Pub Date : 2014-05-13DOI: 10.1109/ENERGYCON.2014.6850432
Bo Sun, Fengjiang Wu, T. Dragičević, J. Guerrero, J. Vasquez
This paper introduce a seven level grid connected system based on the TRSPWM strategy and a Quasi PR current controller has a good output performance with a fast response and compensation for the low order harmonics in grid. With the multilevel output voltage and a high tracking current strategy with a low-order harmonic compensator, the grid connected system could operate properly in a polluted grid with low order harmonic. The simulation based on MATLAB verify the proposed the accuracy and feasibility of the proposed scheme.
{"title":"A single phase seven-level grid-connected inverter based on three reference SPWM strategy","authors":"Bo Sun, Fengjiang Wu, T. Dragičević, J. Guerrero, J. Vasquez","doi":"10.1109/ENERGYCON.2014.6850432","DOIUrl":"https://doi.org/10.1109/ENERGYCON.2014.6850432","url":null,"abstract":"This paper introduce a seven level grid connected system based on the TRSPWM strategy and a Quasi PR current controller has a good output performance with a fast response and compensation for the low order harmonics in grid. With the multilevel output voltage and a high tracking current strategy with a low-order harmonic compensator, the grid connected system could operate properly in a polluted grid with low order harmonic. The simulation based on MATLAB verify the proposed the accuracy and feasibility of the proposed scheme.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"4 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":"130076187","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}
Pub Date : 2014-05-13DOI: 10.1109/ENERGYCON.2014.6850626
M. Vrazic, D. Vuljaj, Arsen Pavasović, H. Paukovic
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.
{"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}
Pub Date : 2014-05-13DOI: 10.1109/ENERGYCON.2014.6850494
I. Ramljak, M. Majstrović, E. Sutlovic
Fire ignition as a consequence of conductor clashing has happened in many countries all over the world. These fires can cause severe environmental (forest fires) and financial damage, and even be potential life-threatening. The goal of the article is to describe the processes which occur when two live conductor clash together. The most dangerous product of conductor clashing are particles (sparks), which fall to the ground, while being hot enough to potentially start a fire. Primary, by defining of those sparks we can do the first step which would lead to the answer: “Is conductor clashing the cause of fires?” Conductor clashing was simulated in two environmental conditions. The first one was in a live low voltage electricity distribution network as line-to-line short circuit and the second one was in laboratory conditions. Al/Fe conductors of the same characteristics were used in both simulations. Simulations were recorded with high speed camera. Statistical analysis of particles and their probability density function (PDF) are presented in this paper. PDF calculation may be a part of additional criteria on power system protection adjustment.
{"title":"Statistical analysis of particles of conductor clashing","authors":"I. Ramljak, M. Majstrović, E. Sutlovic","doi":"10.1109/ENERGYCON.2014.6850494","DOIUrl":"https://doi.org/10.1109/ENERGYCON.2014.6850494","url":null,"abstract":"Fire ignition as a consequence of conductor clashing has happened in many countries all over the world. These fires can cause severe environmental (forest fires) and financial damage, and even be potential life-threatening. The goal of the article is to describe the processes which occur when two live conductor clash together. The most dangerous product of conductor clashing are particles (sparks), which fall to the ground, while being hot enough to potentially start a fire. Primary, by defining of those sparks we can do the first step which would lead to the answer: “Is conductor clashing the cause of fires?” Conductor clashing was simulated in two environmental conditions. The first one was in a live low voltage electricity distribution network as line-to-line short circuit and the second one was in laboratory conditions. Al/Fe conductors of the same characteristics were used in both simulations. Simulations were recorded with high speed camera. Statistical analysis of particles and their probability density function (PDF) are presented in this paper. PDF calculation may be a part of additional criteria on power system protection adjustment.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"13 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":"128199485","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}
Pub Date : 2014-05-13DOI: 10.1109/ENERGYCON.2014.6850603
H. Chale-Gongora, Olivier de Weck, Abdelkrim Doufene, T. Ishimatsu, D. Krob
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.
{"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}
Pub Date : 2014-05-13DOI: 10.1109/ENERGYCON.2014.6850468
Shuping Dang, Jiahong Ju, L. Baker, A. Gholamzadeh, Yizhi Li
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.
{"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}
Pub Date : 2014-05-13DOI: 10.1109/ENERGYCON.2014.6850430
A. Hammoda, Mohammed Buamud, M. Nasr, M. Tamasas
The aim of this paper is to estimate and evaluate the dc/dc converters based on Energy factor and sub-sequential parameters to obtain mathematical model of power DC/DC converters (second order transfer function for any number of capacitors and inductors). The Elementary of positive output voltage-lift DC/DC Luo-converter and two stages positive output cascade boost converter super-lift DC/DC Luo-converter are chosen as the main focus case study of this paper. A computer simulation using NI SIMULINK results have been presented to verify the presented theoretical analysis.
{"title":"Estimation of advanced DC/DC Luo-converters based on Energy factor and sub-sequential parameters","authors":"A. Hammoda, Mohammed Buamud, M. Nasr, M. Tamasas","doi":"10.1109/ENERGYCON.2014.6850430","DOIUrl":"https://doi.org/10.1109/ENERGYCON.2014.6850430","url":null,"abstract":"The aim of this paper is to estimate and evaluate the dc/dc converters based on Energy factor and sub-sequential parameters to obtain mathematical model of power DC/DC converters (second order transfer function for any number of capacitors and inductors). The Elementary of positive output voltage-lift DC/DC Luo-converter and two stages positive output cascade boost converter super-lift DC/DC Luo-converter are chosen as the main focus case study of this paper. A computer simulation using NI SIMULINK results have been presented to verify the presented theoretical analysis.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"87 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":"126303207","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}
Pub Date : 2014-05-13DOI: 10.1109/ENERGYCON.2014.6850439
P. Chusovitin, A. Pazderin
The paper presents results of the research devoted to PMU-based power system small-signal stability monitoring. Proposed method allows tracking in-phase groups of generators and critical generators in the groups by analyzing low-frequency oscillations. Further developed, method is able to identify proximity to power system stability boundary. The technique developed is based on power system equivalent model identification. Identification procedure exploits PMU data. In the paper, applicability of the technique is demonstrated using 9-node power system model.
{"title":"Small-signal stability monitoring using PMU","authors":"P. Chusovitin, A. Pazderin","doi":"10.1109/ENERGYCON.2014.6850439","DOIUrl":"https://doi.org/10.1109/ENERGYCON.2014.6850439","url":null,"abstract":"The paper presents results of the research devoted to PMU-based power system small-signal stability monitoring. Proposed method allows tracking in-phase groups of generators and critical generators in the groups by analyzing low-frequency oscillations. Further developed, method is able to identify proximity to power system stability boundary. The technique developed is based on power system equivalent model identification. Identification procedure exploits PMU data. In the paper, applicability of the technique is demonstrated using 9-node power system model.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"1 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":"122538433","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}
Pub Date : 2014-05-13DOI: 10.1109/ENERGYCON.2014.6850585
Edgar Galván-López, C. Harris, L. Trujillo, K. Rodríguez-Vázquez, S. Clarke, V. Cahill
Smart Grid (SG) technologies are becoming increasingly dynamic, motivating the use of computational intelligence to support the SG by predicting and intelligently responding to certain requests (e.g, reducing electricity costs given fluctuating prices). The presented work intends to do precisely this, to make intelligent decisions to switch on electric devices at times when the electricity price (prices that change over time) is the lowest while at the same time attempting to balance energy usage by avoiding turning on multiple devices at the same time, whenever possible. To this end, we use Monte Carlo Tree Search (MCTS), a real-time decision algorithm. MCTS takes into consideration what might happen in the future by approximating what other entities/agents (electric devices) might do via Monte Carlo simulations. We propose two variants of this method: (a) maxn MCTS approach where the competition for resources (e.g, lowest electricity price) happens in one single decision tree and where all the devices are considered, and (b) two-agent MCTS approach, where the competition for resources is distributed among various decision trees. To validate our results, we used two scenarios, a rather simple one where there are no constraints associated to the problem, and another more complex, and realistic scenario with equality and inequality constraints associated to the problem. The results achieved by this real-time decision tree algorithm are very promising, specially those achieved by the maxn MCTS approach.
{"title":"Autonomous Demand-Side Management system based on Monte Carlo Tree Search","authors":"Edgar Galván-López, C. Harris, L. Trujillo, K. Rodríguez-Vázquez, S. Clarke, V. Cahill","doi":"10.1109/ENERGYCON.2014.6850585","DOIUrl":"https://doi.org/10.1109/ENERGYCON.2014.6850585","url":null,"abstract":"Smart Grid (SG) technologies are becoming increasingly dynamic, motivating the use of computational intelligence to support the SG by predicting and intelligently responding to certain requests (e.g, reducing electricity costs given fluctuating prices). The presented work intends to do precisely this, to make intelligent decisions to switch on electric devices at times when the electricity price (prices that change over time) is the lowest while at the same time attempting to balance energy usage by avoiding turning on multiple devices at the same time, whenever possible. To this end, we use Monte Carlo Tree Search (MCTS), a real-time decision algorithm. MCTS takes into consideration what might happen in the future by approximating what other entities/agents (electric devices) might do via Monte Carlo simulations. We propose two variants of this method: (a) maxn MCTS approach where the competition for resources (e.g, lowest electricity price) happens in one single decision tree and where all the devices are considered, and (b) two-agent MCTS approach, where the competition for resources is distributed among various decision trees. To validate our results, we used two scenarios, a rather simple one where there are no constraints associated to the problem, and another more complex, and realistic scenario with equality and inequality constraints associated to the problem. The results achieved by this real-time decision tree algorithm are very promising, specially those achieved by the maxn MCTS approach.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"67 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":"122815035","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}
Pub Date : 2014-05-13DOI: 10.1109/ENERGYCON.2014.6850483
M. Moradzadeh, B. Zwaenepoel, J. Van de Vyver, L. Vandevelde
Allowing the connection of additional renewable energy sources (RES) in areas with limited transmission capacity is becoming of a serious concern. Building new transmission lines only provides a long-term solution to cope with this issue due to the fact that it takes much longer time (up to 5-10 years) compared to time needed to build new wind farms (about 1 year). Storage is proven to be an effective solution to make maximal use of existing grid infrastructures in the short-term. This paper proposes a cost-benefit optimization formulation for optimally sizing the storage in a wind-storage system which is connected to an external spot market via limited transmission lines. A small test system is studied in order to find the optimal size of storage to avoid congestion by allowing revenue to be generated only via reducing the congestion-induced wind curtailment. Additional revenue streams can be also included to maximize the monetary value of the wind-storage system.
{"title":"Congestion-induced wind curtailment mitigation using energy storage","authors":"M. Moradzadeh, B. Zwaenepoel, J. Van de Vyver, L. Vandevelde","doi":"10.1109/ENERGYCON.2014.6850483","DOIUrl":"https://doi.org/10.1109/ENERGYCON.2014.6850483","url":null,"abstract":"Allowing the connection of additional renewable energy sources (RES) in areas with limited transmission capacity is becoming of a serious concern. Building new transmission lines only provides a long-term solution to cope with this issue due to the fact that it takes much longer time (up to 5-10 years) compared to time needed to build new wind farms (about 1 year). Storage is proven to be an effective solution to make maximal use of existing grid infrastructures in the short-term. This paper proposes a cost-benefit optimization formulation for optimally sizing the storage in a wind-storage system which is connected to an external spot market via limited transmission lines. A small test system is studied in order to find the optimal size of storage to avoid congestion by allowing revenue to be generated only via reducing the congestion-induced wind curtailment. Additional revenue streams can be also included to maximize the monetary value of the wind-storage system.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"32 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":"127749216","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}
Pub Date : 2014-05-13DOI: 10.1109/ENERGYCON.2014.6850566
M. Celidonio, E. Fionda, L. Pulcini, E. Sergio, D. Di Zenobio
In the context of the FP7 CIP-ICT Programme, the EDISON project1 has the ambitious goal to introduce a new way of thinking lighting networks in buildings, for both retrofitting actions and new constructions. It proposes an innovative ICT-based solution for lighting infrastructure that aims to improve power efficiency, reduce CO2 emissions and encourage the use of small-scale renewable energy sources in public and private buildings. In particular, this paper focuses on a relevant aspect of the EDISON solution: the centralization of DC power supply in a LED lighting infrastructure. To this aim, a short analysis has been carried out in order to give evidence of the benefits arising from the application of this approach. Finally, preliminary results achieved in targeted Pilot actions, implemented in different European countries, have been reported.
{"title":"A centralised DC power supply solution for LED lighting networks","authors":"M. Celidonio, E. Fionda, L. Pulcini, E. Sergio, D. Di Zenobio","doi":"10.1109/ENERGYCON.2014.6850566","DOIUrl":"https://doi.org/10.1109/ENERGYCON.2014.6850566","url":null,"abstract":"In the context of the FP7 CIP-ICT Programme, the EDISON project1 has the ambitious goal to introduce a new way of thinking lighting networks in buildings, for both retrofitting actions and new constructions. It proposes an innovative ICT-based solution for lighting infrastructure that aims to improve power efficiency, reduce CO2 emissions and encourage the use of small-scale renewable energy sources in public and private buildings. In particular, this paper focuses on a relevant aspect of the EDISON solution: the centralization of DC power supply in a LED lighting infrastructure. To this aim, a short analysis has been carried out in order to give evidence of the benefits arising from the application of this approach. Finally, preliminary results achieved in targeted Pilot actions, implemented in different European countries, have been reported.","PeriodicalId":410611,"journal":{"name":"2014 IEEE International Energy Conference (ENERGYCON)","volume":"90 2 Pt 1 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":"129178570","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}
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