| 1. |
- Abrahamson, Lars, et al.
(author)
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Fast calculation of the dimensioning factors of the railway power supply system
- 2007
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In: Computational Methods and Experimental Measurements XIII. - : WIT Press. - 9781845640842 ; , s. 85-95
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Conference paper (peer-reviewed)abstract
- Because of environmental and economical reasons, in Sweden and the rest of Europe, both personal and goods transports on railway are increasing. Therefore great railway infrastructure investments are expected to come. An important part of this infrastructure is the railway power supply system. Exactly how much, when and where the traffic will increase is not known for sure. This means investment planning for an uncertain future. The more uncertain parameters, such as traffic density and weight of trains, and the further future considered, the greater the inevitable amount of cases that have to be considered. When doing simulations concerning a tremendous amount of cases, each part of the simulation model has to be computationally fast - in real life this means approximations. The two most important issues to estimate given a certain power system configuration, when planning for an electric traction system, are the energy consumption of the and and the train delays that a too weak system would cause. In this paper, some modeling suggestions of the energy consumption and the maximal train velocities are presented. Two linear, and one nonlinear model are presented and compared. The comparisons regard both computer speed and representability. The independent variables of these models are a selection of parameters describing the power system, i.e.: power system technology used on each section, and traffic intensity.
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| 2. |
- Abrahamsson, Lars, et al.
(author)
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Basic modeling for electric traction systems under uncertainty
- 2006
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In: PROCEEDINGS OF THE 41ST INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE, VOLS 1 AND 2. - NEW YORK : IEEE. - 9781861353429 ; , s. 252-256
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Conference paper (peer-reviewed)abstract
- The objective of this paper is initially to present a basic modeling of the railway traction system. This model includes the basic technologies used today. The voltage dependencies of the maximal possible power consumption as well as the maximal velocity of the common Re-locomotives are included. The latter is very crucial for the studies of time table sensitivity, which is of our immediate interest. Moreover, a method is presented, that estimates the expected train delay time for a given feeding technology. The reference timetable assumes the same train and surrounding conditions, but no voltage drops. In the numerical example where the developed model is applied to a realistic test system, a set of possible amounts of railway traffic are treated as uncertainties. Mainly, the contributions of this paper are three: compiling and connecting already accepted models, the development of a method for numerical calculations using this model compilation, and an example to apply this model on.
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| 3. |
- Abrahamsson, Lars, et al.
(author)
-
Fast calculation of some important dimensioning factors of the railway power supply system
- 2007
-
Conference paper (peer-reviewed)abstract
- Because of environmental and economical reasons, in Sweden and the rest of Europe, both personal and goods transports on railway are increasing. Therefore great railway infrastructure investments are expected to come. An important part of this infrastructure is the railway power supply system. Exactly how much, when and where the traffic will increase is not known for sure. This means investment planning for an uncertain future. The more uncertain parameters, such as traffic density and weight of trains, and the further future considered, the greater the inevitable amount of cases that have to be considered. When doing simulations concerning a tremendous amount of cases, each part of the simulation model has to be computationally fast – in real life this means approximations. The two most important issues to estimate given a certain power system configuration, when planning for an electric traction system, are the energy consumption of the grid and the train delays that a too weak system would cause. In this paper, some modeling suggestions of the energy consumption and the maximal train velocities are presented. Two linear models, and one nonlinear model are presented and compared. The comparisons regard both computer speed and representability. The independent variables of these models are a selection of parameters describing the power system, i.e.: power system technology used on each section, and traffic intensity.
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| 4. |
- Abrahamsson, Lars, et al.
(author)
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Fast estimation of the relation between aggregated train power system information and the power and energy converted
- 2008
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In: 2008 Australasian Universities Power Engineering Conference, AUPEC 2008. - : IEEE conference proceedings. - 9781424441624 ; , s. 1-6
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Conference paper (peer-reviewed)abstract
- Transports on rail are increasing and major investments in the railway infrastructure, including the Railway Power Supply System (RPSS), are expected. The future railway power demands are naturally not known for certain. The more remote the uncertain future, the greater the number of scenarios that have to be considered. Large numbers of scenarios make time demanding simulations unattractive. The aim of this paper is to present a fast approximator that uses aggregated RPSS information. Since the electrical and mechanical relations governing an RPSS are quite intricate, an approximator based on Neural Networks (NN), is applied. This paper presents a design suggestion for an NN estimating the power and energy flows through each converter station, given RPSS data and levels of train traffic. Even if the future usage of the NN is investment planning, the modeling of such an approximator has a value in itself concerning the understanding of the relations between RPSS and train traffic.
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| 5. |
- Abrahamsson, Lars, et al.
(author)
-
Fast estimation of the relation between aggregated train power system information and the power and energy converted
- 2009
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In: Australian Journal of Electrical and Electronic Engineering. - 1448-837X. ; 6:3, s. 311-318
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Journal article (peer-reviewed)abstract
- Transports on rail are increasing and major investments in the railway infrastructure, including the railway power supply system (RPSS), are expected. The future railway power demands are naturally not known for certain. The more remote the uncertain future, the greater the number of scenarios that have to be considered. Large numbers of scenarios make time-demanding simulations unattractive. The aim of this paper is to present a fast approximator that uses aggregated RPSS information. Since the electrical and mechanical relations governing an RPSS are quite intricate, an approximator based on neural networks (NN) is applied. This paper presents a design suggestion for an NN estimating the power and energy flows through each converter station, given RPSS data and levels of train traffic. Even if the future usage of the NN is investment planning, the modelling of such an approximator has a value in itself concerning the understanding of the relations between RPSS and train traffic.
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| 6. |
- Abrahamsson, Lars, et al.
(author)
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Operation simulation of traction systems
- 2008
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In: COMPUTERS IN RAILWAYS XI. ; , s. 283-292
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Conference paper (peer-reviewed)abstract
- The objective of this paper is initially to present a basic modeling of the railway traction system. This model includes the basic technologies used today. The voltage dependencies of the maximal possible power consumption as well as the maximal velocity of the common Rc-locomotives are included. The latter is very crucial for the studies of time table sensitivity, which is of our immediate interest. Moreover, a method is presented that estimates the expected train delay time for a given feeding technology. The reference timetable assumes the same train and surrounding conditions, but no voltage drops. In the numerical example where the developed model is applied to a realistic test system, a set of possible amounts of railway traffic are treated as uncertainties. Mainly, the contributions of this paper are three: compiling and connecting already accepted models, the development of a method for numerical calculations using this model compilation, and an example to apply this model on.
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| 7. |
- Abrahamsson, Lars, et al.
(author)
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Railway power supply investment decisions considering the voltage drops : Assuming the future traffic to be known
- 2009
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In: 2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09. - 9781424450985
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Conference paper (other academic/artistic)abstract
- Transports on rail are increasing and major railway infrastructure investments are expected. An important part of this infrastructure is the railway power supply system. The future railway power demands are naturally not known for certain. The more distant the uncertain future is, the greater the number of scenarios that have to be considered. Large numbers of scenarios make time demanding simulations unattractive. Therefore a fast approximator that uses aggregated railway power supply system information has been developed. In particular the approximator studies the impacts of voltage drops on the traffic flow. The weaker the power system and the heavier the traffic, the greater the voltage drops. And the greater the voltage drops, the more limited the maximal attainable tractive force on the locomotives. That approximator is in this paper used as a constraint in the embryo of a railway power supply system investment planning program, where investment decisions are assumed to be realized immediately, and there is no preexisting power supply system to consider. The traffic forecasts are in this first approach assumed to be perfect. This stepwise creation of the planning program makes evaluating it easier. The basic investment planning model presented here constitutes the foundation for further improvements.
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| 8. |
- Abrahamsson, Lars, 1979-
(author)
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Railway Power Supply Models and Methods for Long-term Investment Analysis
- 2008
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Licentiate thesis (other academic/artistic)abstract
- The aim of the project is to suggest an investment planning programwhere the welfare of the society is to be maximized. In order to beable to decide on a wise investment plan, one needs to know theconsequences of different choices of power system configurations.Therefore the impacts of different future traffic demands are ofinterest for a railway power system owner.Since investments are supposed to last a long time, their futureusage has to be considered. Moreover, the lead times of investmentscan be of considerable duration lengths. Because of the uncertaintyof the future, deterministic case studies might not be suitable andthen a large number of outcomes are to be studied, probable outcomesas well as outcomes with a high level of impact.In order to be able to make a valid long-term investment analysis ofthe railway power supply system, one needs to use proper railwaypower supply models and methods. The aim of this thesis is topresent a stable modeling and methodological basis for the cominginvestment planning phase of this PhD research project. The focus isset on studying the consequences of a railway power supply systemwhich is too weak.The thesis contains an overview of models of some electrical andmechanical relations important for electric traction systems. Someof these models are further developed, and some are modified forimproved computational properties. A flexible electric tractionsystem simulator based on the above mentioned models has beendeveloped and the applied methods and resulting abilities arepresented.The main scientific contribution of this thesis is that a fast andapproximative neural network model, which calculates some importantaggregated results of the interaction between the railway powersystem and the train traffic, has been developed. This approximativemodel was developed in order to reduce computation times. Reductionof computation times is very important when a huge number ofoutcomes are studied. A complete simulation of a train power systemin operation takes a long time, often not less than about a tenth ofthe simulated traffic time. The neural network is trained with someselected aggregated results extracted from a wide set of railwayoperation simulation cases. The choices of network inputs andoutputs are motivated in the thesis. The performance of thesimulator as well as the approximator are visualized in casestudies.
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| 9. |
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| 10. |
- Ali, Muhammad, et al.
(author)
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Effect of wake consideration on estimated costs of wind energy curtailments
- 2009
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In: 8th International Workshop on Large Scale Integration of Wind Power into Power Systems as well as on Transmission Networks of Offshore Wind Farms, 14-15 Oct. 2009 Bremen.
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Conference paper (peer-reviewed)abstract
- Measures such as energy curtailment or gridreinforcement are required to integrate the upcoming windgeneration in parts of the power system with existing transmissionbottlenecks. In order to choose between these two measurespotential wind energy curtailments and its costs need to becarefully evaluated. The paper analyzes the effect of wakeconsideration on the overall energy curtailment cost. For thispurpose detailed wake model was used taking into account partialand multiple shading of wind turbines. It is shown that not onlywind speed but also wind direction of the incoming wind affects theamount of energy produced by a wind farm. A comparison ofcurtailment cost with cost for grid reinforcement in areas withlimited transmission capacity was carried out with and withoutconsideration of wake effect. The effect on curtailment cost due toavailability of wind turbines is also investigated both with andwithout wake effect consideration. The results have proven thatwith consideration of wake effect and availability potential windenergy curtailments are reduced and hence curtailment costs arelowered, making curtailment a cheaper option than gridreinforcement. The method illustrated in the paper can be used inpre-feasibility study to compare the costs of wind curtailment withthe costs of grid reinforcement in order to make sound economicdecision. The method can also be applied in wind farm energy yield estimation.
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