Energy Management for an Onboard Storage System Based on Multi-Objective Optimization

The power consumption of a tram is characterized by distinct peaks combined with a low average value. Using an onboard energy storage, the overhead line peak power and energy consumption can be reduced. The storage device introduces a degree of freedom for control of the power flow. To incorporate the freedom an energy management is required. The design of the energy management can be seen as a multi-objective optimization problem with the objectives "minimize line peak power" and "minimize energy consumption". As common to most multi-objective optimization problems it is not possible to minimize both objectives at the same time. The results of the optimization problem can be described by a Pareto set, from which one Pareto point has to be selected depending on the weights of the objectives. As one Pareto set only represents the solution to a fixed set of system parameters, in case of parameter variations an adaptation process is necessary. This process can be realized by using an operator-controller-module, which consists of a cognitive part for planning tasks with lower real-time requirements and a reflective part for the execution level

[1]  M. Steiner,et al.  Energy storage on board of railway vehicles , 2005, 2005 European Conference on Power Electronics and Applications.

[2]  J. Bocker,et al.  Self-Optimization as a Framework for Advanced Control Systems , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[3]  Holger Giese,et al.  Structured Information Processing for Self-Optimizing Mechatronic Systems , 2004, ICINCO.

[4]  M. Dellnitz,et al.  Covering Pareto Sets by Multilevel Subdivision Techniques , 2005 .

[5]  Alfred Rufer,et al.  Hybrid vehicle in railways applications: supercapacitive energy storage for diesel-electric locomotives , 2004 .

[6]  C. Hillermeier Nonlinear Multiobjective Optimization: A Generalized Homotopy Approach , 2001 .

[7]  A. Dell'Aere Multi-Objective Optimization in Self-Optimizing Systems , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[8]  Alfred Rufer,et al.  The use of supercapacitors for energy storage in traction systems , 2004 .

[9]  Jürgen Teich,et al.  Covering Pareto Sets by Multilevel Evolutionary Subdivision Techniques , 2003, EMO.

[10]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[11]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[12]  Oliver Schütze,et al.  A New Data Structure for the Nondominance Problem in Multi-objective Optimization , 2003, EMO.

[13]  Oliver Schütze,et al.  On Continuation Methods for the Numerical Treatment of Multi-Objective Optimization Problems , 2005, Practical Approaches to Multi-Objective Optimization.

[14]  Claus Hillermeier,et al.  Nonlinear Multiobjective Optimization , 2001 .

[15]  Matthias Ehrgott,et al.  Multicriteria Optimization , 2005 .