptive smart grid control 利用网络QoS实现自适应智能电网控制的可靠性

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI: 10.1109/ENERGYCON.2014.6850526

J. Madsen, Thomas le Fevre Kristensen, R. Olsen, H. Schwefel, L. Totu

引用次数: 9

Planning an itinerary for an electric vehicle 规划电动汽车的行程

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI: 10.1109/ENERGYCON.2014.6850603

H. Chale-Gongora, Olivier de Weck, Abdelkrim Doufene, T. Ishimatsu, D. Krob

{"title":"Planning an itinerary for an electric vehicle","authors":"H. Chale-Gongora, Olivier de Weck, Abdelkrim Doufene, T. Ishimatsu, D. Krob","doi":"10.1109/ENERGYCON.2014.6850603","DOIUrl":"https://doi.org/10.1109/ENERGYCON.2014.6850603","url":null,"abstract":"The steady increase in oil prices and awareness regarding environmental risks due to carbon dioxide emissions are promoting the current interest in electric vehicles. However, the current relatively low driving range (autonomy) of these vehicles, especially compared with the autonomy of existing internal combustion vehicles, remains an obstacle to their development. In order to reassure a driver of an electric vehicle and allow him to reach his destinations beyond the battery capacity, we describe a system which generates an energy plan for the driver. We present in this paper the electric vehicle ecosystem and we focus on the contribution of using the generalized multi-commodity network flow (GMCNF) model as a vehicle routing model that considers energy consumption and charging time in order to ensure the usage of an electric vehicle beyond its embedded autonomy by selecting the best routes to reach the destination with minimal time and/or cost. We also present some perspectives related to the utilization of autonomous electric vehicles and wireless charging systems. We conclude with some open research questions.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126430786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

A single phase seven-level grid-connected inverter based on three reference SPWM strategy 基于三参考SPWM策略的单相七电平并网逆变器

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI: 10.1109/ENERGYCON.2014.6850432

Bo Sun, Fengjiang Wu, T. Dragičević, J. Guerrero, J. Vasquez

引用次数: 4

Electric vehicle number assessment for year 2020 in Croatia 克罗地亚2020年电动汽车数量评估

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI: 10.1109/ENERGYCON.2014.6850626

M. Vrazic, D. Vuljaj, Arsen Pavasović, H. Paukovic

{"title":"Electric vehicle number assessment for year 2020 in Croatia","authors":"M. Vrazic, D. Vuljaj, Arsen Pavasović, H. Paukovic","doi":"10.1109/ENERGYCON.2014.6850626","DOIUrl":"https://doi.org/10.1109/ENERGYCON.2014.6850626","url":null,"abstract":"For the purpose of researching charging station distribution for electric vehicles it was necessary to estimate the number of electric vehicles, especially cars in Croatia until the year 2020. Electric vehicles are definitely the future of transportation. First these will be cars since they are the most common means of transport. But besides the vehicles, attention should be paid to the best possible preparation in the field of infrastructure. It means that charging stations as well as a different system in vehicles should be standardized. Finally, all that should be built. Of course, different systems and components will be developed at the same time, so it is very hard to predict the future right now. All the above-mentioned greatly depends on the number of electric vehicles predicted for the next 10 years. Of course, the number of electric vehicles that will be sold does not depend only on the offer on the market but also on buyers' purchasing power. Due to everything mentioned so far, it is very hard to predict the number of vehicles sold in the future. On the other hand, such estimations are necessary and they represent the basis for further development of several systems especially infrastructure that needs most time and money for development. This paper will present an estimation of electric vehicle sale in Croatia as well as all the conditions and assumptions used for that estimation.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"49 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128836871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Transmission pricing in interconnected systems - A case study of the Nordic countries 互联系统中的输电定价——北欧国家的案例研究

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI: 10.1109/ENERGYCON.2014.6850618

K. Ostman, M. Hesamzadeh

引用次数: 2

Prediction of wind park output power based on turbine effective wind speed - a model identification approach 基于风力机有效风速的风电场输出功率预测——一种模型辨识方法

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI: 10.1109/ENERGYCON.2014.6850466

I. Munteanu, G. Besançon

引用次数: 2

Hybrid forecasting model of power demand based on three-stage synthesis and stochastically self-adapting mechanism 基于三阶段综合和随机自适应机制的电力需求混合预测模型

2014 IEEE International Energy Conference (ENERGYCON) Pub Date : 2014-05-13 DOI: 10.1109/ENERGYCON.2014.6850468

Shuping Dang, Jiahong Ju, L. Baker, A. Gholamzadeh, Yizhi Li

{"title":"Hybrid forecasting model of power demand based on three-stage synthesis and stochastically self-adapting mechanism","authors":"Shuping Dang, Jiahong Ju, L. Baker, A. Gholamzadeh, Yizhi Li","doi":"10.1109/ENERGYCON.2014.6850468","DOIUrl":"https://doi.org/10.1109/ENERGYCON.2014.6850468","url":null,"abstract":"The power demand over the electrical power system and smart grid is a random function in the time domain which is affected by a larger number of stochastic factors, for example weather, date and economy as well as a series of unpredictable human factors. Therefore, the most convenient and efficient methodology to forecast the power demand is a stochastic model based on statistics and fuzzy mathematics, because it can merge all complex factors which are difficult or even impossible to be modelled mathematically into an appropriate correction variable. In this paper, we will introduce a hybrid forecasting model of power demand which separates the forecasting process into three stages, i.e. long-term, middle-term and short-term analysis. Most of the long-term factors will be combined in a comprehensive correction factor for the middle-term stage. In the middle-term stage the forecasting mechanism integrates several different forecasting principles and methods to produce a combined forecasting result and dynamically adjusts its forecasting scheme by different weights for different forecasting methods by measuring and comparing the forecasting result and its corresponding practical measurement. By this self-adapting algorithm, the forecasting model is able to forecast the next 24-hour power demand via using the historical data obtained in its database. In the short-term stage, a fine adjustment mechanism will be involved to enhance the reliability and robustness of the holistic forecasting mechanism.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127108621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12