Method to evaluate solutions for complex systems: rail energy

Many solutions have been developed to reduce energy consumption in rail, covering the three main areas of rolling stock, infrastructure and operations. These solutions often show significant energy savings in theory, simulation and practice. However, the success of a solution can only be evaluated within the scope of the study performed, which is limited to specific case studies. Because railways vary greatly, a solution deemed effective when applied to one railway may not be well suited to another, due to inherent differences. This work therefore aims to develop a method to evaluate solutions for complex systems, using energy saving in rail as an example. Distinct subsystems are quantitatively defined by determining the factors that make them unique. For rail, these are categorised into route, vehicle and service characteristics. Next, key performance indicators are identified that relate to the success of solutions. Finally, a sensitivity analysis is performed to evaluate which factors influence solutio...

[1]  A. Saltelli,et al.  An alternative way to compute Fourier amplitude sensitivity test (FAST) , 1998 .

[2]  Andrea Saltelli,et al.  From screening to quantitative sensitivity analysis. A unified approach , 2011, Comput. Phys. Commun..

[3]  Sigrid Reiter,et al.  A performance comparison of sensitivity analysis methods for building energy models , 2015 .

[4]  Phil Howlett,et al.  Coasting boards vs optimalcontrol , 2010 .

[5]  Minoru Kondo,et al.  Development of a High Efficiency Induction Motor and the Estimation of Energy Conservation Effect , 2014 .

[6]  Takafumi Fukushima,et al.  Traction systems using power electronics for Shinkansen High-speed Electric Multiple Units , 2010, The 2010 International Power Electronics Conference - ECCE ASIA -.

[7]  Paul Batty,et al.  Sustainable urban rail systems: strategies and technologies for optimal management of regenerative braking energy , 2013 .

[8]  G. McFadden.  Sustainability and carbon reduction on electrified railways , 2010 .

[9]  Felix Schmid,et al.  The Impact of Different Maximum Speeds on Journey Times, Energy Use, Headway Times and the Number of Trains Required for Phase One of Britain’s High Speed Two Line , 2014 .

[10]  M. Kondo,et al.  Rotor design for high efficiency induction motors for railway vehicle traction , 2009, 2009 International Conference on Electrical Machines and Systems.

[11]  Felix Schmid,et al.  A review of methods to measure and calculate train resistances , 2000 .

[12]  Andrea Saltelli,et al.  An effective screening design for sensitivity analysis of large models , 2007, Environ. Model. Softw..

[13]  Daniel Emery,et al.  Railway driver advice systems: Evaluation of methods, tools and systems , 2013, J. Rail Transp. Plan. Manag..

[14]  Felix Schmid,et al.  An assessment of available measures to reduce traction energy use in railway networks , 2015 .

[15]  Paul Batty,et al.  A systems approach to reduce urban rail energy consumption , 2014 .

[16]  I. Sobola,et al.  Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates , 2001 .

[17]  Marco Taisch,et al.  Energy management in production: A novel method to develop key performance indicators for improving energy efficiency , 2015 .

[18]  Koichi Matsuoka,et al.  Energy Saving Technologies for Railway Traction Motors , 2010 .

[19]  R. R. Pecharromán,et al.  Assessment of energy-saving techniques in direct-current-electrified mass transit systems , 2014 .

[20]  Nicolas Urien.  Energy Optimization for Public Transportation Applications , 2013 .

[21]  D. Kirschner,et al.  A methodology for performing global uncertainty and sensitivity analysis in systems biology. , 2008, Journal of theoretical biology.

[22]  Halina Koczyk,et al.  Sensitivity analysis in determining the optimum energy for residential buildings in Polish conditions , 2015 .

[23]  A. Saltelli,et al.  Making best use of model evaluations to compute sensitivity indices , 2002 .